towards key variables to assess national spatial data ......nebert, jos van orshoven, bebas purnawa,...

Towards key variables

to assess National Spatial Data Infrastructures (NSDIs)

in developing countries

Lyande Eelderink

I

Abstract

This research explores how to select a common set of measurable key variables that can be utilised to assess National Spatial Data Infrastructures (NSDIs) in developing countries. This is investigated, based on NSDI case studies of six different developing countries (Colombia, Cuba, Nepal, Indonesia, Nigeria and Ethiopia) from three different continents (Latin America, Asia and Africa). Spatial Data Infrastructures (SDIs) are developed by many countries to better manage and utilise spatial datasets (Rajabifard, 2003). Although many countries claim that they are involved in SDI development, Masser (2005) asserts that these claims need to be treated with caution. Engagement in SDI development does not necessarily mean that the initiative will translate into a fully operational SDI over time. Nevertheless, during the last few years, considerable resources have been spent creating optimal SDIs (Crompvoets, 2003). Developing countries are initiating projects for NSDI development as well. The main difficulties when establishing and implementing NSDIs in developing countries are related to the lack of appreciation, the lack of resources and trained personnel, inefficient bureaucratic processes, and the lack of data (Rajabifard and Williamson, 2003). Up to now efforts to develop NSDIs have not been audited or evaluated systematically (Crompvoets, 2004). To address this gap, Wageningen University, Delft University of Technology, and the University of Melbourne in Australia, have embarked upon a project to develop a framework for worldwide assessment of NSDIs. The application of such a framework would support the establishment and implementation of efficient, effective and coherent NSDIs in both developed and developing countries. Since each country is unique in historical, legal, economic, technological, cultural and institutional terms, the benefits gained and bottlenecks expected for the establishment and implementation of NSDIs are likely to be different as well. Hence, not only effective strategies for establishing and implementing NSDIs may be country-specific but also NSDIs themselves may be different for each country. In order to interpret such differences, this research assumes that a common set of measurable key variables to assess NSDIs is needed. The research problem is, therefore, how to define this set of key variables. In this research, a considerable number of initial variables to assess NSDIs are identified based on critically reviewing existing assessment frameworks. After thoroughly reviewing the six case study countries, from the initially identified list of variables, a reduced list of measurable feasible variables has been developed. Following on from the review of the NSDI initiatives in the three continents and the critical analysis and comparison of the six case study countries, a set of common case study variables has also been derived. Subsequently, a selected group of SDI experts has been consulted to give their opinion on the most important variables for assessment of NSDIs in developing countries out of the list of feasible variables. These expert variables have been compared and matched with the earlier defined case study variables. Resulting from the analyses, the following set of key variables for NSDI assessment in developing countries could be selected: availability of digital data, capacity building, willingness to share, human capital, SDI awareness, delivery mechanism, funding, leadership, vision, institutional arrangements, socio-political stability, interoperability, metadata (availability), and initiatives connected to SDI in the respective country. Besides enhancing and innovating the implementation strategies of NSDIs in developing countries, the resulting common set of measurable key variables contributes to the development of the assessment framework.

III

Acknowledgements I would like to thank the ITC Directorate, Personnel Department, and Head Bureau Marketing and Project Services (MPS) for giving me the opportunity to participate in the GIMA-programme. I am grateful to my supervisors, Joep Crompvoets and Erik de Man, for their guidance and encouragement throughout the GIMA-programme and especially during the period of the MSc research. I hope to continue working with Joep and Erik in the future. Lukasz Grus has the challenging task to develop a framework for the worldwide assessment of NSDIs. I would like to thank Lukasz for his assistance during my MSc research. The NSDI coordinators of the case study countries have been very helpful to me. I would like to thank Lilia Patricia Arias (Colombia), Tatiana Delgado (Cuba), Raja Ram Chhatkuli (Nepal), Bebas Purnawan (Indonesia), Jide Kufoniyi (Nigeria), and Alemu Mekonnin (Ethiopia) for providing me with valuable information on their respective NSDIs. I am grateful to all the SDI experts who have answered the questionnaire during the research. I would like to thank Rizqi Abdulharis, Lilia Patricia Arias, Rodrigo Barriga Vargas, Santiago Borrero, Arnold Bregt, Danny van den Broucke, Raja Ram Chhatkuli, Joep Crompvoets, Tatiana Delgado, Yola Georgiadou, Jide Kufoniyi, Kate Lance, Bastiaan van Loenen, Ian Masser, Javier Morales, Doug Nebert, Jos van Orshoven, Bebas Purnawa, Abbas Rajabifard, Orlando Rodriguez Pabon, Walter de Vries, and Jaap Zevenbergen for their useful comments. All my MPS colleagues have been supportive to me during my studies; I would like to especially thank John Horn, Tom Loran and Ronald Hasselerharm for taking over my duties while I was on study leave. During my studies, I have received assistance and support from many ITC colleagues. I would like to thank all the colleagues of the GIP (Geo-Information Processing) and PGM (Urban and Regional Planning and Geo-Information Management) departments, especially those lecturing in the GIMA-programme. Special thanks go to my ITC friends and colleagues Veronica Botero, Enrique Castellanos, Remco Dost, Job Duim, Iris van Duren, Wim Feringa, Chris Hecker, Jeanna Hyde Hecker, Jelger Kooistra, Ard Kosters, Boudewijn van Leeuwen, Javier Martínez, and Raymond Nijmeijer. Thank you for your words of support and thank you for listening to my GIMA stories during the last three years! From the start of the GIMA-programme, I have been intensively working together with Christiane Sürken. I would like to thank Christiane for her words of encouragement and friendship during the ‘good and bad’ GIMA times. I could not have finished this course without the support of Ruben Vargas. I would like to thank Ruben for his patience and continuous encouragement and support. Enschede, May 2006

V

Table of contents Abstract ................................................................................................................................................... I Acknowledgements.............................................................................................................................. III List of figures .......................................................................................................................................VII List of tables.........................................................................................................................................VII List of abbreviations...........................................................................................................................VIII 1 Introduction..................................................................................................................................... 1 1.1 Motivation and problem description...............................................................................................1 1.2 Selection of case study countries..................................................................................................2 1.3 Overall objective ............................................................................................................................4 1.4 Research questions.......................................................................................................................4 1.5 Thesis structure .............................................................................................................................4 2 Research methodology.................................................................................................................. 7 2.1 Introduction....................................................................................................................................7 2.2 Initially identified variables.............................................................................................................8

2.2.1 Existing evaluation frameworks............................................................................................. 8 2.2.2 Brainstorm session .............................................................................................................. 10

2.3 Feasible variables........................................................................................................................12 2.3.1 Inventory of NSDIs in Latin America, Asia and Africa ......................................................... 13 2.3.2 Reviewing the NSDIs in case study countries..................................................................... 13

2.4 Case study variables ...................................................................................................................13 2.5 Expert variables...........................................................................................................................14 2.6 Selection of the key variables for developing countries ..............................................................15 3 General NSDI developments in developing countries.............................................................. 17 3.1 Introduction..................................................................................................................................17 3.2 NSDI definition.............................................................................................................................17 3.3 Status of NSDIs in developing countries .....................................................................................19

3.3.1 Status Latin America ........................................................................................................... 19 3.3.2 Status Asia........................................................................................................................... 20 3.3.3 Status Africa ........................................................................................................................ 21 3.3.4 Comparative summary ........................................................................................................ 21

4 Latin American case studies....................................................................................................... 23 4.1 Introduction..................................................................................................................................23 4.2 NSDI in Colombia ........................................................................................................................23

4.2.1 Results of assessment by means of identified variables..................................................... 24 4.2.2 Data ..................................................................................................................................... 24 4.2.3 People.................................................................................................................................. 24 4.2.4 Access network ................................................................................................................... 25 4.2.5 Policies ................................................................................................................................ 25 4.2.6 Standards ............................................................................................................................ 25 4.2.7 Other.................................................................................................................................... 26

4.3 NSDI in Cuba...............................................................................................................................26 4.3.1 Results of assessment by means of identified variables..................................................... 26 4.3.2 Data ..................................................................................................................................... 27 4.3.3 People.................................................................................................................................. 27 4.3.4 Access network ................................................................................................................... 27 4.3.5 Policies ................................................................................................................................ 27 4.3.6 Standards ............................................................................................................................ 28 4.3.7 Other.................................................................................................................................... 28

4.4 Comparison .................................................................................................................................28 4.5 Selection of case study variables ................................................................................................29 5 Asian case studies ....................................................................................................................... 35 5.1 Introduction..................................................................................................................................35 5.2 NSDI in Nepal ..............................................................................................................................35

5.2.1 Results of assessment by means of identified variables..................................................... 35 5.2.2 Data ..................................................................................................................................... 36 5.2.3 People.................................................................................................................................. 36 5.2.4 Access network ................................................................................................................... 36 5.2.5 Policies ................................................................................................................................ 36

VI

5.2.6 Standards ............................................................................................................................ 37 5.2.7 Other.................................................................................................................................... 37

5.3 NSDI in Indonesia........................................................................................................................37 5.3.1 Results of assessment by means of identified variables..................................................... 38 5.3.2 Data ..................................................................................................................................... 38 5.3.3 People.................................................................................................................................. 38 5.3.4 Access network ................................................................................................................... 39 5.3.5 Policies ................................................................................................................................ 39 5.3.6 Standards ............................................................................................................................ 39 5.3.7 Other.................................................................................................................................... 39

5.4 Comparison .................................................................................................................................39 5.5 Selection of case study variables ................................................................................................40 6 African case studies .................................................................................................................... 45 6.1 Introduction..................................................................................................................................45 6.2 NSDI in Nigeria............................................................................................................................45

6.2.1 Results of assessment by means of identified variables..................................................... 45 6.2.2 Data ..................................................................................................................................... 45 6.2.3 People.................................................................................................................................. 46 6.2.4 Access network ................................................................................................................... 46 6.2.5 Policies ................................................................................................................................ 46 6.2.6 Standards ............................................................................................................................ 47 6.2.7 Other.................................................................................................................................... 47

6.3 NSDI in Ethiopia ..........................................................................................................................47 6.3.1 Results of assessment by means of identified variables..................................................... 47 6.3.2 Data ..................................................................................................................................... 48 6.3.3 People.................................................................................................................................. 48 6.3.4 Access network ................................................................................................................... 48 6.3.5 Policy ................................................................................................................................... 48 6.3.6 Standards ............................................................................................................................ 48 6.3.7 Other.................................................................................................................................... 48

6.4 Comparison .................................................................................................................................48 6.5 Selection of case study variables ................................................................................................49 7 Selection of key variables to assess NSDIs in developing countries..................................... 53 7.1 Introduction..................................................................................................................................53 7.2 Feasible variables........................................................................................................................53 7.3 Case study variables ...................................................................................................................54 7.4 Expert variables...........................................................................................................................56 7.5 Key variables ...............................................................................................................................59 7.6 Specific for developing countries.................................................................................................60

7.6.1 Availability of digital data ..................................................................................................... 60 7.6.2 Capacity building ................................................................................................................. 60 7.6.3 Willingness to share ............................................................................................................ 60 7.6.4 Human capital...................................................................................................................... 60 7.6.5 Awareness........................................................................................................................... 60 7.6.6 Delivery mechanism ............................................................................................................ 61 7.6.7 Funding................................................................................................................................ 61 7.6.8 Leadership........................................................................................................................... 61 7.6.9 Vision ................................................................................................................................... 61 7.6.10 Institutional arrangements ................................................................................................... 61 7.6.11 Socio-political stability ......................................................................................................... 61 7.6.12 Interoperability ..................................................................................................................... 61 7.6.13 Metadata (availability).......................................................................................................... 62 7.6.14 Initiatives connected to SDI (country’s activity) ................................................................... 62

7.7 Results.........................................................................................................................................62 8 Conclusions and recommendations .......................................................................................... 65 8.1 Conclusions .................................................................................................................................65 8.2 Recommendations.......................................................................................................................66 References ........................................................................................................................................... 69 Appendices .......................................................................................................................................... 75

VII

List of figures Figure 1: Map showing case study countries .......................................................................................... 3 Figure 2: Flow chart of research methodology ........................................................................................ 7 Figure 3: Evaluation areas for SDI (Adapted from Williamson et al., (2003)) ......................................... 8 Figure 4: SDI components (Adapted from Rajabifard et al., 2003) ....................................................... 17 Figure 5: SDI hierarchy (Adapted from Rajabifard et al., 2003) ............................................................ 18 Figure 6: Key variables to assess NSDIs in developing countries – SDI expert opinion ...................... 57

List of tables Table 1: Possible indicators for evaluating SDIs (Adapted from Steudler, 2003) ................................... 9 Table 2: Variables to assess NSDIs based on existing assessment procedures and frameworks ...... 11 Table 3: Comparison case study variables between Colombia and Cuba............................................ 33 Table 4: Comparison case study variables between Nepal and Indonesia........................................... 43 Table 5: Comparison case study variables between Nigeria and Ethiopia ........................................... 51 Table 6: Feasible variables.................................................................................................................... 53 Table 7: Case study variables ............................................................................................................... 55 Table 8: Key variables as selected by SDI experts ............................................................................... 58 Table 9: Variables not selected by SDI experts .................................................................................... 58 Table 10: Key variables for the assessment of NSDIs in developing countries .................................... 59 Table A: Description of the Colombian NSDI ........................................................................................ 82 Table B: Description of the Cuban NSDI ............................................................................................... 87 Table C: Description of the Nepalese NSDI .......................................................................................... 92 Table D: Description of the Indonesian NSDI........................................................................................ 96 Table E: Description of the Nigerian NSDI .......................................................................................... 100 Table F: Description of the Ethiopian NSDI ........................................................................................ 105 Table G: Possible answers to assessment variables (of identified variables Table 2) ....................... 106 Table H: Comparison of data component between case study countries ........................................... 110 Table I: Comparison of people component between case study countries......................................... 112 Table J: Comparison of access network component between case study countries .......................... 115 Table K: Comparison of policy component between case study countries ......................................... 117 Table L: Comparison of standard component between case study countries .................................... 120 Table M: Comparison of other component between case study countries ......................................... 121 Table N: Consulted SDI experts .......................................................................................................... 123 Table O: Results of questionnaire SDI experts ................................................................................... 124

VIII

List of abbreviations CIAF Centro de Investigación y Desarrollo en Información Geográfica – Centre of Research

and Development on Geographic Information (Colombia) CBS Central Bureau of Statistics CEN European Committee for Standardisation CYTED Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo – programme

for development of science and technology EC European Commission EMA Ethiopian Mapping Authority ENRAEMED Ethiopian Natural Resources and Environmental Meta Database FGDC Federal Geographic Data Committee: developing the US National Spatial Data

Infrastructure in cooperation with organisations from state, local and tribal governments, the academic community, and the private sector

GI Geo-Information GIS Geographic Information System HMGN His Majesty's Government of Nepal ICDE Infraestructura Colombiana de Datos Espaciales: Colombian National Spatial Data

Infrastructure initiative IDERC Infraestructura de Datos Espaciales de la República de Cuba: Cuban National Spatial

Data Infrastructure initiative IGAC Agustin Codazzi Geographic Institute: the national surveying and mapping agency of

Colombia ISDI Indonesian Spatial Data Infrastructure ISO International Organisation for Standardisation GSDI Global Spatial Data Infrastructure LAN Local Area Network MSc Master of Science NASRDA National Space Research and Development Agency (Nigeria) NGO Non-governmental organisation NEPAD New Partnership for Africa’s Development NGII National Geographic Information Infrastructure: Nepalese National Spatial Data

Infrastructure initiative NSDI National Spatial Data Infrastructure OGC Open Geospatial Consortium – a non-profit, international, voluntary consensus

standards organisation leading the development of standards for geospatial & location based services

PC IDEA Permanent Committee on SDI for the Americas PC GIAP Permanent Committee on GIS infrastructure for Asia and the Pacific PhD Doctor of Philosophy RAS Remote Access Server RECTAS Regional Centre for Training in Aerospace Surveys (Nigeria) SD Survey Department (Nepal) SDI Spatial Data Infrastructure SLARIM Strengthening Local Authorities in Risk Management SMART Specific, Measurable, Attainable, Relevant and Trackable SWOT Strengths-Opportunities-Weaknesses-Threats TUD University Delft UN United Nations UNDP United Nations Development Programme UNECA United Nations Economic Commission for Africa WCS Web Coverage Service WFS Web Feature Service WMS Web Map Service WPS Web Processing Service WUR Wageningen University & Research

Towards key variables to assess NSDIs in developing countries

Chapter 1: Introduction 1

1 Introduction

1.1 Motivation and problem description In the modern technological age, information has become of vital importance to the economic and social development of a country. Geographic information, in particular, is of increasing importance for the successful execution of (public) tasks. Spatial Data Infrastructures (SDIs) are about the facilitation and coordination of the exchange and sharing of spatial data among stakeholders in the spatial data community (Crompvoets, 2004). Specifically, SDIs facilitate the collection, maintenance, dissemination, and use of spatial information. SDIs could produce significant human and resource savings and returns by reducing duplication and facilitating integration (Chan et al., 2001). Many countries are developing SDIs at different levels ranging from local to state/provincial, national and regional levels, to a global level, in order to improve management and utilisation of spatial datasets (Rajabifard, 2003). However, although many countries declare that they are involved in SDI development, Masser (2005) asserts that these claims need to be treated with caution. Engagement in SDI development does not necessarily mean that the initiative will translate into a fully operational SDI over time. Nevertheless, during the last few years, many countries have spent considerable resources creating optimal SDIs (Crompvoets, 2003). Since 1994, national SDIs (NSDIs) have been developing rapidly. An NSDI has a full impact on the other levels of the SDI hierarchy (global, regional, state/provincial and local) – see also Figure 5 on page 18. For example, in terms of policy, NSDIs have an important effect on the management of both the upper and lower levels. In terms of core datasets, an NSDI has an important role in establishing a data framework for a country. In 2002, 120 countries had already initiated projects for NSDI development (Crompvoets, 2003). This means that (from a worldwide perspective) billions of Euros are spent yearly on NSDI development (Crompvoets, 2004). Up to now NSDI efforts have not been audited or evaluated systematically (Crompvoets, 2004). Evaluation involves assessing the strengths and weaknesses of NSDI-programmes, policies, personnel, products, and organisations to improve their efficiency and effectiveness (Steudler, 2003). Williamson et al. (2003) have suggested a general evaluation framework for SDIs that attempts to accommodate the SDI components such as people, access network, policy, standards and data. However, at this moment, no coherent and comprehensive framework (considering the economic, social, technological and environmental dimensions) exists for the worldwide assessment of NSDIs. The application of such a framework would support the establishment and implementation of efficient, effective and coherent NSDIs in both developed and developing countries. The purpose of a project at the Wageningen University (WUR) called ‘Development of a Framework to Assess National Spatial Data Infrastructures’ funded by the Netherlands Ministry of Economic Affairs through the programme ‘Space for Geo-Information’ is to fill the gap of not having such a framework. The formulation of a conceptual framework is scientifically challenging. The project at the Wageningen University, in cooperation with the Delft University of Technology (TUD), and The Melbourne University in Australia, will contribute to its formulation, considering all the components of an SDI (spatial data (services); networking technology; standards; policies; and, people and structures) and its historical, legal, cultural, technological, institutional and economic context. The project involves PhD research. Masser (2005) mentions that the implementation of an NSDI initiative can be considered as a process of organisational change management. Despite this, the need for capacity building initiatives to be developed in parallel to the processes of NSDI implementation is often underestimated. This is particularly important in developing countries where the implementation of NSDI initiatives is often dependent on a limited number of staff with the necessary geographic information management skills. On the other hand, capacity building might also have negative impact as described by Masser in his research agenda for SDI (GSDI-8 Cairo, 2005). Existing capacities are sometimes ignored. A developing country can be defined as a country with a relatively low standard of living, undeveloped industrial base, and moderate to low human development index (a comparative measure of poverty,



literacy, education, life expectancy, childbirth, and other factors) (World Bank, 2006). Akinyede and Boroffice (2004) note that policy-makers in developing countries do not have the adequate access to accurate (geo) information needed to make rational and prospective allocation and management decisions. Besides the dependency on (external) funding sources, developing countries are facing some other challenges to establish and implement SDIs. According to Rajabifard and Williamson (2003), the main limitations of SDIs in developing countries are thought to be in the lack of appreciation of what an SDI can and cannot do, the lack of resources and trained personnel, inefficient bureaucratic processes, and the lack of data. It is difficult to implement NSDIs, partly due to the shifts in bureaucratic power that are associated with it. For an NSDI to be successful, governments must participate and continuously contribute and support the NSDI developments (FGDC, 2006). To actually sustain the NSDI is a major challenge in developing countries. In many cases foreign donors drive the initiatives instead of the respective governments (Lance, 2003). As described by De Man (2004), SDIs seem to be another ‘promise’ within the continuous development of geographic information technologies. Does the promise of SDIs also hold for developing countries? Are enabling conditions and possible bottlenecks of developing countries different from those of developed countries? Since each country is unique in historical, legal, economic, technological, cultural and institutional terms, the benefits gained and bottlenecks expected for the establishment and implementation of NSDIs are likely to be different as well. Hence, not only effective strategies for establishing and implementing may be country-specific but also NSDIs themselves may be different for each country. In order to interpret these differences, this research assumes that a common set of measurable key variables to assess NSDIs is needed. The research problem is, therefore, how to define this common set of key variables. The purpose of determining key variables is to support effectiveness throughout the processes of planning, implementation, monitoring, reporting and evaluation – that is, throughout the full spectrum of results-based management (UNDP, 2006). The key variables selected for the assessment can also be used to enhance and innovate NSDIs in a more strategic and operational way. This Master of Science (MSc) research explores how to select a common set of measurable key variables to assess NSDIs of developing countries. Investigating NSDI-programmes of six different developing countries (Colombia, Cuba, Nepal, Indonesia, Nigeria and Ethiopia) from three different continents (Latin America, Asia and Africa) supports this research. The choice to look intensively into the NSDIs of these countries is explained in the following section.

1.2 Selection of case study countries The present research fits within several ongoing studies. The determination of a common set of measurable key variables to assess NSDIs could support the development of the framework for the worldwide assessment of NSDIs as described in previous section. A research project that may benefit from the research is ITC’s research project ‘Strengthening Local Authorities in Risk Management’ (SLARIM). The main objective of SLARIM is to develop a methodology for spatial risk information collection and management for municipalities. This methodology will allow local authorities to evaluate the risk of natural disasters in their municipality, in order to implement strategies for vulnerability reduction. PhD studies within this research project are focusing on the understanding of variables and factors that define vulnerability, and how these variables can be used by local authorities for multiple administrative tasks. To facilitate this, an SDI will be designed to aid local authorities in urban vulnerability assessments, as well as to develop disaster prevention and mitigation strategies that can significantly reduce life and material losses. The research is supported by two case studies in two developing countries (Colombia/Latin America and Nepal/Asia). ITC’s SLARIM project may use the outcome of the results of this research with respect to Colombia and Nepal.



The NSDI-programmes of six different countries from three different continents (2 x Latin America, 2 x Asia, and 2 x Africa) are investigated. The World Bank (2006) has listed all the selected case study countries as developing countries. The reason to focus on complementary case study countries during this research is to take into account the business requirements and driving forces that have shaped the purpose, scope, design, implementation and technical aspects of NSDIs. An appreciation of these business requirements and driving forces could assist in the improvement of establishing and implementing NSDIs. By reviewing NSDI initiatives in the three continents, differences and similarities between Latin America, Asia and Africa can be observed. The most important benefits of comparing (N)SDIs with each other are ‘the lessons learnt’ and ‘the identification of good practices’ (Steudler, 2003). For example, both Latin America and Asia have already established regional SDI initiatives (Permanent Committee on SDI for the Americas (PC IDEA) and Permanent Committee on Geographic Information Systems (GIS) infrastructure for Asia and the Pacific (PC GIAP)). In Africa, moves are on the way to create a Committee on Development Information under the auspices of the United Nations Economic Commission for Africa (UNECA) (Rajabifard and Williamson, 2004). A common set of important key variables for assessment could be identified already by looking at the continents. On the basis of research carried out by Crompvoets (2006), during a brainstorm session at the Wageningen University in November 2005, Ethiopia was selected as the first African country for further investigation. UNECA has been strongly promoting the development of the Ethiopian NSDI. As described by Lance (2003), in many cases foreign donors drive the initiatives in developing countries instead of the respective governments. This thesis investigates the influence of the United Nations in Ethiopia. The second African country, Nigeria, was selected after talking with Dr Kufoniyi, Director of the Regional Centre for Training in Aerospace Surveys (RECTAS), and in charge of the implementation of the Nigerian NSDI. Nigeria has been working hard on the NSDI initiative. Recently a policy document has been submitted to the government for acceptance. Colombia has played an important role in promoting SDI in the region; it will be interesting to review the current status and process over the last years. Colombia did play a role in setting up the Cuban NSDI – a workshop on SDI principles was organised in Cuba by the Colombians. During the brainstorm session, Cuba was selected as the second Latin country to investigate further. Cuba has recently launched a portal and seems to speed up its NSDI development fast. ITC’s SLARIM project may use the outcome of the results with respect to Colombia. Indonesia has been selected as the second country from the Asian continent (next to Nepal). This thesis investigates the reasons this developing country started so early with the initiative as well as the current progress. Nepal only started the NSDI initiative in 2002 and had the support of the European Commission (EC) during the first three years. The results of the research on Nepal may contribute to the SLARIM project. The following map is showing the six case study countries.

Cuba

Colombia Nigeria Ethiopia

Nepal

Indonesia

Figure 1: Map showing case study countries



For nearly half a century, the Netherlands government has financed several international cooperation programmes aimed at the sustainable strengthening of institutional capacity for post-secondary education and training in developing countries. With the exception of Cuba and Nigeria, all selected case-study countries participate in this programme. Both ITC and WUR have contributed to the cooperation programmes and have established good relationships with the NSDI coordinators in the respective case study countries; this will make it easier to get additional information on the establishments and developments. Based on existing frameworks, procedures and literature review, the possible variables to assess NSDIs are listed, carefully investigated and compared with respect to the six case study countries. By investigating and comparing the variables of the six developing countries, not only the common variables might be revealed, but also the issues raised in this Chapter might be answered.

1.3 Overall objective The overall objective is to explore how to select a common set of measurable key variables that can be utilised to assess NSDIs – with a focus on developing countries. This thesis contributes to PhD research that focuses on the development and application of a framework to assess NSDIs worldwide. The NSDIs of six developing countries are taken as case studies in this MSc research – Colombia, Cuba, Nepal, Indonesia, Nigeria and Ethiopia (two countries each for three different continents: Latin America, Asia and Africa).

1.4 Research questions The main research question of the thesis is formulated as follows: ‘How to select a common set of measurable key variables that can be utilised to assess NSDIs in developing countries?’ In order to answer the main research question, several sub-questions have to be answered: 1. How is an NSDI defined? 2. What are the variables (and criteria) to assess NSDIs – based on existing assessment procedures

and frameworks? 3. How to assess and compare the NSDIs of the case study countries based on the identified

variables? 4. How to decide on the criteria for selection of the key variables in order to assess NSDIs in

developing countries? The different research steps to be followed in order to select the key variables and to answer the research questions are explained in detail in Chapter 2 (Research methodology).

1.5 Thesis structure This thesis follows the structure as described in Chapter 2 (Research methodology). Throughout the different Chapters of this research, answers to the research questions, as defined in the previous section, are presented. Chapter 1 – Introduction. The first Chapter provides an overview of the research. It presents the motivation, the problem description and gives references to related studies. This Chapter outlines the overall objective of the research and the research questions. Finally, it presents the structure of the thesis.



Chapter 2 – Research methodology. The second Chapter describes the different steps to be followed in order to select key variables that can be utilised to assess NSDIs – applied to developing countries. Possible assessment criteria of NSDIs are identified and a first listing of variables to assess NSDIs is presented. This listing forms the basis of the research. Chapter 3 – Review of NSDI developments in developing countries. The definition of an NSDI is discussed in the third Chapter. Based on literature review, the developments as well as the implementation of NSDIs in Latin America, Asia and Africa are critically reviewed and compared. Chapter 4 – Latin American case studies. The identified variables as listed in Chapter 2 are described in Chapter 4 for Colombia and Cuba. Both countries are compared based on the identified variables. This Chapter presents the feasible and the case study variables (based on comparison of Colombia and Cuba and the results of Chapter 3). Chapter 5 – Asian case studies. The identified variables as listed in Chapter 2 are described in Chapter 5 for Nepal and Indonesia. Both countries are compared based on the identified variables. This Chapter presents the feasible and the case study variables (based on comparison of Nepal and Indonesia and based on the results of Chapter 3). Chapter 6 – African case studies. The identified variables as listed in Chapter 2 are described in Chapter 6 for Nigeria and Ethiopia. Both countries are compared based on the identified variables. This Chapter presents the feasible and the case study variables (based on comparison of Nigeria and Ethiopia and based on the results of Chapter 3). Chapter 7 – Selection of key variables to assess NSDIs in developing countries. Chapter 7 summarises and describes the feasible and case study variables as identified in Chapters 4, 5 and 6. It also describes the result of an SDI expert workshop and presents the opinions of SDI experts with respect to the key variables for developing countries. Subsequently, the key variables to assess NSDIs in developing countries are selected and described by comparing and matching the expert variables with the case study variables (as defined in previous Chapters 4, 5 and 6). Chapter 8 – Conclusions and recommendations. Finally, conclusions as well as recommendations are presented.


Chapter 2: Research methodology 7

2 Research methodology

2.1 Introduction Besides introducing the research steps, this Chapter seeks to answer research question 2 (what are the variables (and criteria) to assess NSDIs – based on existing assessment procedures and frameworks). The selection of the key variables comprises a number of research steps. By critically reviewing existing assessment frameworks, a considerable number of initial variables that can be used to assess NSDIs are identified (see section 2.2). To progress to the feasible variables, those variables that are not measurable are to be removed from the initial list of identified variables. This is done after thoroughly describing the identified variables of the six case study countries. From the initially identified variables, a reduced list of measurable feasible variables has been developed (see section 2.3). Following on from the review of the NSDI initiatives in the three continents in Chapter 3, and the critical analysis and comparison of the case study countries, a set of common case study variables is being derived (see section 2.4). Subsequently, a selected group of SDI experts is consulted to give their opinion on the most important variables for assessment of NSDIs in developing countries out of the list of feasible variables (see section 2.5). These expert variables are compared and matched with the earlier defined case study variables. Resulting from the comparison, a set of key variables for NSDI assessment in developing countries is selected (see section 2.6). These research steps can be visualised with the following flow chart in Figure 2. The details shall be explained in the following sections.

Figure 2: Flow chart of research methodology



Criteria for the selection of key variables are assumed to be similar as for the selection of indicators as described by the United Nations Development Programme (UNDP, 2006); they should be Specific, Measurable, Attainable, Relevant and Trackable (acronym ‘SMART’). These five criteria are kept in mind during the different research steps to come to the final selection. For example, for the selection of the feasible variables, all identified variables of the case study countries are described. The specific, measurable, attainable and trackable variables have been filtered out of the list of identified variables to progress to the feasible variables. The challenge in selecting key variables is to find measures that can meaningfully capture key changes, combining what is substantively relevant as a reflection of the desired result with what is practically realistic in terms of actually collecting and managing data (UNDP, 2006). Therefore, for the selection of the relevant case study variables, the UNDP rule to look at the key changes has been applied. During this research, a case study approach is used. As explained by Van Loenen (2006), case study research allows for a more complete understanding of NSDIs (though Van Loenen speaks of ‘geographic infrastructures’) by examining behaviour in context (see also: Yin, 1994). The purpose of the case study research is twofold, (1) to identify the feasible variables (see section 2.3), and (2) to identify the case study variables (see section 2.4).

2.2 Initially identified variables The following sections explain in detail how the variables for assessment of NSDIs have been identified (identified variables of Figure 2). An identification of assessment criteria of NSDIs assists to make a listing of possible variables to evaluate them (research question 2). Existing evaluation frameworks, as described in literature, each addressing different (single) aspects of NSDIs are used. As described by De Man (2006), SDIs require a multi-faceted way of monitoring and evaluation. Therefore, several assessment frameworks describing different evaluation aspects have to be investigated. Three assessment frameworks as proposed in literature are described in section 2.2.1. In section 2.2.2, the outcome of a brainstorm session at the Wageningen University is described. The identified variables are presented in Table 2, on page 11.

2.2.1 Existing evaluation frameworks The first evaluation framework is a general one suggested by Steudler (2003) for NSDIs. The framework attempts to accommodate the SDI components such as people, access network, policy, standards and data (see Figure 4, page 17, for the SDI components). Issues such as the different stakeholders and the recurring and regular review of objectives and strategies through performance assessment are taken into account in Steudler’s evaluation. Each evaluation area – as suggested by Steudler, and visualized in Figure 3, needs to be evaluated in terms of aspects, indicators, and good practice.

Figure 3: Evaluation areas for SDI (Adapted from Williamson et al., (2003))



Steudler comes up with the following indicators that should be taken into consideration when evaluating an NSDI: Table 1: Possible indicators for evaluating SDIs (Adapted from Steudler, 2003) Area Possible indicators Policy level – Policy

Existence government policy for SDI. Handling of intellectual property rights, privacy issues, pricing. Objectives for acquisition and use of spatial data.

Management level – Standards

Standardisation arrangements for data dissemination and access network.

Institutional arrangements of agencies involved in providing spatial data.

Organisational arrangements for coordination of spatial data. Definition of core datasets. Data modelling. Interoperability.

Management level – Access network

Access pricing and privileges. Delivery mechanism and procedure. Value-adding arrangements.

Operational level – Access network

Type of network. Data volume. Response time.

Operational level – Data

Data format, capture method, maintenance, quality and accuracy. Definition of core datasets.

Other influencing factors – People

Number of organisations and people involved (human resources). Opportunities for training (capacity building). Market situation for data providers, integrators and end-users.

Performance assessment Degree of satisfying the objectives and strategies. User satisfaction. Diffusion and use of spatial data and information. Turnover and reliability.

Indicators that become apparent because of an evaluation can be summarised as a SWOT (‘strength-weakness-opportunity-threat’) matrix. Steudler emphasises that the indicators are only a general framework for evaluation and require further development. The second evaluation framework is discussed by Kok and Van Loenen (2004). ‘Organisational theory’ is used to assess the success of NSDIs. Since the components of the SDI are continuously changing (see Figure 4, page 17), the organisational component needs to change accordingly to enable further development of the SDI. Based on organisational theory developed by Boonstra (2004), Kok and Van Loenen define four stages of development of NSDIs, namely: (1) stand-alone stage (SDI has no priority), (2) exchange stage (focus on standardisation and framework datasets), (3) intermediary stage (increasing awareness for cooperation – organisations change from internally centred towards open and externally centred), and (4) the network stage (broad support for SDI). Kok and Van Loenen state that the likeliness to come to an organisational ideal depends on four critical organisational indicators: (1) leadership, (2) vision, (3) communication channels and (4) ability for self-organisation. These organisational indicators can be described as the extent to which the NSDI vision is supported. For example: Leadership: both political support and management support are important. Outreach and capacity

building are mentioned as tools that may lead to support from politicians and support from the work floor.

A vision: a vision shared by stakeholders is likely to direct the activities into the same direction – the vision directs the SDI activities.

Communication channels: to actively participate in the decision-making process, open communication channels should be strived for.

Ability of the spatial information community for self-organisation: all stakeholders recognise their responsibility for their (part of the) NSDI.



The presence of these organisational indicators combined with the four development stages as mentioned above, result in the ‘organisational maturity matrix’. The more coherent the community is, the more likely it will be that the SDI development is successful. Kok and Van Loenen conclude that, from an organisational point of view, it is critical that the SDI vision is widely supported, that leadership in geo-information community is present, and communication channels are open to all and frequently used, making the GI community a mature sector (in organisational context) that is ready for changes. The third interesting study has been carried out by Delgado et al. (2005). An SDI readiness index has been developed, which can be defined as ‘the degree to which a country is prepared to deliver its geographical information in a community (local, national, regional or global)’. Several previous studies were reviewed and global factors were identified from several points of view: organisational, information, access network, people and financial resources. The SDI readiness index provides a quantitative means to compare countries, as well as compare SDI progress over time within a country. Delgado first identified a wide spectrum of factors influencing SDI development, established a hierarchy of priorities, and then ‘discovered’ their incidence in countries with respect to NSDI implementation. The model has been assessed in a case study on Cuba.

2.2.2 Brainstorm session During a brainstorm session at the Wageningen University on November 16th, 2005, a table with variables to assess NSDIs has been developed (identified variables of Figure 2). The three frameworks, as discussed in the section above, focus on different, not complete (single) aspects of assessment. The framework described by Steudler (2003) mainly focuses on performance, the framework of Kok and Van Loenen (2004) zooms in at the organisational fit, while Delgado et al. (2005) focus on the readiness. Besides the three frameworks, as described in section 2.2.1, a considerable number of other scientific articles have been reviewed critically. Next to the three focuses as mentioned earlier, other assessment criteria have been taken into consideration to make the table with possible assessment variables as complete as possible. The reviewed articles all give indications for variables to investigate and to take into consideration while evaluating an NSDI. Articles describing situations in both developing and developed countries have been examined to develop the table. The identified variables, as observed in literature, have been written down on a white board during the brainstorm session and have been placed in a table following the five dynamic components of the SDI: data, people, access network, policy, and standards (see Figure 4, page 17). One extra item, called ‘other’, has been added to the table. This item mentions those variables that do not fit in one of the five ‘traditional’ SDI components. The work of Abdel-Salam et al. (2005), Crompvoets et al. (2004; 2006), Delgado et al. (2005) (section 2.2.1), Georgiadou (2005), Kok and Van Loenen (2004) (section 2.2.1), Masser (1999; 2005), Onsrud (1998), Orshoven Van (2003), Steudler et al. (2004) (section 2.2.1), and Rodriguez-Pabon (2005) contributed to the development of Table 2. The table below presents 94 identified variables to assess NSDIs as developed in Wageningen on November 16th, 2005 (research question 2). The definitions of the identified variables can be found in the Appendix.



Table 2: Variables to assess NSDIs based on existing assessment procedures and frameworks SDI COMPONENTS

Data component Core data sets Data format Maintenance Quality Accuracy Updating – adding of new data Resolution Language Availability digital data sets Relevance Reliability Data content Uniformity (country reference system) People component Driving forces (data acquisition, SDI) Definition of core data sets Language Number and type of suppliers Number and type of users Number of participating institutes in network Capacity building (information dissemination, short courses and workshops, research and facilitation) Education (type, availability) SDI (GIS) related conferences/journals/ stakeholders Research (to support NSDI) User satisfaction (SDI & approach) User involvement Private/commercial participation Awareness (spatial data, SDI concept) Human capital SDI culture Involvement professional organisations (NGOs etc.) Size of user involvement Willingness to share data Uncertainty avoidance Access network component Delivery mechanism (availability, search and procedures) Network architecture (type, telecommunications, Internet) Data volume / data sets Response time Number of visitors Number of web references Number of language used Frequency of web updates Status Preview possibility Implementing body E-business Performance (usefulness) Reliability Policy component Executing coordinating body SDI directive (existence) SDI directive (freedom of info act / copyright)

VAR

IAB

LES

Funding (source)



Funding (amount) Funding (model) Funding (stability) Intellectual property Privacy Pricing (data & access to services) Institutional arrangements for suppliers/users/value-adders Access privileges Legal arrangement for suppliers/users/value-adders Leadership (who, power) Vision (political, long-term) Partnership arrangements Public/private partnerships Data collection body Member of regional organisation Liability Commercialization of data Policy of preview Nature of spatial information market E-government existence Socio-political stability Standards component Data transfer Metadata (availability) Type and use of metadata standard (ISO, CEN, FGDC) Services Interoperability WMS WFS WPS WCS Others component SDI coverage (local, global) Status Development approach (bottom-up, top-down) Decentralization / centralization Communication channels SDI's complexity Hierarchy (vertical & horizontal relationships) SDI's maturity SDI's history (years of existence) SDI's impact visibility Initiatives connected to SDI (country’s activity) NSDI definition (goal) Main challenge (e.g. implementation or maintenance)

2.3 Feasible variables This research is attempting to define a common set of measurable key variables. Ninety-four variables have been identified and are presented in Table 2. Not all variables of this table might be (easily) measurable. In the Chapters 4, 5 and 6, for each of the six case study countries, all listed identified variables of Table 2 are carefully checked based on literature review and interviews with the national SDI coordinators via e-mail. To come to the feasible variables, those variables that are not measurable are to be removed from the initial list of identified variables.



The following sections explain in more detail which rules have been applied to progress from the initially identified list of variables (identified variables of Figure 2) to the reduced list of feasible variables (feasible variables of Figure 2).

2.3.1 Inventory of NSDIs in Latin America, Asia and Africa As mentioned in Chapter 1, section 1.1, this research focuses on NSDIs. Since many different definitions of NSDIs exist in literature, in Chapter 3, a definition of an NSDI used throughout this research is given (research question 1). It might very well be that the three continents require different sets of key variables for effective assessment. Accordingly, based on literature review, Chapter 3 is a review of the NSDI developments in the three different continents (Latin America, Asia and Africa). By reviewing the developments in the continents, important variables might become apparent and criteria for the selection of key assessment variables can be identified already (research question 4).

2.3.2 Reviewing the NSDIs in case study countries Literature is consulted intensively to fill out the tables with identified variables of the different case study countries. Not all required information on the identified variables can be found in literature / Internet. Interviews with the national SDI coordinators (phone, e-mail) are a good option to retrieve further information on the NSDIs of the case study countries. After having filled out the tables, the respective national coordinators are asked to review the tables and to give information on those variables for which no information can be found in literature / Internet. All the tables of the different case study countries are presented in the Appendix (Table A up to F). After the above-described research on the case study countries (Chapters 4, 5 and 6), the number of identified variables can be reduced to a list of feasible variables. The following set of rules has been applied to reduce the list of initially identified variables: (1) for some of the variables no information is available – even after consultation with the national coordinators, the variable appears to be not measurable, (2) some of the variables appear to be sub-variables of a larger variable – sub-variables can be removed. Furthermore, (3) some of the respective countries have already arranged a number of the variables – no changes can be noticed or are to be expected. As mentioned earlier, UNDP (2006) suggests variables to be Specific, Measurable, Attainable, Relevant and Trackable (acronym ‘SMART’) – mainly the Specific, Measurable, Attainable and Trackable criteria are kept in mind selecting the feasible variables. In summary, based on investigating all the identified variables of the six case study countries and applying the rules as explained in the previous paragraph, the initial list of identified variables can be reduced to a smaller list of variables, which are called the feasible variables in this research. The feasible variables are presented in Chapter 7, section 7.2.

2.4 Case study variables This section explains how the NSDIs of the case study countries have been analysed and compared (research question 3). Given that SDI implementation is likely to take place over a long period of time with changing technologies (Masser, 2005), together with the dynamic (external) political and institutional circumstances that surround it, the evaluation of NSDI-programmes at different time frames is considered as very important. Due to time constraints, this research has only looked at the present status of the NSDIs of the case study countries (December 2005 / January 2006). However, the history of the different NSDIs has been examined and described in Chapters 4, 5 and 6. The list of feasible variables is still very extensive (49 feasible variables). This research attempts to select a common set of key variables. To identify the common variables, all the feasible variables of the six case study countries have to be compared with each other. The UNDP rule to look at the key



changes, as previously explained in section 2.1, is applied to select the relevant case study variables. To ease the search for key changes within the feasible variables of the different SDI components (data, people, access network, policy, standard, and other) of the six case study countries, first the possible answers to the variables have been re-classified (see Table G, Appendix, for the re-classification). To give an example; looking at the core data sets (first variable of the data component), the answers ‘defined’ and ‘not defined’ have been added to ease comparison of this variable between the six case study countries. Second, the previously filled out tables (section 2.3.2) of the six case study countries have been used to construct the comparison tables for all SDI components; with the assistance of the re-classified answers. By doing so, the feasible variables can be compared with each other rather easily – key changes can be discovered rather simply, and, subsequently relevant case study variables can be selected. Each of the separate Chapters (4, 5 and 6) also aims to identify criteria for the selection of key variables (research question 4). To identify criteria for the selection of key variables, the necessary (or: ‘minimal’) conditions that an NSDI has to fulfil to gain progress, continuity and good performance over time have to be identified and taken into consideration (Masser, SDI expert workshop Wageningen, 2006). The literature review of Chapter 3 (as explained in section 2.3.1) gives criteria for the selection of important assessment variables. The analysis and comparison of the different SDI components of the six case study countries (‘the search for key changes’ by means of the comparison tables) and the identification of criteria for the selection of key variables, assists to reduce the list of 49 feasible variables to a smaller, common set of 29 case study country variables, which are called the case study variables in this research (case study variables of Figure 2). Chapters 4, 5, and 6 present the comparison and the criteria. The case study variables can be found in Chapter 7, section 7.3. All the comparison tables (Table H up to Table M) can be found in the Appendix.

2.5 Expert variables In this research, a selected group of SDI experts has been consulted to validate the resulting list of case study variables (expert variables of Figure 2). SDI experts have been asked to give their opinion on the ten most important assessment variables for developing countries out of the list of feasible variables. SDI experts have been asked to only select the ten most important feasible variables in order to progress to a justifiable number of key variables. The opinions of the experts have been compared with each other and ranked. A set of expert variables has subsequently been selected. Chapter 7, section 7.4 presents the findings of the experts. The list of consulted SDI experts and their individual opinions can be found in the Appendix (Table N and Table O). It was decided to validate the case study variables by SDI experts because of several reasons. For example, by selecting different or more case study countries, other variables could have come forward as important. Furthermore, for comparison of the variables in the different SDI components of the case study countries, the correlation between the variables or underlying factors could have been explored. To give an example, indices could have been used. An index is a composite indicator, formed by amalgamating two or more different measures into one (UNDP, 2006). With indices, ‘weight’ must be attributed to components according to their relative importance (UNDP, 2006). In other words, if one of the component attributes is inherently more important than another, it should be assigned a heavier weight or share of the combined measure. In this research, the decision has been made not to work with indices. To assign weights to the many different variables and the separate SDI components is not an easy task. Since each country is unique in historical, legal, economic, technological, cultural and institutional terms, a certain variable might have more weight in one country than in the other. Moreover, not all information on the variables per SDI component can be retrieved and/or is available. Another method to reduce the number of variables and to detect structure in the relationships between variables is factor analysis (StatSoft, 2003). Seeing the large number of identified variables, the variety in measurement modes (qualitative, quantitative) and the limited time frame of this research, this research has not looked at factor analysis techniques.



For above described reasons, a selected group of SDI experts has been consulted to validate the resulting list of case study variables.

2.6 Selection of the key variables for developing countries A common set of measurable key variables (key variables of Figure 2) is selected based on the comparison and matching of the case study variables (section 2.4) with the expert variables (section 2.5). It is checked if the expert variables are part of the case study variables. The most frequently selected expert variables that are part of the case study variables are selected as the key variables. The final selection of key variables is described in more detail in Chapter 7. Furthermore, in section 7.6, whether or not the key variables for assessment of NSDIs in developing countries are different from those of developed countries are checked and described. The resulting common set of measurable key variables may be used to enhance and innovate NSDIs in developing countries in a more strategic and operational way.


Chapter 3: General NSDI developments in developing countries 17

3 General NSDI developments in developing countries

3.1 Introduction

As noted by Akinyede and Boroffice (2004), lack of SDI progress in developing countries is rooted in a number of factors, which include poor quality data collection, organisation and management practices and the lack of adequate infrastructure and skilled human capacity. Policy-makers do not have the adequate access to accurate geo-information needed to make rational and prospective allocation and management decisions. Akinyede and Boroffice claim that in developing countries this has led to food insecurity and hunger, air and water pollution, environmental degradation, poverty, diseases and death. The GSDI Cookbook (2004) states that geo-information is of vital importance to make decisions at local, regional, and global level. Plenty of examples in which geographic information is assisting the decision-making process, more recently combined with the associated ‘spatial data infrastructures’ that support information discovery, access and use of this information, can be thought of (e.g. disaster recovery, crime management etc.). As can be seen from Figure 4 (Adapted from Rajabifard et al., 2003), an SDI consists of five dynamic components: (1) the institutional framework (policy), (2) technical standards (standards), (3) fundamental datasets (data), (4) access networks (networking technology), and (5) people (human resources). In recent studies (Masser, 2005; Delgado, 2005), next to the human resources, the financial resources are taken into consideration as well. To secure funding is a relevant issue in not only developing countries; NSDIs require constant accomplishments and financial input over a long period of time.

Figure 4: SDI components (Adapted from Rajabifard et al., 2003) An NSDI has stronger relationships as well as a more important role in building the other levels of SDIs (Rajabifard et al., 2003). By identifying a common set of measurable key variables to assess NSDIs, the infrastructures could be improved and set up in a more decisive and operational way. This Chapter seeks to answer research question 1. It gives a definition of an NSDI – based on reviewing existing definitions in literature. The three continents might require different sets of key variables for effective assessment. Therefore, in Chapter 3, the NSDIs in the three continents under investigation (Latin America, Asia and Africa) are critically reviewed and compared. The most important benefits of comparing (N)SDIs with each other are ‘the lessons learnt’ and ‘identification of good practices’ (Steudler, 2003). Checking and reviewing also gives an indication of the criteria to select those variables that are most important for assessment: the key variables. In order to select the key variables, the necessary (or: ‘minimal’) conditions that an NSDI has to fulfil to gain progress, continuity and good performance over time have to be identified and taken into consideration (Masser, SDI workshop Wageningen, 2006).

3.2 NSDI definition Since the publication of the Executive Order on ‘Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure’ (President Clinton, USA, 1994), many countries throughout the world have initiated NSDIs. The goal of these infrastructures is to reduce duplication of effort among agencies, improve quality and reduce costs related to geographic information, to make



geographic data more accessible to the public, to increase the benefits of using available data, and to establish key partnerships with states, counties, cities, tribal nations, academia and the private sector to increase data availability (FGDC, 2006). It can be noticed from literature that an SDI is defined in many different ways. However, its common intent is ‘to create an environment in which all stakeholders can cooperate with each other and interact with technology to better achieve their objectives at different political/administrative levels’ (Rajabifard et al., 2003). Bregt and Crompvoets (2005) define the stakeholders of an SDI as: geo-information (GI) users, GI producers, GI companies, politicians, and standardisation companies. Although many different definitions of SDIs exist, Masser (2005) shows that four key concepts underpin all SDIs: (1) they attempt to maximize the use of geographic information, (2) they cannot be realised without coordination on the governmental part, (3) they must be user driven, and (4) a wide range of activities is involved in SDI implementation – ranging from technical to institutional matters as well as required human and financial resources.

Figure 5: SDI hierarchy (Adapted from Rajabifard et al., 2003) Figure 5 visualizes the SDI hierarchy: the national level occupies a central position in the SDI hierarchy as the critical link or hinge between the higher and the lower levels (Rajabifard et al., 2000). In other words, the SDI at the national level accommodates a central connection between the lower and higher levels to guarantee a continuous agreement on standards, policies and sharing of data. Masser (2005) describes NSDI initiatives as follows: ‘At the national level, strategic initiatives are formulated and implemented by governments in most countries to manage their national geographic information assets. In some countries, it may refer to comprehensive and inclusive GI strategies from the standpoint of the stakeholders involved, whereas in others it may describe initiatives that are partial in their coverage and limited in stakeholder participation’. From the several existing definitions of (N)SDIs, which are not all listed in this research, it can be concluded that ‘the national SDI is an initiative intended to create an enabling environment for a wide variety of users to access and retrieve complete and consistent datasets with national coverage in an easy and secure way – the national SDI forms a fundamental framework to exchange data across many agencies and disciplines (Rajabifard et al., 2003)’. This definition is used throughout this research. The most effective strategies for implementing NSDIs, most likely, differ per country. Some NSDIs accomplish more than others. Assessing the strengths and weaknesses and comparing the NSDI-programmes in developing countries assists in finding common, measurable key variables for assessment. Taking critical key variables for assessment into consideration during initiation and development may enrich all NSDIs.

Global SDI

Regional SDI

National SDI

State SDI

Local SDI

Corporate SDI



3.3 Status of NSDIs in developing countries Between 1998 – 2000, a survey to assess the nature, extent and status of SDI activities of nations around the world was accomplished by the University of Maine (USA). The survey results suggested that NSDIs were planned in about 54 countries. In South/Central-America, initiatives were noticed in 15 countries (with Argentina, Colombia, Mexico and Uruguay responding to the questionnaire in an earlier stage). In Asia, 8 initiatives were observed (with India, Indonesia, Macau, Malaysia, Mongolia and South Korea responding to the questionnaire in an earlier stage). In Africa, only South Africa responded to the questionnaire. Because of the expanded interest in geographic information, nowadays many countries and organisations have embraced SDIs. In 2002, 120 countries had already initiated projects for NSDI development (Crompvoets, 2003). Masser (2005) describes NSDI initiatives based on a model called: ‘The diffusion of innovations’ as developed by Everett Rogers. The model can be used to describe types of innovations – like SDI. Roger defined five adopter categories based on the degree to which an individual or a unit of adoption is relatively earlier in adopting new ideas than other members of the system: innovators, early adopters, early majority, late majority, and laggards. According to the model of Rogers, 11 NSDI initiatives are described as innovators/early adopters (for 1998), under which Indonesia and Malaysia from Asia. At that time (1998), no initiatives were listed in Latin America and/or Africa. Masser also describes the early adopters of NSDIs and a considerable number of developing countries in South/Central-America and Asia fall into this category. In Africa, only one initiative is noted in the early adopter category, which is South Africa. Some other, mainly sub-Saharan African countries, follow as ‘early majority’. South Africa played an important role in promoting SDI in the region (mainly sub-Saharan Africa), likewise Colombia with respect to Latin America. For the first generation of NSDIs (Rajabifard et al., 2003), data was the key driver of development and the focus of initiative development. For the second generation (as of the year 2000), the use of data and applications and the need of users are the driving forces for development. Rajabifard concludes that a switch to a more ‘socio-technical viewpoint’, including facilitation and coordination (‘people’), could be observed while the first NSDIs were more techno-centred. Masser (2005) summarises the driving forces behind NSDI initiatives as ‘the promotion of economic development, the stimulation of better government, and fostering of environmental sustainability’. Predominantly in Africa, the driving forces are related to the modernisation and environmental management. Nowadays, E-government is also mentioned in literature as an important driving force: a robust NSDI can expand the power of geo-information and enable the spatial delivery of government services (FGDC, 2006). E-government refers to the use by government agencies of information technologies that have the ability to transform relations with citizens, businesses, and other arms of government (World Bank, 2006). In the developing world, international donors are playing an important role in the enforcement of (N)SDIs. However, projects funded by the donors almost always have a restricted life span, whereas SDI developments require continuous achievements over a long period of time. Therefore, the input of the donor raises issues of sustainability. It might very well be that, as soon as the funding is exhausted, collaboration and continuity fades away. In order to better understand the concepts of the business requirements and driving forces of NSDIs in developing countries, the status is reviewed to collect information on ‘the lessons learnt’ and ‘identification of good practices’. The following sections further investigate the status of NSDIs in Latin America, Asia and Africa. As from Chapter 4, the case study countries of the three different continents are investigated and compared with each other in-depth.

3.3.1 Status Latin America To survey progress in the development of NSDIs in Latin America and the Caribbean, Lance and Hyman (2003) sent out a survey in 2000. Almost all respondents (from 18 countries) said their country had some kind of effort to develop an NSDI – mostly led by national mapping agencies. From the survey, it became clear that most of the countries have no law, government directive or other legal mechanism that calls for the development of an NSDI. Besides the lack of funding, legal matters and copyright issues were mentioned as constraints to develop NSDIs in Latin America.



Updates to the survey were collected in 2003. Nine countries responded. Those countries with a government directive, dedicated funding, pricing policies for data, a long-term strategic vision and committed personnel made significant advances (e.g. Chile). Countries without a government directive and lack of funding made considerable less progress (e.g. Panama, Venezuela). The overall impression that is created by this survey is one of a growing awareness of SDI concepts and approaches in the Americas, together with the recognition that the main obstacle to be overcome in these countries are institutional rather than technical in nature. Another survey was carried out in the period 2000 – 2002 by Crompvoets et al. (2004) to assess the worldwide developments of national clearinghouses; the access facilitator to spatial data and complementary services. Clearinghouses are key components of SDIs: they help to satisfy the objective of data sharing across networks (Hyman et al., 2003). From 1994 to 2005, 83 countries had implemented a clearinghouse on the web, with 25 countries having projects for implementation (Crompvoets, 2006). In ‘American countries’, 23 countries had implemented clearinghouses (e.g. Argentina, Bolivia, Brazil, Chile, Colombia, Uruguay, Guyana), 4 countries were initiating NSDIs and 8 countries did not show any initiative (Crompvoets, 2006). With respect to clearinghouses, Hyman et al. concluded in 2003 that many national mapping agencies had implemented clearinghouses in Latin America and the Caribbean, but noticed less adoption by environment, agriculture ministries, statistics and census agencies, or universities (Hyman et al., 2003). In most countries in Latin America the basic data with reference to topography, transport, hydrology, land cover and administrative boundaries is available in digital form, but there is often a lack of standardisation and harmonisation (Masser, 2005).

3.3.2 Status Asia Masser (2005) described both Indonesia and Malaysia as NSDI innovators based on a study carried out in 1998. Both developing countries have some form of federal system of government: they have a considerable degree of federal control over land-related matters. The driving forces for NSDI initiation in Indonesia and Malaysia were related to better planning and government – the infrastructure development was seen as a means of facilitating government planning and resource development. Both developing countries have a formal mandate from government. In Malaysia, a feasibility study was carried out first to explore the options for a national geographic information strategy. In 2003, Rajabifard and Williamson estimated that between 20 and 30 percent of the Asian countries were developing plans to initiate national SDIs. According to Crompvoets (2006), 21 countries implemented a clearinghouse in the period 1994 to 2005 in Asia-Pacific countries; from which 5 countries were in the development stage and 38 countries did not show any initiative (Crompvoets, 2006). Rajabifard also reviewed SDI activities in the Asia-Pacific region. In an article in GIS Development (2003), he explains that spatial data is traditionally collected and disseminated by a range of mandated national organisations according to a wide variety of standards in the Asia-Pacific region. Next to the absence of standards, a lack of culture to share data exists which puts constrains on the transparency and the required knowledge for decision-making. The development of an SDI initiative is a long-term process, which requires a long-term vision and strategy. As a strategy, Rajabifard suggests to speed up this process by taking short-term goals and demonstrating their results to the users and other interested people as soon as they reach completion. An important conclusion is made based on the review carried out in the Asia-Pacific region (Rajabifard, 2003): the success of an SDI is not dependent on its legal or technical culture, but whether it provides an effective communication channel to all stakeholders and permits easy access to spatial data adequately, simply, quickly, securely and at low cost. Rajabifard states that there is little justification for NSDI development if the resources are not available to keep the SDI up-to-date. Funding and resources to secure the implementation of SDI is always an important issue.



3.3.3 Status Africa In a conference on ‘Spatial Information for Sustainable Development’ in Kenya in 2001, it was concluded that in some of the African countries, widespread telecommunication and Internet access were not available, which was limiting the applicability of state-of-the-art NSDI technical solutions. It was furthermore concluded that the use of spatial information to support sustainable development would only be achieved if solutions start with realistic objectives and grow incrementally through political and market needs. South Africa is described by Masser (2005) as an early adopter of NSDI. According to Lance (2003), already in the mid-1980s efforts were made in South Africa to establish a ‘National Land Information System’. Already at that time, the ambition was to integrate data from different agencies. Although the initiative was not successful in those days, awareness for the need of data standards and cooperation between institutes was raised. Nowadays, South Africa’s spatial data infrastructure has become a funded activity within the budget of the Department of Land Affairs. However, chances for obtaining funding for SDI directly are limited in Africa. Although many countries have NSDI initiatives, it is not prominent on the political agenda due to more critical issues such as poverty, HIV/AIDS, drought, flooding etc. Lance mentions that SDI components are mostly ‘squeezed inside’ budgets for poverty alleviation, environment monitoring etc. Lance (2003) lists some 20 SDI initiatives in Africa in 2003. From 1994 to 2005, 12 countries had implemented a clearinghouse on the web, with 11 countries having projects for implementation and 28 countries not showing any initiative (Crompvoets, 2006). According to Lance (2003), the main problems facing SDI development in Africa are: political support, legal status (or enabling legislation) to support efforts, and leadership. While the national mapping agencies are the key contributors to SDI development, other entities have the political influence and funding that drives the initiatives. Kufoniyi (2004) states that African countries are realising the need to establish SDIs – the implementation of SDI in Africa is gradually but surely progressing. The need to adopt policies for promoting awareness and public access to standard and coordinated geospatial data production, management and dissemination by all sectors, including the establishment of a clearinghouse at various levels in the countries with linkages with the private sector, is slowly realised. Kufoniyi explains that most of the problems (inadequate, poor quality and inaccessible data, poor organisation and management practices, lack of adequate infrastructure and skilled human resources) could be eliminated by the establishment of ‘National Geospatial Information Policies’. A national policy would facilitate trust and respect among all stakeholders. Masser (2005) explains that there is a difference between NSDI initiatives in Europe and the Americas on the one hand and Asia and the Pacific and Africa on the other. ‘Most of the former are classified as either high income or upper middle by the World Bank whereas most of the latter are low-income countries. The differences reflect the considerable gap that exists between these two parts of the world with respect to wealth and also, to a large extent, the resources that are likely to be available to implement SDI initiatives’.

3.3.4 Comparative summary The status of NSDIs in Latin America, Asia and Africa is reviewed in above sections. As also summarised by Masser (2005), the driving forces behind the initiatives in the three continents are, in general, similar: i.e. promoting of economic development, stimulating better government and fostering environmental sustainability. Primarily in Africa, driving forces are related to the modernisation and environmental management. In the developing world, international donors are playing an important role in the implementation of (N)SDIs; in several cases the donor drives the initiative instead of the respective government (Lance, 2003). In Latin America, most data is available in digital format but the lack of standardisation and harmonisation is often a barrier. The main obstacles are institutional rather than technical in nature (Masser, 2005). In Asia, next to the absence of standards, a lack of culture to share data exists. Not all data is available digitally yet (Rajabifard, 2003). In Africa, the absence of widespread



telecommunication and Internet access and the lack of digital data are still limiting NSDI developments. Main challenges with respect to NSDI development are related to political support, legal status and leadership (Lance, 2003). Although many African countries have NSDI initiatives, it is not prominent on the political agenda due to more critical issues such as poverty, HIV/AIDS, drought, flooding etc. (Lance, 2003). From research carried out by Crompvoets (2006) on the implementation of clearinghouses, it can be concluded that Latin America has considerably more clearinghouse initiatives (implementation + initiatives) than Asia and Africa. In all continents, the awareness to realise NSDIs is growing and initiatives are (slowly) progressing. With respect to the limitations as earlier described by Rajabifard and Williamson (Chapter 1, section 1.1), developing countries appear to be working on problems related to data, organisational issues, and skilled human resources.


Chapter 4: Latin American case studies 23

4 Latin American case studies

4.1 Introduction Chapter 2 identified variables to assess NSDIs, based on reviewing existing assessment procedures and frameworks as described in literature. Chapters 4, 5, and 6 strive to answer research question 3 (how to assess and compare the NSDIs) by describing, analysing and comparing the SDI components of the six case study countries as explained in the research methodology (Chapter 2). Chapters 4, 5, and 6 also attempt to identify criteria for the selection of key variables (research question 4). After reviewing the six case study countries, from the initially identified list of variables, a reduced list of feasible variables is developed. The list of feasible variables is presented in Chapter 7 (section 7.2). Following on from the review of the NSDI initiatives in the three continents and the critical analysis and comparison of the six case study countries, a set of common case study variables is also derived. The list of all case study variables is presented in Chapter 7 (section 7.3). Chapter 4 concentrates on the Latin American case study countries (Colombia and Cuba), Chapter 5 focuses on the Asian case study countries (Nepal and Indonesia) and Chapter 6 describes the African case study countries (Nigeria and Ethiopia).

4.2 NSDI in Colombia Colombia is the fourth-largest country in South America. It shares borders with Panama (to the Northwest), Venezuela (East), Brazil (Southeast), Peru (South) and Ecuador (Southwest). Colombian territory also includes the San Andrés and Providencia island groups. In the 1990’s, an awareness of the benefits of geographic information started to grow in Colombia among municipalities, environmental agencies, oil companies, and the utilities sector (GSDI Cookbook, 2004). With a view to fulfilling their mandates, government agencies were carrying out various initiatives to develop national information systems in the areas under their jurisdiction. However, the institutions were building the information systems independently (GSDI Cookbook, 2004). In Colombia, the major drivers for the NSDI are generated from the nation’s programmes for governance to address national issues related to the environment, the economy, and social issues (from: http://www.icde.org.co/). The development of the NSDI in Colombia, the ‘Infraestructura Colombiana de Datos Espaciales’ or ‘ICDE’, is a joint venture between various agencies. The Agustin Codazzi Geographic Institute (IGAC), the national surveying and mapping agency, and other government agencies established Colombia as an early adopter and developer of NSDI (Procig, 2006; Masser, 2005). A core group of Colombian institutions have already signed agreements on how the NSDI will work, have developed NSDI working groups and have held meetings to advance their network (from: http://www.icde.org.co/). A survey on NSDI developments (Procig, 2006) describes Colombia as a success story – playing an important role in promoting SDI in the region. However, the web site dedicated to the Colombian NSDI (http://www.icde.org.co) appears to be rather outdated (last updated in 2001). Initiatives to coordinate SDI actions in Colombia at a national level face significant constraints such as decreasing budgets, inter-organisational barriers, lack of high-level support, limited capacity for research and development and lack of knowledge about the GI-market (GSDI Cookbook, 2004). Masser (2005) claims that Colombia has achieved a great deal without a formal mandate from the government, but at the same time argues that its future development requires high-level support from the government in the form of either a presidential decree or a ministerial council order. The GSDI Cookbook (2004) claims the same; it is encouraging Colombia to renew efforts by seeking and acquiring high-level support of the government for the further development of the NSDI.



The ICDE portal has recently been launched via IGAC’s website (http://www.igac.gov.co), however, through this portal only data of IGAC can be previewed. Data of ICDE participating institutes is not presented (yet) through the ICDE portal, although the different stakeholders all have their own portals for data access and retrieval.

4.2.1 Results of assessment by means of identified variables In the following sections, the results of the evaluation of the Colombian NSDI are described by means of the initially identified variables. The complete assessment can be found in Table A (Appendix). The five dynamic components of the SDI (data, people, access network, policy, standards) are explained separately. The ‘other’ component, in which all identified variables that do not fit in one of the five SDI components are placed, is being described as well. After having checked the identified variables of both Colombia and Cuba, the countries will be compared with each other with the assistance of Table H up to Table M. Mrs Lilia Patricia Arias, in charge of the Colombian NSDI initiative (ICDE) on behalf of IGAC, has reviewed and commented on the assessment table via e-mail (February 2006). In the following sections, unless otherwise indicated, the source of reference is Mrs Arias. Dr Javier Morales, a former staff member of IGAC and currently employed by ITC, has reviewed the assessment table as well. During an interview on January 16th, 2006, additional information on the ICDE developments was received via Dr Morales.

4.2.2 Data In Colombia, most data is available in digital format. The private sector is involved in helping to produce and/or update geographic data for the Colombian NSDI, the commercial sector is also hired to install, operate, and maintain the network infrastructure and/or to disseminate data. Metadata of most products can be retrieved via the web sites of the participating ICDE institutes. Bearing in mind that organisations have followed their own institutional policies and specifications for the production of spatial data, and that there is an increasing need for a consistent set of information to meet national and global perspectives for development, ICDE has the responsibility for the definition of general guidelines to improve the geographic information management. Therefore, ICDE institutions established a working group on framework data, information policies and standards (from: http://www.icde.org.co/grupos.htm). Arias mentioned that data is produced according to a national standard at different scales and levels of coverage, that the main goals are oriented towards the production of new data instead of maintaining the current data, and that new data is added on request of local projects and user demand. Colombia has its own (new) uniformity system, called ‘magna sirgas’.

4.2.3 People Well-educated GIS/SDI experts are available in Colombia. The Centre of Research and Development on Geographic Information, CIAF, is in charge of carrying out training courses. For example, short courses on SDI and metadata are organised regularly. Quite a number of Master of Science courses in Geo-informatics, Geography and Information Systems are available in Colombia. In the 1990s, NSDI awareness started to grow in Colombia. Now, most of the public institutions know about ICDE and understand its importance. Organisations have been increasing the level of participation in ICDE planning and technical implementation, but only IGAC has assigned personnel exclusively for ICDE activities. The driving forces for NSDI development in Colombia are: (1) definition of strategies that organise the production and distribution of geographic information, (2) establishment of cooperation between



producers and users of geographic information, (3) documentation of produced data and facilitation of the access, (4) improvement of decision making process, and (5) harmonisation of information systems and interoperability (from: http://www.icde.org.co). The users are not directly involved in the NSDI initiative. IGAC is currently carrying out a small survey, through its web site, to measure user satisfaction with the portal. According to Arias the satisfaction level is increasing because the access to data has been improved. No exact information on the number of users of the NSDI is available.

4.2.4 Access network Consolidated as one of the ICDE working groups, the clearinghouse has focused on implementing distributed metadata catalogues and online services to facilitate the discovery and use of geographic information. The ICDE portal has recently been launched via IGAC’s website (http://www.igac.gov.co), however, through this portal only data of IGAC can be previewed. Data of ICDE participating institutes is not being presented (yet) through the ICDE portal although the different stakeholders all have their own portals ready. According to Dr Morales (interview January 16th, 2005), the different metadata servers could be technically linked to each other rather easy because agreements on standards have been made already. However, it is not clear at this moment if all participating institutes have followed the agreed regulations on standardisation. No information on the number of visitors to the portal is available. The language used in the portal is Spanish; responses to queries are rather slow. No E-business services have been presented up to now.

4.2.5 Policies Dr Morales explained that in Colombia no formal mandate of the government with respect to NSDI implementation exists. The previous director of IGAC had a clear vision on the benefits of a Colombian NSDI and strongly pursued its implementation. However, for an NSDI to be successful, the government must participate and continuously contribute and support the NSDI developments (FGDC, 2006) as well. Contributions and efforts to further develop the NSDI are expected from all stakeholders – developments cannot depend on one person and/or organisation. IGAC guides the process but no official leader has been appointed. IGAC realises that high-level support seems to be the major area requiring further efforts. No formal legal agreements exist to address issues such as privacy, access, use, pricing and liability. Suppliers have come to an agreement to facilitate the access to data (from: http://www.icde.org.co/productores.htm). IGAC is planning to propose an international credit contract with a multilateral organisation in order to further finance the NSDI developments.

4.2.6 Standards A working group on standards and metadata is in place. A national geographic metadata standard was defined in March 1999 based on the ISO and FGDC standards. IGAC developed a metadata engine to create, edit, validate and publish metadata. Up to now (2006), ICDE institutions have created about 180,000 metadata units. ‘Interoperability’ as such has not been implemented. According to Arias, a spatial object catalogue is being developed by IGAC, which still has to be discussed with the different participating institutions.



4.2.7 Other Although there is a general definition of Colombia’s NSDI status and scope, it is necessary to link a greater number of partners. It should be assessed if the actual ICDE vision meets the needs of the different type of stakeholders. ICDE has struggled to gain visibility; currently the public institutions know and understand the importance. Arias notices a number of challenges in Colombia, most significantly, the organisational issues. No formal mandate exists to build the ICDE. The institutions continue to focus on the development of geographic information suitable for their own needs. Secondly, the policy issues. No formal legal agreements exist to address issues such as privacy, access, use, pricing and liability. Furthermore, no user need study has been carried out and no information is available regarding the costs and benefits of geographic information in the decision making process. Colombia has a bottom-up NSDI development approach. The (government) agencies decided to work together. IGAC is promoting high-level top-down support to institutionalise relationships. Looking at the evaluation framework of Kok and Van Loenen (2004) (section 2.2.1), Colombia can be placed between the ‘exchange stage’ (focus on standardisation and datasets) and the ‘intermediary stage’ (awareness for cooperation). Arias mentions that the main efforts, at present, are towards the formulation of policy.

4.3 NSDI in Cuba Cuba is the Caribbean's largest and least commercialised island and one of the world's last bastions of communism. Cuba is administered by a centralised government with 14 provinces and 169 municipalities (Delgado, 2005). Currently, the Hydrographical and Geodetic Service is in charge of the general coordination of the Spatial Data Infrastructure of the Cuban Republic (‘Infraestructura de Datos Espaciales de la República de Cuba’ or ‘IDERC’), supported by the National Office of Society Information of the Ministry of Informatics and Communication. In 1999, the Hydrographical and Geodetic Service of Cuba identified the need to develop an NSDI. At that time, no SDI initiative existed in Cuba. During the first stage of the project (2001 – 2003), the so-called ‘capacity building stage’, activities such as seminars and workshops related to SDI took place. For example, in 2002 a representative of IGAC, Colombia, conducted a seminar on the principles of SDIs in Cuba. The main actors of the IDERC initiative were present during the seminar (Delgado, 2003). The University of Wisconsin-Madison (USA) and the Ministry of Informatics and Communications of Cuba organised a workshop on metadata, clearinghouses and map servers in 2003. This workshop created awareness and NSDI support in Cuba (Delgado, 2003). Other activities that took place during the initial phase of the project were the first establishments of inter-institutional relationships, the first steps towards a legal framework and the implementation of Open Geospatial Consortium (OGC) specifications at the Hydrological and Geodetic Service. During the second stage of the project (2004 – present), Cuba launched the Geospatial Portal as part of the NSDI (http://www.iderc.co.cu). Delgado (2005) considers the launching of the portal as an important step in the Cuban NSDI history; however, she also states that further work will have to be done to tackle issues such as the participation of all stakeholders to share geographic data effectively.

4.3.1 Results of assessment by means of identified variables In the following sections, the results of the evaluation of the Cuban NSDI are described by means of the identified variables. The complete assessment can be found in Table B (Appendix). The five dynamic components of the SDI (data, people, access network, policy, standards) are explained separately. The ‘other’ component, in which all identified variables that do not fit in one of the five SDI components are placed, is being described as well.



Ms Tatiana Delgado, in charge of the Cuban NSDI initiative (IDERC), has reviewed and commented on the assessment table via the e-mail (February 2006). In the following sections, unless otherwise indicated, the source of reference is Ms Delgado.

4.3.2 Data Delgado mentions that at present, only the national mapping agency is providing data to IDERC; they take care of uniformity. In future, when other providers start to supply data, measurements to keep uniformity should be adopted. In Cuba, not all data is available in digital format yet. An inventory of existing spatial data is currently being undertaken as part of the work of the commission in charge of IDERC. The commission wants to increase the availability of data and to add new data to the portal. The commission is also working on a maintenance strategy – at present data is only being updated on demand of clients (including the demand of the State).

4.3.3 People According to Delgado, some 10 professionals with good SDI skills are available in Cuba. Another 40 professionals are available with ‘moderate’ skills. Better-trained professionals are needed. In Cuba, plans to start a University Degree on Geo-informatics are being initiated at the moment. Mainly IT/programming skills are lacking – GI(S) education is available. Delgado explains that the main driving force in Cuba for NSDI development is the mandate of the government. Awareness on importance exists but is still rather low. A communication strategy has been developed to explain the importance of the NSDI initiative to the different stakeholders. Several conferences and workshops are being organised to increase awareness and to give information to mainly the political and technical sectors. The user involvement in the initiative is still limited but will hopefully increase because of the newly developed communication strategy. No information on the number of users is available. Delgado believes that the user satisfaction is limited because of the few services offered by the portal.

4.3.4 Access network In 2005, Cuba launched the Geospatial Portal (http://www.iderc.co.cu). Delgado (2005) considers the launching of the portal as an important step in the Cuban NSDI history; however, she also states that further work will have to be done to tackle issues such as the participation of all stakeholders to share geographic data effectively. At present, only the Hydrographic and Geodetic Service supplies data to the portal. Some 1500 visitors access the portal on a monthly basis. The portal is updated every three months. Through the portal, tourist can purchase maps; this initiative will certainly increase the visibility of the Cuban NSDI (for an example: http://bazar.cuba.cu/geocuba/).

4.3.5 Policies In November 2005, the Commission to realise the Cuban NSDI was officially approved by the government (‘Comisión Nacional de la Infraestructura de Datos Espaciales de la República de Cuba’ or ‘CIDERC’). The Cuban government invests approximately 300,000 US$ in the NSDI development on an annual basis. A strategy document up to the year 2010 has been developed. Legal and institutional arrangements are unknown.



4.3.6 Standards Although ISO standards have been adopted in Cuba, standardisation is considered as a major challenge. Data is currently produced in different formats. Metadata availability is poor; a strategy has been formalised to increase this. Open Geospatial Consortium (OGC) specifications have been implemented at the Hydrological and Geodetic Service.

4.3.7 Other According to Delgado, Cuba is facing the following challenges: the current implementation and the maintenance of the infrastructure in the future. Other challenges that can be noticed are: lack of human resources to implement and work on the initiative, organisational arrangements (policy), and the continuity of the funding. Cuba has a top-down NSDI development approach. Looking at the evaluation framework of Kok and Van Loenen (2004) (section 2.2.1), Cuba can be placed between the ‘exchange stage’ (focus on standardisation and datasets) and the ‘intermediary stage’ (awareness for cooperation).

4.4 Comparison As mentioned in section 2.3, not all identified variables are (easily) measurable. After reviewing all the variables of the case study countries, the identified list can be reduced to a list of feasible variables. To reduce the number of identified variables, the set of rules as explained in section 2.3.2 is applied. The final set of feasible variables can be found in Chapter 7 (section 7.2). To identify the common case study variables, all the variables describing Colombia and Cuba have to be compared with each other. To ease comparison, possible answers have been ‘re-classified’ in Table G (Appendix), which are used for the different SDI components in Table H up to Table M (Appendix). The comparison tables are based on the country descriptions (literature, interview national coordinators) as earlier presented in Table A and Table B (Appendix). Are there noticeable differences between the variables of the case study countries? Or has the variable not been arranged yet? Again the UNDP rule to look at the key changes, as explained in section 2.1, is applied to select the relevant case study variables. The following paragraphs highlight the main findings per SDI component. Colombia has been one of the early adopters of NSDI and has played an important role in promoting SDI in the region. A representative of IGAC actually conducted a workshop in Cuba on the principles of SDI in 2002. Looking at the data component (Table H, Appendix), some similarities and differences can be noticed between Colombia and Cuba. Core data sets, formats, quality, resolution and uniformity have all been arranged considerably well in the Latin case study countries. In Colombia most of the data is available in digital format. Cuba is currently undertaking an inventory of existing spatial data – Cuba would like to increase the availability and to add new data to its NSDI. Not all data is digitally available yet. Data maintenance and updating has low priority in Colombia and Cuba; data is only updated on the request of clients. With respect to people (Table I, Appendix), contrary to Colombia, Cuba cannot give a definition of the core data sets. In both countries GI education is available. For example, in Colombia, short courses on SDI and metadata can be followed and several postgraduate courses on GI are available. Cuba is developing a new MSc on Geo-Informatics. Colombia has well-trained professionals but according to Delgado, Cuba could use more SDI experts to speed up and improve NSDI development. Most public institutions in Colombia are aware of the importance of the NSDI. In Cuba, the awareness is steadily growing but could be improved. The user satisfaction needs improvement in both Colombia and Cuba. Both countries cannot present numbers on user involvement and private participation in the NSDI.



Research programmes, conferences and journals on SDI are available in both countries. On the willingness to share data, no information is available. Both Latin case study countries have access networks (Table J, Appendix). Through the recently launched portal of Colombia, only data of IGAC can be previewed. The other participating institutes have their own access networks; the different servers should be linked to one common access network. Responses to queries in the Colombian portal are rather slow; the portal appears not to be very reliable. In Cuba, only one supplier (the leading institute) provides the portal with data. Delgado mentions that the user satisfaction is limited. Maintenance is one of the tools to keep the user satisfied; therefore the website of the Cuban portal gets updated every three months. The portal of Cuba follows the latest trends (OGC – WMS etc.) and even started offering e-services (E-business). With respect to policy (Table K, Appendix), in Cuba the formal mandate drives the initiative. Colombia has no mandate and no ‘official’ leader; driving forces are related to cooperation, the facilitation of data access, improvement of the decision-making process and the harmonisation of information systems and interoperability. Initiatives to coordinate SDI actions in Colombia at a national level face significant constraints like decreasing budgets, inter-organisational barriers, lack of high-level support, limited capacity for research and development and lack of knowledge about the GI-market (GSDI Cookbook, 2004, Masser, 2005). Furthermore, the socio-political situation in Colombia is very unstable. Colombia hopes to obtain a credit contract with a multilateral organisation to give the ICDE a push forward. In Colombia an agreement between the data suppliers to facilitate access to data has been signed. Unfortunately, no information on Cuban’s legal and institutional arrangements is available. Long-term, political NSDI visions have not been developed in Colombia and Cuba yet. The international ISO metadata standard has been adopted in both case study countries (Table L, Appendix). Colombia developed a metadata engine. In Cuba, the availability of metadata is limited. On the other hand, as mentioned before, Cuba is following the latest OGC trends such as WMS. The comparison of the other component (Table M, Appendix) clearly shows the different NSDI approaches of Colombia and Cuba. Colombia has a bottom-up, decentralised approach (without formal mandate) while Cuba has a top-down, centralised NSDI approach (with formal mandate). NSDI definitions of both countries are similar. Although Colombia started its initiative much earlier, both countries are in similar stages of development and are both facing difficulties with respect to organisational arrangements. Colombia could probably make a significant step forward by linking the different metadata servers and to present available metadata through a common ICDE clearinghouse.

4.5 Selection of case study variables The analysis and comparison of the case study countries increases insight in the driving forces behind the NSDIs. The necessary, minimum conditions for countries to make progress and ensure continuity over time are revealed. The appreciation of these issues assists in the identification of case study variables. For example, while comparing the Latin case study countries in section 4.4, the formal mandate* appears to be very important since the Cuban initiative (with mandate) appears to progres faster than the Colombia initiative (without mandate). Colombia is confronted with difficulties to coordinate its NSDI activities because of the lack of high-level support (GSDI Cookbook 2004; Masser 2005; and Arias 2006). Participating institutes are building their own access networks instead of working towards a common access network. In Colombia most data is available in digital format. In Cuba not all data is available digitally yet. To supply the access network with data and/or metadata, data has to be available digitally. Cuba understands this and intends to increase the availability and, moreover, to add new data to the NSDI. Insufficient SDI experts are available in Cuba. People require training to implement the different SDI components. In Cuba, the first step towards a MSc course on Geo-Informatics has been taken. User satisfaction and awareness has to increase in both countries. Cuba has developed a communication

* Italics refer to identified variables (Table 2)



strategy to do so. Colombia is currently carrying out a (small) survey through IGAC’s website to measure satisfaction. Both countries have access networks in place. As explained by Crompvoets (2006), the delivery mechanism is one of the key features of an NSDI. It is regarded as the access network of an NSDI, facilitating the nation’s spatial data and related services. The NSDI should ideally provide access to spatial data adequately, simply, quickly, securely and at low cost. The access network is (rather) transparent and visible and is therefore considered as very important (Crompvoets, 2006). Data of only one supplier is presented through the portals of both countries (‘product portals’). In Colombia, the different (metadata) servers of the participating institutes should be linked together. Responses to queries are rather slow; the Colombian portal appears not to be very reliable. Cuba is working on the facilitation of data access (involvement of more stakeholders) and does follow the latest (OGC) technological trends closely. Colombia and Cuba did not develop a long-term, political NSDI vision yet. In the dynamic NSDI environment, a long-term vision is considered as very important. A vision of the NSDI is aimed at improving the economic, environmental and social well being of communities and citizens. It recognizes that the availability of and access to spatial data will increase knowledge and understanding and will improve decision-making capabilities (UCGIS, 2006). Not much information is available on legal and institutional arrangements for both countries. Colombia’s ICDE website presenting this information is rather outdated (2001). Standards and metadata standards have been adopted in the Latin case study countries. In Colombia, at this moment, it is not clear if all participating institutes have followed the agreed upon regulations on standardisation (Morales, interview 2006) which will obviously complicate the linkage of the metadata servers. Cuba lacks metadata entries. Next to the in-depth assessments of Colombia and Cuba, in Chapter 3 the NSDI developments in Latin America have been reviewed. In literature, several SDI experts have given indications for the criteria to select key variables to assess NSDIs. For example, looking at Latin America: Lance and Hymann (2003) concluded from their survey that those countries in Latin America with a government directive, dedicated funding, pricing policies for data, a long-term strategic vision and committed personnel made significant advances. Besides the lack of funding, legal matters and copyright issues were mentioned as constraints to develop NSDIs in Latin America. The main obstacles to be overcome in the Latin American countries are institutional rather than technical in nature. Both Arias and Delgado (e-mail 2006) confirm this statement by mentioning the institutional issues as a challenge for the further implementation of the NSDIs in Colombia and Cuba. Masser (2005) concluded that most Latin America countries have the basic data with reference to topography, transport, hydrology, land cover and administrative boundaries available in digital form, but often lack standardisation and harmonisation. This is certainly true in the case study countries. Colombia defined standards in 1999 but is not sure if institutes have followed the regulations. In Cuba, standardisation is considered a major challenge. Limited capacity for research and development slows down SDI development (GSDI Cookbook, 2004). Both Colombia and Cuba do have research programmes to support SDI developments in place. However, especially in Cuba, insufficient well-trained SDI experts are available to carry out the research.



From combining the above-described research in sections 4.4 and 4.5 (the comparison of the variables as can be found in Table H up to Table M and the literature review of Chapter 3), the case study variables of Colombia and Cuba may be summarised as follows: Data component: Availability of digital data:

If data is not available in digital format, they cannot be previewed and/or exchanged through the access network. The availability of digital data is considered as very relevant. Cuba does not have all data available in digital format yet. Data of only one provider is presented through the portals of both Colombia and Cuba (‘product portals’).

The quality of data: The data should be of good quality (complete, consistent – see definition in Appendix). If not, users might loose interest in sharing.

Updating – adding of new data: Cuba wants to increase data availability and to add new data to the NSDI to increase user satisfaction. In Colombia, new data is added on request of local projects and user demand only.

Maintaining of the datasets: At the moment, data maintenance has no priority in Colombia and Cuba. However, the importance of maintenance is understood.

People component: Human capital:

People require training to implement the different SDI components. For example, as explained by Delgado, insufficient experts with SDI knowledge are currently available in Cuba. Colombia claims to have sufficient SDI experts.

Capacity building: Masser (2005) mentioned that the need for capacity building initiatives to be developed in parallel to the processes of NSDI implementation is often underestimated (see Chapter 1). This is particularly important in developing countries where the implementation of NSDI initiatives is often dependent on a limited number of staff with the necessary geographic information management skills. Although in Cuba short SDI courses and workshops can be followed, Delgado explained that Cuba is in need of SDI experts – people require short courses, workshops etc. to implement the different SDI components.

Capacity for NSDI research and development: Both Colombia and Cuba do have research programmes to support SDI developments in place. However, especially in Cuba, insufficient well-trained SDI experts are available to carry out the research.

SDI education: Although education is available in Colombia and Cuba, in Cuba insufficient experts with SDI knowledge are available. Cuba is currently developing an MSc in Geo-Informatics.

User satisfaction: The whole infrastructure is being developed for users – users should be satisfied. Especially Cuba

mentions that the satisfaction is lagging behind because of the limited services offered through the portal. Colombia is currently measuring user satisfaction by means of a small questionnaire through IGAC’s website. Awareness:

SDIs facilitate the collection, maintenance, dissemination, and use of spatial information. As earlier mentioned in Chapter 1, SDIs could produce significant human and resource savings and returns by reducing duplication and facilitating integration (Chan et al., 2001). If the SDI principles are not well understood, cooperation will be difficult to achieve. The awareness level is moderate in both Colombia and Cuba.

Access network component: The availability of a delivery mechanism (access network):

Both countries have established a discovery and delivery mechanism. Colombia can improve its access network by linking the different (meta)data servers. Cuba tries to encourage the participation of all stakeholders to share geographic data effectively through the portal. At the moment, likewise in Colombia, only the leading institute supplies data to the portal (‘product portal’).



Reliability: Responses to queries in the Colombian portal are rather slow. Sometimes the portal even freezes. The performance and reliability could be improved.

Policy component: Existence of a directive of the government:

Developments in Colombia seem to lag behind because of the lack of support of the government (GSDI Cookbook, 2004; Masser, 2005). The Cuban NSDI has a governmental directive.

Availability of funding for NSDI development: There is a necessity to formulate funding models, which will sustain the SDI in the long term (Giff and Coleman, 2003). To secure funding is a relevant issue not only in developing countries; NSDIs require constant accomplishments and financial input over a long period of time. On the funding of the Colombian NSDI, no information is available. In Cuba, approximately 300,000 US$ is available on a yearly basis. The sustainability of funding is considered a challenge in both Colombia and Cuba.

The presence of a long-term strategic vision: As explained earlier, a long-term strategic vision is considered as very important. Colombia and Cuba have not developed long-term NSDI visions yet.

The availability of a suitable institutional framework: A suitable institution framework is needed to provide the leadership, direction and priority setting to enable a focused approach for the vision of an NSDI. The main obstacles to be overcome in the Latin American countries are institutional rather than technical in nature (Lance and Hymann, 2003). Both Arias and Delgado confirm the statement of Lance and Hymann by mentioning the institutional arrangements as a major challenge.

The presence of policy documents describing legal arrangements: The legal and regulatory environment of SDIs is in a stage of dynamic development (Kabel, 2000). Mostly, data is acquired, processed and maintained by different institutions. Arrangements of legal aspects and policy towards geo-information should be clearly documented. No formal legal agreements exist to address issues such as privacy, access, use, pricing and liability in Colombia. With respect to Cuba, no information is available.

The existence of leadership: Colombia has no mandate and no ‘official’ leader. The GSDI Cookbook (2004) is encouraging Colombia to seek and acquire high-level support of the government for the further development of the NSDI.

Socio-political stability: It is difficult to implement NSDIs, partly due to the shifts in bureaucratic power that are associated with it. For an NSDI to be successful, government must participate and continuously contribute and support the NSDI developments (FGDC, 2006). The socio-political situation in Colombia is unstable.

Standards component: Adoption of standards:

In Latin America, most basic data is available in digital format (Masser, 2005) but often lack standardisation and harmonisation. Standards, access and interoperability are suggested as the key mechanism for ensuring an integrated approach – effective standards ease difficulties in the efficient use and maintenance of NSDIs (Croswell, 2000). In both Colombia and Cuba, standardisation needs support and encouragement.

Availability of metadata: Colombia adopted a metadata standard based on ISO and FGDC. Cuba adopted the ISO standard. One of the challenges faced by users of data is the lack of information about information sources that might be relevant to their needs. Appropriate metadata services can help them to find out this information. Colombia developed a metadata engine; metadata is poorly documented in Cuba.

Other component: Challenges:

The other component shows the different NSDI approaches of Colombia and Cuba (bottom-up versus top-down, no mandate versus mandate). Although Colombia started its initiative much earlier, both countries are at similar stage of development and both face difficulties with respect to organisational arrangements (see policy component).



Table 3 presents the case study variables of the Latin Case study countries: Colombia and Cuba. Table 3: Comparison case study variables between Colombia and Cuba Latin America SDI components

Case study variables

Col

ombi

a

Cub

a

Data

Availability of digital datasets Good quality of data sets Updating – adding new data Maintaining datasets

Considerable

Good Yes No

Some

Acceptable No No

People

Human capital (‘resources’) Capacity building

Research and development capacity

SDI education User satisfaction Awareness of SDI concepts

Sufficient

Yes

Yes

Available Moderate Moderate

Not sufficient

Yes Limited

Yes Not sufficient

people Available Not good Moderate

Access network

Availability of delivery mechanism

Reliability Performance

Yes

Product portal Reasonable Reasonable

Yes

Product portal Reasonable Reasonable

Policy

Existence of directive Funding

Long-term strategic vision Institutional arrangements in place Legal arrangements in place Existence of leadership Socio-political stability

Not present

Yes Unstable

No No No

Not present Unstable

Present

Yes Unstable

No No information No information

Present Stable

Standards

Adoption of standards

Availability of metadata Interoperability

Yes

Needs encouragement

Yes No

Yes

Needs encouragement

Partly Yes

Other Institutional arrangements Development approach

Challenge Bottom-up

Challenge Top-down

In Chapter 7, section 7.3, the case study variables of all six case study countries are presented together in one Table.


Chapter 5: Asian case studies 35

5 Asian case studies

5.1 Introduction Chapter 2 identified variables to assess NSDIs, based on reviewing existing assessment procedures and frameworks as described in literature. Chapter 5 strives to answer research question 3 (how to assess and compare the NSDIs) by describing, analysing and comparing the NSDIs of the Asian case study countries (Nepal and Indonesia) as explained in the research methodology (Chapter 2). Similar to the previous Chapter, this Chapter attempts to identify criteria for selection of key variables (research question 4).

5.2 NSDI in Nepal Nepal is located on the southern part of the Himalaya, wedged between China to the north and India to the south. Budhathoki et al. (not dated) describe the history of GI in Nepal as follows: In the 1990s, not too many GIS activities were observed in Nepal. Activities were focused on the digital conversion of maps, without understanding all possibilities that geographic information systems were offering. According to Budhathoki, ‘small islands’ of spatial databases were built in the country. In the late 1990s, discussions on the need for a more comprehensive IT policy for Nepal started. The concept of SDIs was more and more adopted around the world and also reached Nepal. There was an increased awareness in the professional market that Nepal would be wasting a considerable sum of its limited resources in the (duplicated) creation of spatial data unless a mechanism for coordinated development of the several spatial databases was to be constructed soon. Those Nepalese who attended academic courses, training and/or symposiums in geo-spatial science and related studies abroad, started lobbying for an NSDI in Nepal. In 2002, the Nepalese government realised the importance of supporting the creation of an infrastructure to facilitate the sharing of geographical information within the country. The ‘National Geographic Information Infrastructure’ (NGII) programme, the national level SDI initiative in Nepal, was established in 2002 and had the support from the European Commission (EC) during the first 3 years. The government of Nepal initiated the NGII programme with the objective to ‘avoid duplication in spatial data creation and usage through the networking of different GI systems in the country’. Kayastha (2005) further explains this objective by stating that the Nepalese government aims to maximize the economic, social and environmental benefits from the investment already made with the establishment of the NGII.

5.2.1 Results of assessment by means of identified variables In the following sections, the results of the evaluation of the Nepalese NSDI are described by means of the initially identified variables. The complete assessment can be found in Table C (Appendix). Each of the five dynamic components of the SDI (data, people, access network, policy, standards) is explained. The ‘other’ component, in which all identified variables that do not fit in one of the five SDI components are placed, is described as well. Mr Raja Ram Chhatkuli, the National Director of the NGII Programme, has reviewed and commented on the assessment table via e-mail (December 2005 / January 2006). In the following sections, unless otherwise indicated, the source of reference is Mr Chhatkuli.



5.2.2 Data Although the tendency of most data producers gradually changes towards sharing of datasets, it is still very difficult to find out whether data of a particular kind exists. Most participating agencies in the NGII do not have data in digital form yet or have digital data in a non-sharable format. Almost all available data (topographic maps, ortho-photos) are produced by the Survey Department – the leading organisation behind the Nepalese NSDI initiative. According to Sharma (2004), the NSDI of Nepal is ‘a system in the beginning state’ where only the establishment of the national topographic and population census databases have been incorporated. Mr Chhatkuli explains that the main concern is the populating of the infrastructure with data itself wheras updating and adding new data has no priority as yet.

5.2.3 People Nepal has many qualified and trained GIS professionals. Nevertheless, most universities in Nepal focus on spatial data handling and analysis rather than emphasising on the importance of standards, data sharing and the explanation of the benefits of developing SDIs. A low level of awareness exists with decision-makers regarding the potential benefits of SDIs. The awareness level of those who studied abroad is much higher (they started lobbying for the NSDI in Nepal). The importance of capacity building activities is realised (short courses, workshops etc.), but the activities did not happen yet. The driving forces behind the initiative can be explained as follows: (1) realisation of wasting a considerable sum of limited resources in the (duplicated) creation of spatial data, (2) mandate of government (2002), (3) assistance of the European Commission (EC), and (4) drive for new public management. A smooth expansion of the NGII requires that due consideration and meaningful alliance has to be developed with key stakeholders. Chhatkuli explains that the private sector, academic sector and user community should be involved as well; this has not yet been done in Nepal. A timely involvement of the users – for whom the whole infrastructure is being developed – will ensure that the NGII will ultimately meet the expectations of the users and will be operational in a sustainable matter. No information on the number of users is available. In Nepal, no research programme exists to support the development of the NSDI.

5.2.4 Access network A metadata system is in place and some data (of the Survey Department) is already available. However, the portal (http://www.dosm.gov.np/) is rather unstable and most of the time not reachable. Chhatkuli (2005) suggested initiating a clearinghouse but realised that such effort requires consensus among the data producers, which is not yet reached.

5.2.5 Policies Nepal has a formal mandate of the government to establish a ‘National Geographic Information Infrastructure’ (2002). During the first three years of development, the programme had the support from the European Commission. At this moment, the government of Nepal funds the initiative. The Survey Department in Nepal realised that the proposed ‘NGII’ programme is ‘the call of the day’ (Acharya et al., not dated). Like national mapping agencies all over the world, the Survey Department has to make important decisions: there is a growing tendency for privatisation, competitiveness and a drive for new public management. On one side there is a reduction in budget and decrease in positions, while on the other side mapping organisations are pressed with new user-demands. The



Nepalese government insists on greater economy, efficiency and effectiveness in public spending (Acharya et al., not dated). The Survey Department realised that the NGII is a multi-functional and inter-organisational activity and has taken the role of focal point for NSDI establishment as well as keeping its traditional role of National Mapping Agency. Inter-organisational working groups (Standards, Pricing and Copyrights) have been established already to work towards the NSDI, with again a lead role of the Survey Department. The development of a proper institutional framework for creating capacity and willingness is considered more challenging and difficult than overcoming technical difficulties such as setting-up a clearinghouse. A continued political, administrative and technological commitment is needed to develop an NSDI. However, it is not always easy to maintain policy continuity in a developing country like Nepal. A long-term political vision has not yet been developed.

5.2.6 Standards An inter-organisational workgroup on standards has been established. Most of the participating agencies do not have data in digital format – if digital data exists, a significant amount of time is required to bring them into a sharable form. With respect to the metadata system, the FGDC standard has been adopted.

5.2.7 Other Nepal is undertaking a ‘bottom-up approach’ for NSDI establishment. According to Chhatkuli, it tries to make best use of already available resources. The Survey Department realises that there are problems related to horizontal communication within the public sector. For example, the existence, communication and diffusion of GIS knowledge among end-users, technical professionals and decision-makers are crucial but not yet happening. According to Chhatkuli, the main challenges for the Nepalese NSDI are: the proper institutional setup, common standards, SDI culture, and sustainability.

5.3 NSDI in Indonesia The Republic of Indonesia, located in Southeast Asia, is an archipelago of nearly 17,000 islands with a total coastline exceeding 81,000 km. Masser (2005) explains that in 1993, an interagency working group was established to identify the most important land data users and producers to establish a national geographic information system for planning purposes in Indonesia. Bakosurtanal, the National Coordinating Agency for Surveying and Mapping, coordinated this working group. Indonesia was one of the first countries to initiate an NSDI. In the third meeting of the working group in 1997, the data providers and user institutions were identified, a national catalogue was introduced and the copyright issue was discussed. At that time, several institutions had their products available in digital format but they were concerned about the security of their products. Indonesia has a large collection of spatial data. Data is collected and managed by many government agencies at all levels: national, provincial, district and municipal. Data is stored in different standards (Matindas et al., 2004). In 2000, the working group agreed that the Indonesian Spatial Data Infrastructure (ISDI) should be built (Matindas et al., 2004). The objective of the ISDI, the national level SDI initiative in Indonesia, is to make available fundamental datasets within the Indonesian territory with a national standard and accessible to the



data users. Bakosurtanal has broken down the development of the infrastructure in phases. In 2001, the first phase started with the development of ISDI nodes, databases and metadata, a clearinghouse and standards. The following phase, which started in 2005, focuses on the improvement of coordination mechanisms, the completion of the spatial databases and national metadata developments, and the activation of the clearinghouse. Bakosurtanal has developed a long-term ISDI vision, up to 2020. Issues such as the implementation of local clearinghouses and the maintenance of spatial fundamental data, standards etc. have been taken into consideration. According to Puntodewo (2005), the perdurable commitment (programme, human resources and funding) is the main challenge in Indonesia.

5.3.1 Results of assessment by means of identified variables In the following sections, the results of the evaluation of the Indonesian NSDI are described by means of the identified variables. The complete assessment can be found in Table D (Appendix). All five dynamic components of the SDI (data, people, access network, policy, standards) have been investigated and will be described. The ‘other’ component, in which all identified variables that do not fit under the five SDI components are placed, is being described as well. Mr Bebas Purnawan, the National Coordinator of the ISDI Programme (Bakosurtanal), has reviewed and commented on the assessment table via e-mail (February 2006). In the following sections, unless otherwise indicated, the source of reference is Mr Purnawan.

5.3.2 Data Most of the fundamental data sets, as well as the thematic data sets, are available in digital format. Government institutions produce most data; the government requires that all producers deliver data to users (Puntedewo and Nataprawira, 2004). However, most data is produced for own use, awareness to disseminate is not always present (Matindas et al., 2004). Unfortunately, not all data does yet conform to one spatial reference system; standardisation has to be encouraged (Puntodewo et al., 2004). A draft document on data management has been developed. This document has been created for the agencies to develop and maintain their spatial databases in such way that data is of good quality, well maintained and can be nationally integrated (Matindas et al., 2004). In the second phase of the ISDI initiative (2005 – 2009), Indonesia started with the development of a National Spatial Information System in order to encourage standardised data collection.

5.3.3 People The quantity and quality of human resources is inadequate (Puntedewo and Nataprawira, 2004). A human resource development plan exists, personnel are to be recruited and trained. Bakosurtanal has the mandate to increase the capability of SDI human resources and conducts workshops to regional high rank officials to create SDI awareness. Providing regular training and education needs cooperation between institutions in improving human resources capability. The driving forces behind the initiative can be explained as follows: (1) reaching of synergy among all government institutions, private sector, universities, non-governmental organisations (NGOs), and the community, (2) to optimise community participation in spatial data acquisition and dissemination in order to support economic growth, improvement of social and environmental conditions, and (3) government institutions to put good governance into practice. A forum on research and development has been established, a provincial research council will be defined. No information on the number of users of the NSDI is available.



5.3.4 Access network Within the provincial and local government, little understanding on the use of the clearinghouse exists. However, understanding is a necessity, because the development is funded by all governments in Indonesia including the central, provincial and local government (Puntedewo and Nataprawira, 2004). The development of the clearinghouse is a long and complex process because it involves a large number of datasets, many data producing institutes and quite a number of professionals (Puntedewo and Nataprawira, 2004). The FGDC standard has been adopted for the collection of metadata; however, the existence of metadata is inappropriate in almost all data producing institutes (Puntedewo and Nataprawira, 2004). The access network can be accessed through the website of Bakosurtanal; but requires improvement. The portal is rather slow. Bakosurtanal does expect to receive a Japanese grant to improve the access network (from: http://www.mofa.go.jp/policy/oda/longlist/indonesia.html).

5.3.5 Policies Indonesia does have a presidential instruction, which regulates the operation of SDIs. Abdulharis et al. (2005) describe five recommendations for the establishment of legal aspects and policy within the Indonesian ISDI: (1) the foundation of a permanent administrative body, (2) the implementation of regulations with respect to copyright and trade secrecy, (3) the determination of the basic access to geo-information based on the nature of the user (public, private, educational) and the nature of the use (commercial, non-commercial purpose), (4) description of the copyright issue, and (5) determination of online access to geo-information. According to Abdulharis et al., these arrangements will accelerate the development of the ISDI. A long-term vision document (up to 2020) is available. It describes, for example, the implementation of clearinghouses at different levels and the maintenance of fundamental data. The government of Indonesia has issued a presidential instruction concerning E-government (Puntodewo et al., 2004).

5.3.6 Standards The FGDC standards have been adopted. However, the existence of standardised metadata in almost all data producing institutes is inappropriate (Puntedewo and Nataprawira, 2004). In the second phase of the ISDI initiative (2005 – 2009), Indonesia started with the development of a National Spatial Information System for the standardised data collection. However, regulations seem not to be available yet.

5.3.7 Other The main challenges for the Indonesian NSDI are the recognition from government and parliament, maintaining the commitment (programme, human resources and funding), getting inter-institutional commitment, and the creation of regulations. Indonesia has a top-down NSDI development approach.

5.4 Comparison As mentioned in section 2.3, not all identified variables are (easily) measurable. After reviewing all the variables of the case study countries, the identified list can be reduced to a list of feasible variables. To



reduce the number of variables, the set of rules as explained in section 2.3.2 is applied. The final set of feasible variables can be found in Chapter 7 (section 7.2). To identify the common case study variables, all the variables describing Nepal and Indonesia have to be compared with each other. To ease comparison, possible answers have been ‘pre-classified’ in Table G (Appendix), which are used in Table H up to Table M (Appendix). The comparison tables are based on the country descriptions (literature, interview national coordinators) as earlier presented in Table C and Table D (Appendix). Are there noticeable differences between the variables of the case study countries? Or has the variable not been arranged yet? Again the UNDP rule to look at the key changes, as explained in section 2.1, is applied to select the case study variables. The following paragraphs highlight the main finding per SDI component. Indonesia has been one of the first countries to initiate an NSDI. Nepal started its initiative at the end of the nineties; Nepalese who studied abroad started lobbying for the NSDI. Looking at the data component (Table H, Appendix), some similarities and differences can be noticed between Nepal and Indonesia. Core data sets, formats, maintenance, resolution, and uniformity have all been arranged considerably well. In Nepal, most participating agencies do not have data in digital format yet while in Indonesia most data is available digitally but not always following the same standard. With respect to people (Table I, Appendix), Nepal states that many GIS professionals are available in the country but also mentions the lack of specific SDI knowledge; Indonesia mentions a lack of GI and IT professionals. Bakosurtanal (Indonesia) conducts workshops to regional high rank officials to increase SDI awareness. Driving forces in both countries are similar; both countries mention ‘good governance’ as a driving force. A timely involvement of the users – for whom the whole infrastructure is being developed – will ensure that the NSDI will ultimately meet the expectations of the users and will be operational in a sustainable manner. In Nepal, users have not yet been involved in the initiative. In Indonesia, all possible user groups are involved in the initiative. Both Nepal and Indonesia have an access network for the access and retrieval of data (Table J, Appendix). However, the access network of Nepal is almost never operational and the response time of the network of Indonesia is (rather) slow. Indonesia has just secured a considerable grant from Japan for the improvement of the access network. With respect to policy (Table K, Appendix), formal mandates exist both in Nepal and in Indonesia. Little information is available on the legal and institutional arrangements in the Asian case study countries. Abdulharis et al. (2005) have described recommendations to speed up legal arrangements in Indonesia. In Indonesia, a presidential instruction has been issued concerning the involvement of ICT in the implementation of good governance: all government agencies have to implement ‘E-government’ services. The socio-political situation in both countries is rather unstable. Indonesia has developed a long-term, political NSDI vision (up to 2020); Nepal did not develop such vision yet. The international FGDC standard has been adopted in both Nepal and Indonesia (Table L, Appendix). However, the follow-up on standardisation has to be encouraged in both countries. In Indonesia, a document has been created for the agencies to develop and maintain their spatial databases in such way that data is of good quality, well maintained and can be nationally integrated. Awareness and willingness to share data is not always present in both countries. The comparison of the other component (Table M, Appendix) shows that the challenges in both countries are similar: the creation of regulations (legal and institutional arrangements), the encouragement of using standards and sustainability and commitment (of both human resources and funding). However, Indonesia with its considerable SDI history seems to progress faster and smoother than Nepal. Indonesia shows quite some initiative: a considerable Japanese grant is expected; which will boost the development further.

5.5 Selection of case study variables The analysis and comparison of the case study countries increases insight in the driving forces behind the NSDIs. The necessary, minimum conditions for countries to make progress and ensure continuity



over time are revealed. The appreciation of these issues assists in the identification of case study variables. For example, while comparing the Asian case study countries in section 5.4, it becomes clear that the availability of digital datasets* is important. If data is not available in digital format, they cannot be previewed and/or exchanged through the access network. Nepal has a limited access to digital data, Nepal is still working on digitalisation of data – updating and adding new data is not yet a priority. In Indonesia, a document has been created for the agencies to develop and maintain their spatial databases in such way that data is of good quality, well maintained and can be nationally integrated (‘interoperable’). In Indonesia, the existence of standardised metadata in almost all data producing institutes is inappropriate (Puntedewo and Nataprawira, 2004). From the history of Nepal, SDI education comes forward as an important asset for awareness creation and understanding the importance of sharing data. Those who studied abroad started lobbying for the NSDI. A lack of trained human resources is mentioned in Indonesia. Nepal has good GIS professionals, however, SDI knowledge appears to be somewhat lacking. A timely involvement of the users ensures that the NSDI will ultimately meet the expectations of the users and will be operational in a sustainable manner. In Nepal, users have not yet been involved in the initiative. In Indonesia, the user groups are involved in the initiative. Both Asian case study countries are struggling with their access network (not operational, slow, not reliable). Indonesia has developed a long-term NSDI vision; Nepal did not. Both countries do have a mandate to develop the NSDI. The follow-up on standardisation has to be encouraged in both countries. The creation of regulation (legal arrangements), the encouragement of using standards and sustainability and commitment (human resources and funding) are mentioned in both countries as challenges. In Nepal, the existence, communication and diffusion of GIS knowledge among end-users, technical professionals and decision-makers are crucial but not yet happening. Next to the in-depth assessment of Nepal and Indonesia, in Chapter 3 the NSDI developments in Asia have been reviewed. Several SDI experts have given indications for the criteria to select key variables to assess NSDIs. For example, looking at Asia: Rajabifard (2003) explains that next to the absence of standards, a lack of culture to share data exists in Asia which puts constrains on the transparency and the required knowledge for decision-making. The development of an SDI initiative is a long-term process, which requires a long-term vision and strategy. Another important conclusion is made by Rajabifard based on a review carried out in the Asia-Pacific region: the success of an SDI is not dependent on its legal or technical culture, but whether it provides an effective communication channel to all stakeholders and permits easy access to spatial data adequately, simply, quickly, securely and at low cost. Rajabifard states that there is little justification for NSDI development if the resources are not available to keep the SDI up-to-date. Funding and resources to secure the implementation of SDI is always an important issue. Kayastha et al. (2005) pose a critical question with respect to the institutional framework in Nepal: ‘Governance – how can the combination of spatial information resources from different agencies be facilitated?’ An approach based on standards, access and interoperability is suggested as the key mechanism for ensuring an integrated approach to achieve the proposed vision and to address spatial problems the government is facing. A suitable institutional framework for coordination is suggested and needed to provide the leadership, direction and priority setting to enable a focused approach for the vision of an SDI. A continued political, administrative and technological commitment is needed to develop an NSDI. It is not always easy to maintain policy continuity in a developing country (Chhatkuli, 2005).




From combining the above-described research in sections 5.4 and 5.5 (the comparison of the variables as can be found in Table H up to Table M and the literature review of Chapter 3), the case study variables of Nepal and Indonesia may be summarised as follows: Data component: Availability of digital data sets:

Nepal has a limited access to digital data. In Indonesia, most of the data (however not all) is available in digital format.

The quality of data: The data should be of good quality (complete, consistent – see definition in Appendix). If not, users might loose interest in sharing. In Indonesia, a document has been created for the agencies to develop and maintain their spatial databases in such way that data is of good quality, well maintained and can be nationally integrated (‘interoperable’).

Updating – adding of new data: Updating and adding of new data has no priority yet in Nepal, the main concern is the populating of the infrastructure itself.

Maintaining of the datasets: Data should be maintained; the SDI should be kept up-to-date (for improvement of quality, to always use the latest information etc.). In Nepal, maintenance has no priority. Not even all data is available digitally yet.

People component: SDI education:

Nepal mentioned that GIS training courses are available but that specific SDI education is lacking. People require training to implement the different SDI components. Indonesia has a lack of trained human resources; the access to SDI education is moderate.

Capacity building: The importance of capacity building activities is realised in Nepal; but activities did not happen yet. Indonesia conducts workshops to increase SDI awareness.

The willingness to share of data: A lack of culture to share data exists in Asia (including Nepal and Indonesia), which puts constrains on the transparency and the required knowledge for decision-making.

Human capital: Nepal mentioned a lack of professionals with SDI knowledge; Indonesia mentioned a lack of trained human resources with respect to GI and IT in general.

The involvement of the private sector, academic sector and user community: A timely involvement of the users – for whom the whole infrastructure is being developed – will ensure that the NSDI will ultimately meet the expectations of the users and will be operational in a sustainable matter. Chhatkuli explained that in Nepal the users are not yet involved in the initiative. In Indonesia, the users are involved.

Awareness: The awareness level is moderate in Nepal and Indonesia.


Both Nepal and Indonesia have established a discovery and delivery mechanism. However, they do not function well.

Reliability: The access network of Nepal is almost never reachable and therefore not reliable.

Performance: The response time of the network of Indonesia is (rather) slow.


Both Nepal and Indonesia have a directive of the government. However, according to Chhatkuli (2005), it is not always easy to maintain policy continuity in a developing country such as Nepal.

The presence of a long-term strategic vision: Nepal did not yet define a long-term vision. Indonesia has developed a strategy document up to 2020.



Availability of funding for NSDI development: Both Nepal and Indonesia have funding available for NSDI development. However, the funding is not likely to be stable (project funding).

The availability of a suitable institutional framework: The creation of institutional arrangements is mentioned as a challenge in both Asian case study countries.

The presence of policy documents describing legal arrangements: The creations of legal arrangements are mentioned as challenges in Nepal and Indonesia. To effectively share and exchange data, arrangements should be in place.

Socio-political stability: The socio-political stability of both Nepal and Indonesia is unstable.

E-government existence: In Indonesia, a presidential instruction has been issued concerning the involvement of ICT in the implementation of good governance: all government agencies have to implement ‘E-government’ services. Nepal did not start with E-government activities yet.

Standards component: Adoption of standards:

Although standards have been adopted in Nepal and Indonesia, the follow-up on standardisation has to be encouraged in both countries.

Availability of metadata: In Indonesia, the existence of standardised metadata in almost all data producing institutes is inappropriate (Puntedewo and Nataprawira, 2004). In Nepal, metadata is not hardly available.

Other component: The provision of an effective communication channel to all stakeholders:

The success of an SDI is not only dependent on its legal or technical culture; it should provide an effective communication channel to all stakeholders (Rajabifard, 2003). Nepal realises problems related to horizontal communication within the public sector. For example, the existence, communication and diffusion of GIS knowledge among end-users, technical professionals and decision-makers are crucial but not yet happening.

Initiatives connected to SDI (country’s activity): Bakosurtanal does expect to receive a Japanese grant; this grant assist to advance the NSDI development considerable. No information is available on the initiatives in Nepal.

Development approach: The other component shows the different NSDI approaches of Nepal and Indonesia (bottom-up versus top-down).

Table 4 presents the comparison of the Asian case study countries: Nepal and Indonesia. Table 4: Comparison case study variables between Nepal and Indonesia Asia SDI components


Nep

al

Indo

nesi

a

Data

Availability of digital datasets Good quality of datasets Updating – adding new data Maintaining datasets

Some

Acceptable No No

Some Good Yes Yes



People

Willingness to share data Human capital (‘resources’) Capacity building Involvement of users from all sectors SDI education

Awareness

Moderate

Not sufficient No No

Not available

Moderate

No

Not sufficient Yes Yes

Available Limited

Moderate

Access network

Availability of delivery mechanism


Yes

Not working well Bad Bad

Yes

Not working well Moderate Moderate

Policy


Long-term strategic vision Institutional arrangements in place Legal arrangements in place Socio-political stability E-government existence

Present

Yes Unstable

No No No

Unstable No

Present

Yes Unstable

Yes No No

Unstable Yes

Standards


Availability of metadata Interoperability

Yes

Not working well Partly

No

Yes

Not working well Partly

No

Other

Effective communication channels Initiatives connected to SDI (country’s

activity) Development approach

No

No information

Bottom-up

No information

Grant Japanese Government Top-down


Chapter 6: African case studies 45

6 African case studies

6.1 Introduction Chapter 6 strives to answer research question 3 by describing, analysing and comparing the NSDIs of the African case study countries (Nigeria and Ethiopia) by means of the identified variables as explained in Chapter 2. Likewise the Chapters 4 and 5, this Chapter attempts to identify criteria for selection of the key variables (research question 4).

6.2 NSDI in Nigeria In Nigeria, GI is acquired and stored in analogue form by various governmental agencies and the private sector. It is acquired and stored for own use and applications – with the difficulties of unnecessary overlaps and duplication, lack of accessibility, and varying standards and formats. Due to the increasing awareness of the use of GI for decision-making over the past years, linked with the expected availability of primary datasets from the Nigerian satellite, the country has realised the need to adopt policies for promoting greater awareness and public access to standard and coordinated geo-spatial production, management and dissemination by all sectoral institutions (Kufoniyi and Agbaje, 2005). In September 2002, the Ministry of Science and Technology requested a committee to draft a ‘Geospatial Information Policy’ to guide the implementation of the NSDI. The draft policy was circulated to stakeholders and submitted to the Ministry in September 2003. The initiative is coordinated by the National Space Research and Development Agency (NASRDA, www.nasrda.org). For implementation of the project, NASRDA appointed the Regional Centre for Training in Aerospace Surveys (RECTAS, www.rectas.org). Kufoniyi (2005), the General Director of RECTAS, states that currently a users’ requirements survey and analysis is being carried out alongside an awareness campaign to increase the stakeholders’ buy-in to the initiative. He mentions that the survey is expected to logically review existing stakeholders and their data and databases that will impact the development and implementation of the project. Nigeria is currently waiting for the policy to turn into a law (Kufoniyi, e-mail 2005).

6.2.1 Results of assessment by means of identified variables In the following sections, the results of the evaluation of the Nigerian NSDI are described by means of the identified variables. The complete assessment can be found in Table E (Appendix). Each of the five dynamic components of the SDI (data, people, access network, policy, standards) is described. The ‘other’ component, in which all identified variables that do not fit under the five SDI components are placed, is being described as well. Dr Jide Kufoniyi, the General Director of RECTAS, has checked the assessment table via e-mail (December 2005). In the following sections, unless otherwise indicated, the source of reference is Dr Kufoniyi.

6.2.2 Data In Nigeria, there is no coordinated production, management and dissemination of spatial datasets. There is no policy for data quality, access, sharing and exchange. In Nigeria, most of the GI is acquired and stored in analogue form. Currently the existing topographic analogue maps are being converted to digital format. The topographic maps will be one of the essential datasets for the Nigerian NSDI (Kufoniyi and Agbaje, 2005).



6.2.3 People

A working group on capacity building and awareness has been established to encourage: basic training, promotion of research, promotion of awareness, reviewing geo-informatics curricula, and promotion of institutional reforms. However, despite the developments that are taking place, availability of trained personnel is still a problem in the implementation of the NSDI project (Igbokwe and Ono, 2005). The driving forces behind the initiative can be summarised as follows: (1) need to adopt policies for promoting greater awareness and public access to standard and coordinated spatial data production, management and dissemination by all sectoral institutions, (2) successful launch of Nigeria’s Earth Observation Satellite (NigeriaSat-1), (3) New Partnership for Africa’s Development (NEPAD) – provision of relevant GI to facilitate national development and regional integration, (4) call of the United Nations Economic Commission for Africa (UNECA) to establish SDI, and (5) ICT – as it permits GI sharing and growth. Currently, a user requirement survey and analysis is being carried out alongside an awareness campaign to increase the stakeholders’ buy-in in the NSDI initiative. The survey will review the existing stakeholders and their data and databases that will impact the development and implementation of the NSDI. The survey will also capture the current data within the data producers, co-producers, users and other stakeholders. An assessment of the level of synchronisation between existing data and desired data will be carried out (Kufoniyi and Agbaje, 2005). According to Kufoniyi, a research programme to support the NSDI development is present in Nigeria. Research has been stimulated by the launch of the Nigerian satellite (NigeriaSat-1).

6.2.4 Access network With respect to the access network, the intention is to put in place a high-speed and high-bandwidth backbone carrier as the main gateway and master server and implement a database server at each node. At the moment, no access network is available. Telecommunication facilities are still problematic in Nigeria. The introduction of the wireless communication network is an asset, but the service still needs improvement. Closely connected is the electricity power needed to support all activities, which in some places simply does not exist (Igbokwe and Ono, 2005).

6.2.5 Policies An NSDI committee has been established to guide the establishment and implementation of the NSDI in line with the GI policy – members of professional organisations are part of the committee. Unfortunately, the council has not yet ratified the policy (Igbokwe and Ono, 2005). Six working groups have been established to work on issues such as datasets, standards, clearinghouse and metadata, capacity building and awareness, legal issues and sustainability and funding. The GI policy addresses means of funding of all NSDI components. The fund shall accrue from: minimum 2.5% of annual budget; 10% of national ecological fund; 0.5% profit-over-tax of private organisations; and all income generated from access charges and data sales; and international funding and grants (Kufoniyi and Agbaje, 2005). Igbokwe and Ono (2005) also mention that UNECA is committing technical manpower and funds to help African Countries that are embarking on NSDI implementation. According to Kufoniyi no grants have been given to Nigeria so far. The socio-political situation of Nigeria is unstable.



6.2.6 Standards A workgroup on standards has been established. The ISO standard has been adopted in Nigeria.

6.2.7 Other Nigeria is mainly undertaking a ‘top-down approach’ for NSDI establishment – a National Policy drives the initiative. According to Kufoniyi, the main challenges for the Nigerian NSDI are: funding, passage of policy into law, and capacity building.

6.3 NSDI in Ethiopia On 29 October 2002, the Ethiopian Mapping Authority (EMA) organised a one-day NSDI workshop in collaboration with the United Nations Economic Commission for Africa (UNECA). EMA invited approximately 50 ministries and government organisations that have a direct connection with spatial data (producers or users). The following resolutions were passed as a conclusion of the workshop: The Ethiopian Mapping Authority (EMA), based on the existing capacity, experience and legal

mandate is to take responsibility of facilitating development of NSDI at the national level as a provisional project.

The national workshop is to be held within 6 months time in such a way that all stakeholders are to be aware in the development of NSDI.

All stakeholders, funding agencies and spatial data producers and processors are to play an important role in NSDI developing funding and capacity building.

Policy issues such as data production, processing, standardisation, and dissemination have to developed without duplication and affecting the national economy.

Also in October 2002, UNECA with EMA and the Global Spatial Data Infrastructure (GSDI) Secretariat conducted a metadata/clearinghouse/web-mapping workshop. Participants included information management specialists from UNECA, EMA, Ministry of Water Resources, and the Ministry of Science and Technology. This work has contributed to the Ethiopian Natural Resources and Environmental Meta-Database (ENRAEMED) (http://geoinfo.uneca.org/geoinfo/ethiopia/index.html). This metadata base is operated by a partnership of major Ethiopian institutions concerned with the generation, storage and dissemination of data related to natural resources and the environment.

6.3.1 Results of assessment by means of identified variables On January 27th, 2006, an interview with Mr Alemu Mekonnin, Head of the GIS Department of EMA, took place at ITC. Mr Mekonnin is currently pursuing an MSc in the field of Geo-Information Management there. Although regular meetings of the NSDI steering committee are taking place in Ethiopia, no progress has been made. According to Mr Mekonnin, the concept of an NSDI was not well understood when the initiative started in 2002 (section 6.3). It was believed that an NSDI was just a ‘tool’ to prevent data duplication – people were not aware of and did not understand the other SDI components. In the following sections, the interview with Mr Mekonnin is summarised. The assessment can be found in Table F (Appendix). Although all possible channels in Ethiopia have been approached (EMA, UNECA, contacts WUR and contacts ITC), unfortunately little information on the Ethiopian NSDI has been received.



6.3.2 Data Data in Ethiopia is mainly available in analogue format. Ethiopia is working on the conversion to the digital format.

6.3.3 People The SDI concept is not well understood in Ethiopia. The awareness level is very low.

6.3.4 Access network There is no access network available. However, a metadata software tool called ENRAEMED has been developed (see also section 6.3.6).

6.3.5 Policy Ethiopia does not have a formal mandate to work on the NSDI. No legal, institutional framework etc. is available. The socio-political situation in Ethiopia is very unstable.

6.3.6 Standards Awareness on the importance of meta-data standards has been created through the ENRAEMED initiative (http://geoinfo.uneca.org/geoinfo/ethiopia/index.html); a metadata software tool. However, Mr Mekonnin mentions that filling out the metadata forms, as described in ENRAEMED, is a lot of work. It might very well be that not all stakeholders fill out the necessary forms correctly or completely. ENRAEMED makes use of ISO and FGDC standards.

6.3.7 Other Looking at the evaluation framework of Kok and Van Loenen (2004) (section 2.2.1), Ethiopia’s NSDI initiative is in the stand-alone stage: SDI has no priority at all. During the interview with Mr Mekonnin of EMA, it was mentioned that a report to obtain funding for the establishment of the NSDI has been presented by EMA to the Ministry of Finances in 2005. The Ministry administers foreign donor money, which is intended for capacity building activities. Interest in E-government is present in Ethiopia; the proposal of EMA focussed on the NSDI establishment (mainly on the conversion from analogue to digital data) and had a relation to E-government services. Although the Ministry gave the ‘green light’ to EMA, the project never started due to the unstable political situation in Ethiopia.

6.4 Comparison The comparison of the Nigerian and the Ethiopian NSDI can be found in the tables Table H up to Table M (Appendix). To compare the NSDIs of the African case study countries Nigeria and Ethiopia is a challenging task. On Ethiopia not much information is available. Both countries are in different phases of NSDI development. Nigeria is working hard on the digitalisation of data and policy components of the NSDI, while Ethiopia seems to have established no progress at all since the initiation in 2002. NSDI has no priority in Ethiopia; the concepts are not well understood. Nevertheless, while comparing the case study countries, some conclusions can be drawn. For example, looking at the data component (Table H, Appendix), both countries hardly have digital data available and are working hard on the conversion. Nigeria claims that available data is mostly outdated and requires updating. In Nigeria, a survey is being carried out with the idea to capture the current data within the data producers, co-producers, users and other stakeholders. An assessment of the



level of synchronisation between existing data and desired data is also being carried out (Kufoniyi and Agbaje, 2005). With respect to people (Table I, Appendix), properly trained staff is a problem in Nigeria. Research is stimulated – especially since the launch of the NigeriaSat-1 satellite. In Nigeria, awareness of the benefits of NSDI development is present. With respect to Ethiopia, one might perhaps conclude that UNECA and GSDI enforced the development of the NSDI in 2002. NSDI stakeholders were not yet ready at that time. As mentioned by Mr Mekonnin of EMA, NSDI principles were not well understood. NSDI was seen as a ‘tool to prevent data duplication’. Proper education to understand the benefits of NSDIs was not given to the Ethiopians. Both Nigeria and Ethiopia do not have access networks and no data/metadata to present (Table J, Appendix) although, in Ethiopia, metadata was created during the ENRAEMED initiative. With respect to policy (Table K, Appendix), Nigeria and Ethiopia do not have formal mandates to initiate NSDIs, although Nigeria has presented a policy document to the government and is expecting the policy to turn into law. In both countries, the socio-political situation is unstable. Nigeria has adopted the international ISO standard, while Ethiopia has adopted a metadata standard based on ISO and FGDC during the ENRAEMED initiative (Table L, Appendix). The comparison of the other component (Table M, Appendix) shows that Nigeria and Ethiopia both have top-down approaches but are in different phases of establishment. In Ethiopia, the NSDI development has no priority at all.

6.5 Selection of case study variables The analysis and comparison of the case study countries increases insight in the driving forces behind the NSDIs. The necessary, minimum conditions for countries to make progress and ensure continuity over time are revealed. The appreciation of these issues assists in the identification of case study variables. For example, it becomes directly clear that an NSDI cannot be initiated without awareness* and understanding while looking at and comparing Nigeria and Ethiopia. The principles of an SDI are not well understood in Ethiopia. SDI education is most likely an important asset for awareness creation and understanding the importance of sharing data. A lack of trained human resources is now noticeable in both countries. Capacity building, for example through short courses and workshops, could assist to increase the understanding of NSDI principles and benefits. From section 6.4, it becomes clear that the availability of digital datasets is very important. Both African case study countries are working on the digitalisation of data. Nigeria mentions that most data is outdated and needs updating. Data should be of good quality (complete, consistent). Nigeria has a detailed policy document in place, but without having the data in place, NSDI progress will be limited. Access networks are not yet available. Nigeria has the intention to build an access network in the near future but also has to work on the digital data availability. A national policy document drives the initiative in Nigeria. According to Kufoniyi (e-mail, December 2005), the main challenge for Nigeria will be the turning of the policy into law. Political support will give the NSDI initiative a push forwards. Next to the in-depth assessments of Nigeria and Ethiopia, in Chapter 3 the NSDI developments in Africa have been reviewed. Several SDI experts have given indications for the criteria to select key variables to assess NSDIs. For example, looking at Africa: During a conference on ‘Spatial Information for Sustainable Development’ in Kenya in 2001, it was concluded that the use of spatial information to support sustainable development would only be achieved if solutions start with realistic objectives and grow incrementally through political and market




needs. According to Lance (2003), the main problems facing SDI development in Africa are: political support, legal status (or enabling legislation) to support efforts, and leadership. Kufoniyi (2004) states that African countries are realising the need to establish SDIs – the implementation of SDI in Africa is gradually but surely progressing. The need to adopt policies for promoting awareness and public access to standard and coordinated spatial data production, management and dissemination by all sectors, including the establishment of a clearinghouse at various levels in the countries with linkages with the private sector, is slowly realised. From combining the above-described research in sections 6.4 and 6.5 (comparison variables as can be found in Table H up to Table M and literature review of Chapter 3), the case study variables of Nigeria and Ethiopia may be summarised as follows: Data component: Availability of digital data sets:

In both African case study countries, hardly any digital data is available. The quality of datasets:

Nigeria mentions that most data is outdated and needs updating. Data should be of good quality (complete, consistent – see definition in Appendix).

Updating – adding of new data: Nigeria mentions that data is outdated and requires updating. New data has to be developed.

People component: SDI education:

As can be seen in Ethiopia, an NSDI initiative cannot be started without understanding the principles. Nigeria is working on its SDI education. Capacity building initiatives are very important. Nigeria has a capacity building working group in place. However, despite the developments taking place in Nigeria, availability of trained personnel is still a problem in the implementation of the NSDI project (Igbokwe and Ono, 2005).

Awareness: Ethiopia’s NSDI initiative is in the stand-alone stage: SDI has no priority at all. The SDI concepts and principles are not (well) understood. Without understanding the benefits, the initiative will not make any progress.


In Nigeria and Ethiopia, no access network is available yet. However, initiatives are set. Hardly any digital data (and/or metadata) is available to present through an access network.


In Nigeria a policy document is ready. With the support of the government, the NSDI initiative would get a serious push forward. In Ethiopia, no formal mandate of the government exists to develop the NSDI.

Availability of funding for NSDI development: Nigeria already described regulations with respect to future funding. The political situation in Ethiopia is very unstable at the moment. As explained by Mr Mekonnin (interview January 2006) funding for the NSDI initiative is not available.

The presence of a long-term strategic vision: Long-term visions have not yet been thought of in Nigeria and Ethiopia.

The presence of a policy document describing legal arrangements: Nigeria has put ideas on paper in a policy document. Ethiopia has nothing on paper yet.

The availability of a suitable institutional framework: Nigeria has put ideas on paper in the policy document. Ethiopia has nothing on paper yet.

The existence of a leader: Leadership is required to develop an SDI. EMA is the leader of the initiative in Ethiopia. However, the NSDI principles might not be well understood by EMA. Leadership is better defined in Nigeria (NASRDA/RECTAS).

Socio-political stability: Both in Nigeria and Ethiopia the socio-political situation is unstable.



Standard component: Adoption of standards:

In Nigeria and Ethiopia, metadata standards are based on ISO and FGDC standards. Mekonnin (interview, January 2006) mentioned that awareness on the importance of standards has been created during the ENRAEMED initiative but that institutions do not fill out the metadata forms.

Other component: Challenges:

According to Kufoniyi, challenges in Nigeria are related to funding, the passage of the policy document into law and capacity building activities. In Ethiopia, awareness and understanding have to be created first.

SDI’s maturity: The comparison of the other component shows that Nigeria and Ethiopia are in different phases of establishment (exchange stage versus stand-alone stage). In Ethiopia, the NSDI development has no priority at all.

Table 5 presents the comparison of the African case study countries: Nigeria and Ethiopia. Table 5: Comparison case study variables between Nigeria and Ethiopia AFRICA SDI components


Nig

eria

Ethi

opia

Data

Availability of digital datasets Good quality of datasets

Updating – adding new data

Some ↔ none

Analogue: acceptable

No

Some ↔ none

--

No

People

Human capital (‘resources’) Capacity building SDI education Awareness of SDI concepts

Not sufficient

No Working on Moderate

Not sufficient

No Not available

Bad

Access network Availability of delivery mechanism

No

No

Policy


Long-term strategic vision Institutional arrangements in place

Legal arrangements in place

Existence of leadership

Socio-political stability

Not present

No Described

No No

Described No

Described Yes

Unstable

Not present

No

No No

No

Yes

But without understanding

Unstable

Standards


Yes

Yes

Not correctly or completely



Other

Funding Policy → law Capacity building SDI’s maturity

Challenge Challenge Challenge

Exchange stage

Stand-alone stage


Chapter 7: Selection of key variables to assess NSDIs in developing countries 53

7 Selection of key variables to assess NSDIs in developing countries

7.1 Introduction Chapters 4, 5, and 6 described the NSDIs of Colombia, Cuba, Nepal, Indonesia, Nigeria and Ethiopia. Feasible and case study variables have been detected (see Figure 2). This Chapter presents the feasible variables. Next, the case study variables as found in Chapters 4, 5 and 6 are summarised in one table. The opinion of SDI experts was solicited regarding the feasible variables in two steps: (1) during the SDI expert workshop (Wageningen, January 2006) and (2) by means of a questionnaire. The variables selected by the SDI experts are listed in this Chapter as well. Finally, this Chapter presents the main result of the research, a common set of measurable key variables that can be utilised to assess NSDIs in developing countries.

7.2 Feasible variables In Chapters 4, 5 and 6, for each of the six case study countries, all listed variables of Table 2 were carefully checked and described based on literature review and interviewing the national SDI coordinators via e-mail. To come to the feasible variables, those variables that are not measurable were removed from the initial list of 94 identified variables. The set of rules as explained in section 2.3.2 was applied to remove variables from the initial list of identified variables. The following table presents the feasible variables. Table 6: Feasible variables

SDI COMPONENTS Data component Data format Maintenance Quality Updating – adding of new data Language (data format etc.) Availability digital data sets People component Driving forces (data acquisition, SDI) Language Number and type of suppliers Number and type of users Capacity building (information dissemination, short courses, workshops, research & facilitation) Education (type, availability) Research (to support NSDI) User satisfaction (SDI & approach) User involvement Private /commercial participation Awareness (spatial data, SDI concept) Human capital (human resources) SDI culture Willingness to share data Access network Delivery mechanism (availability, search and procedures) Response time

FEA

SIB

LE V

AR

IAB

LES

Nr. of visitors



Number of language used Preview possibility E-business Performance (usefulness) Reliability Policy SDI directive (existence) Funding Institutional arrangements (for suppliers/users/value-adders) Legal arrangement (for suppliers/users/value-adders) Leadership Vision (political, long-term) Partnership arrangements Public/private partnerships E-government existence Socio-political stability Standards Data transfer Metadata (availability) Services Interoperability Other Development approach (bottom-up, top-down) Decentralization / centralization Communication channels SDI's complexity SDI's maturity SDI's impact visibility Initiatives connected to SDI (country’s activity)

The list of feasible variables is still extensive and therefore not operational (49 feasible variables). Feasible variables can be found in all SDI components.

7.3 Case study variables After checking and describing the variables of the six case study countries, from the initial list of identified variables, a reduced list of feasible could be developed. The literature review of Chapter 3 identified criteria for the selection of important assessment variables. Thoroughly analysing and comparing the identified variables of the case study countries with each other revealed case study variables. As explained in section 2.4, for the selection of the relevant case study variables, the UNDP rule to look at the key changes has been applied. To ease the search for key changes of the feasible variables within the different SDI components of the six case study countries, the possible answers to the variables were re-classified (see Table G, Appendix, for the re-classification of all answers). Following from the critical analysis and comparison (‘the search for key changes’ by means of the comparison tables), a set of common case study variables has been derived.



In the following table, the case study variables as earlier defined in Table 3, Table 4 and Table 5 are presented together in one Table. Table 7: Case study variables Case study countries

Latin America Asia Africa

SDI

CO

MPO

NEN

TS


Col

ombi

a

Cub

a

Nep

al

Indo

nesi

a

Nig

eria

Ethi

opia

Data

Availability of digital data

sets Good quality of data

Updating – adding new

data Maintaining data sets

Consider

able

Good

Yes

No

Some

Accept able

No

No

Some

Accept able

No

Yes

Some

Good

Yes

Yes

Some

↔ None

--

Yes

No

Some ↔ None

--

--

No

People

Willingness to share

Human capital

(‘resources’) Capacity building Research/development

capacity SDI education Involvement users all

sectors User satisfaction Awareness SDI concepts

--

Sufficient

Yes Yes

Available No

Moderate

Moderate

--

Not sufficient

Yes Yes No

capacity

Available No

Not good

Moderate

Moderate

Not sufficient

No No

Not available

No

Not good

Moderate

No

Not sufficient

Yes No

Not available

Yes

--

Moderate

No

Not sufficient

No Yes

Not available

No

--

Moderate

No

Not sufficient

-- --

-- --

Not good

Not good

Access network

Availability delivery

mechanism Reliability

Performance

Yes

Reason able

Reason

able

Yes

Reason able

Reason

able

Yes Not

working well Bad

Bad

Yes Not

working well

Moderate

Moderate

No

--

--

No

--

--



Policy

Existence of directive

Funding Long-term strategic vision Institutional arrangements

in place Legal arrangements in

place Existence of leadership

Socio-political stability E-government existence

Not

present

Yes No No

No

Not present

Unstable

Yes

Present

Yes No --

--

Present

Stable Yes

Present

Yes No No

No

Present

Unstable No

Present

Yes Yes No

No

Present

Unstable Yes

Not

present

No Yes No

No

Present

Unstable Yes

Not

present

No No No

No

Present

Unstable --

Standards

Adoption of standards Availability of metadata Interoperability

Yes Yes No

Yes Partly Yes

Yes Partly

No

Yes Partly

No

Yes No No

Yes Partly

No

Other

Effective communication

channels SDI’s maturity

Initiatives connected to

SDI (country’s activity)

Accept able Ex

change

GIS for land use planning

Accept able Ex

change

National Society

Inf. Prog.

Not good

Ex change

--

--

Ex change

Grant Japan Gov.

--

Ex change

(Active part. in conf.)

--

Stand alone

--

The case study variables of the six case study countries are quite similar. However, slight differences can be noticed in some of the components. To give some examples, the African case study countries do not have established access networks yet. Therefore, variables such as ‘reliability’ and ‘performance’ do not have a value yet. Looking at the people component, only Colombia claims to have sufficient SDI experts. With respect to the standards component, a metadata standard has been adopted in almost all countries; however this variable also requires encouragement in almost all case study countries. Case study variables are noticeable in all SDI components (data, people, access network, policy, standards, and ‘other’). However, as can be noticed from the above table, most case study variables can be found in the ‘people’ and ‘policy’ components. Issues related to people and policies appear to have a significant influence and impact on NSDI progress over time.

7.4 Expert variables On 19 – 20 January 2006, a workshop entitled ‘Exploring Spatial Data Infrastructures’ was organised in Wageningen. Discussions were held around a number of subjects, under which topics of interest for this research, such as: ‘Is it possible to develop an assessment framework for SDI?’ and ‘What are the criteria for choosing variables and indicators for assessment?’ On the second day of the workshop, the criteria for selection of assessment variables were discussed. This question appeared to be hard to answer because criteria are likely to be country-specific and may depend on the level of maturity of the NSDI (Kok and Van Loenen, 2004, section 2.2.1, page 8). This research looks at the level of maturity. The experts did agree that the criteria should be directly linked to the different SDI components (see Figure 4, page 17) and that the variables should be measurable in some way. This research follows the SDI components and searches for measurable variables (section 2.3). In order to validate the resulting list of case study variables, twenty-six SDI experts were asked to give their opinion on the key variables for assessment of NSDIs in developing countries in March 2006.



Most of the experts who attended the workshop in Wageningen were asked to give their opinion on the variables; also the national coordinators earlier contacted were again consulted. For an overview of the SDI experts consulted, please see Table N (Appendix). The SDI experts received the reduced list of 49 feasible variables (as explained in section 2.3). They were asked to select the 10 most important variables for assessment of NSDIs in developing countries out of the list of feasible variables. Twenty-two experts responded to the question (a response of 85%). Table O (Appendix) presents the individual selections of the experts. The following graph presents the selection of the SDI experts:

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Looking at the graph, three groups of expert variables can be noticed: (1) the group with the most frequently selected variables (selected between 15 and 7 times), (2) the group with an average selection (selected between 6 and 4 times), and (3) the group with the variables selected only 3, 2 or 1 time(s). The boundary limits for each of the three groups were selected by carefully looking at the graph and the boundary variables. The variables of the first group (most often selected variables) may be qualified as the most important for assessment of NSDIs in developing countries. The following table presents the most often selected variables.



Table 8: Key variables as selected by SDI experts Variables selected by experts Number of times

selected Data component Availability of digital data 15 People component Capacity building 13 Willingness to share 10 Human capital 9 Awareness 8 Access network component Delivery mechanism (availability, search and procedures) 8 Policy component Funding 14 Leadership 11 Vision 10 Institutional arrangements 9 Socio-political stability 7 Standards component Interoperability 9 Metadata (availability) 8 Other component Initiatives connected to SDI 8 The experts selected variables out of all the SDI components. As can be noticed from Figure 6, most of the feasible variables have been selected at least once. Masser (2005) concluded that the main obstacles for NSDI establishment and development are mostly institutional rather than technical in nature. The access network component does come forward as an expert variable (technical); however, also the policy component (all feasible variables) and the people component were again selected very frequently. Once more, issues related to policies and people appear to have a significant influence and impact on NSDI progress over time. Only 9 variables out of the list of feasible variables (Table 6) were not selected at all. The following table presents the variables that have not been selected. Table 9: Variables not selected by SDI experts Variables not selected by experts Data component Language People component Language Access network component Response time Nr. of visitors Nr. of languages used Preview possibility E-business Other component SDI’s complexity SDI’s maturity The language variable in the data and in the people component has not been selected. To work with different languages (e.g. English next to the respective language of the country), might be of less importance in developing countries. Some of the developing countries are still having difficulties to actually develop a good functioning access network. In Africa, for example, telecommunication facilities are still problematic. One might



assume that, for this reason, variables with respect to the access network have not all been selected. However, it does not mean that the non-selected variables are not important. As also commented by some of the SDI experts, variables might be linked to each other. Two variables out of the other component were not selected. It might be that the variables in this component were more difficult to understand without further explanation of their meaning.

7.5 Key variables While comparing the case study variables (section 7.3, Table 7) with the expert variables (section 7.4, Table 8), the highest category of variables as selected by the experts (14 variables) all fit within the case study variables (29 variables). The 14 expert variables as presented in Table 8 may therefore be qualified as the key variables for assessment of NSDIs in developing countries. Table 10 presents the final selection of the key variables for assessment of NSDIs in developing countries. Table 10: Key variables for the assessment of NSDIs in developing countries Case study variables Expert variables Key variables Data component Data component Data component Availability of digital data Availability of digital data 1. Availability of digital data Good quality of data Updating – adding new data Maintaining datasets

People component People component People component Willingness to share Willingness to share 2. Willingness to share Human capital (‘resources’) Human capital (‘resources’) 3. Human capital (‘resources’) Capacity building Capacity building 4. Capacity building Research/development capacity SDI education Involvement users all sectors User satisfaction

Awareness SDI concepts Awareness SDI concepts 5. Awareness SDI concepts Access network component Access network component Access network component Delivery mechanism (availability)

Delivery mechanism (availability)

6. Delivery mechanism (availability)


Policy component Policy component Policy component Existence directive Funding Funding 7. Funding Long-term strategic vision Long term strategic vision 8. Long term strategic vision Institutional arrangements in place

Institutional arrangements in place

9. Institutional arrangements in place

Legal arrangements in place Existence of leadership Existence of leadership 10. Existence of leadership E-government existence Socio-political stability Socio-political stability 11. Socio-political stability Standards component Standards component Standards component Adoption of standards Availability of metadata Availability of metadata 12. Availability of metadata Interoperability Interoperability 13. Interoperability Other component Other component Other component Effective communication channels SDI’s maturity

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7.6 Specific for developing countries Now that 14 key variables for assessment of NSDIs in developing countries have been selected, whether or not the key variables for assessment of NSDIs in developing countries are different from those of developed countries are checked and described in following sections.

7.6.1 Availability of digital data From the case study country research, the conclusion could be drawn that all six countries have difficulties with the availability of digital data. Especially the African case study countries are struggling with the availability of digital data; both case study countries (Nigeria and Ethiopia) are undergoing major efforts to convert their analogue data to digital data. One may assume that the ’availability of digital data’ variable specifically counts for developing countries. Developed countries (mostly) have their data available in digital format.

7.6.2 Capacity building As earlier quoted (Masser (2005), in Chapter 1), the need for capacity building activities to be developed in parallel to the processes of NSDI implementation is often underestimated. This is particularly important in developing countries where the implementation of NSDI initiatives is often dependent on a limited number of staff with the necessary geographic information management skills. With the exception of Nepal and Nigeria (on Ethiopia no information is available), the case study countries are carrying out capacity building activities (such as short courses, workshops). Nevertheless, a lack of human capital (resources) is mentioned by almost all national coordinators (with exception of Colombia). Although developed countries also require capacity building activities, the GSDI Cookbook (2004) rightly states that capacity building activities can be used to foster the implementation of an SDI. One may assume that the ‘capacity building’ variable specifically counts for developing countries.

7.6.3 Willingness to share As previously explained in Chapter 3, Rajabifard (2003) describes a lack of culture to share data in Asia. However, the challenges related to the willingness to share spatial data, can be noticed in both developed and developing countries.

7.6.4 Human capital With the exception of Colombia, all national coordinators have mentioned the lack of well-trained human resources. The ‘human capital’ variable is specifically valid for developing countries. One may assume that in developed countries sufficient well-trained human resources are available.

7.6.5 Awareness Understanding and being aware of the concepts and benefits of an (N)SDI is very important before and during implementation and establishment. For example, looking at the NSDI initiative in Ethiopia: the concepts were not well understood when the initiative started in 2002. It was believed that an NSDI was just a ‘tool’ to prevent data duplication – people were not aware of and did not understand the other SDI components and principles. The awareness level needs improvement in all case study countries. One may assume that the ‘awareness’ variable is very important in developing countries.



7.6.6 Delivery mechanism As mentioned previously during this research, the access network is one of the key features of an NSDI (Crompvoets, 2006). This variable is important in both developed and developing countries. The discovery and delivery mechanism in the case study countries all require improvement. Through the portals of Colombia and Cuba, data of only one provider can be retrieved (‘product portals’). The portal of Nepal is almost never operational and the portal of Indonesia is rather slow. Nigeria and Ethiopia do not have established discovery and delivery mechanisms yet.

7.6.7 Funding To secure funding is a relevant issue not only in developing countries; NSDIs require constant accomplishments and financial input over a long period of time. However, chances for obtaining funding for SDI are limited in developing countries. Although many countries have NSDI initiatives, it is not prominent on the political agenda due to other critical issues. The stability of the variable ‘funding’ is particularly important in developing countries. Mostly, stability cannot be guaranteed.

7.6.8 Leadership For example in Africa, one of the main problems facing SDI development is leadership. While the national mapping agencies are the key contributors to SDI development, other entities have the political influence and funding that drives the initiatives. In Colombia, NSDI leadership is not well defined, which slows down the progress. In Ethiopia, SDI principles might not be well understood by the leader. The ‘leadership’ variable seems to be very important in developing countries.

7.6.9 Vision In the dynamic NSDI environment, a long-term vision is considered as very relevant. From the case study countries, only Indonesia has developed a long-term, political vision towards (future) NSDI development. The ‘vision’ variable is considered as very important for developing countries.

7.6.10 Institutional arrangements Almost all national coordinators have mentioned the institutional arrangements as challenges. This variable is challenging and important in both developed and developing countries.

7.6.11 Socio-political stability A continued political, administrative and technological commitment is needed to develop an NSDI. It is not always easy to maintain policy continuity in a developing country. This variable seems particularly important in these countries. Almost all national coordinators mention the social-political instability.

7.6.12 Interoperability The ability to successfully understand and share various data, software, and hardware across a broad spectrum of organisations and users is relevant for any SDI. Therefore, this variable is not specifically important for developing countries – it is a challenge for all countries.



7.6.13 Metadata (availability) One of the challenges faced by users of data is the lack of information about information sources that might be relevant to their needs. Appropriate metadata services can help them to find out this information. Although this variable is not specific for developing countries, the use of metadata services requires encouragement in almost all case study countries.

7.6.14 Initiatives connected to SDI (country’s activity) If countries are active (for example if activities to undertake actions to increase understanding are organised) a greater willingness to participate in the initiative might be achieved. This variable is specifically important in developing countries. For example, as explained in Chapters 4, 5 and 6, some of the countries already initiated considerable SDI activities (such as the Japanese grant for Indonesia).

7.7 Results

This research explored how to select a common set of measurable key variables that can be utilised to assess NSDIs, with a focus on developing countries. The main result of this research is: A common set of measurable key variables for assessment of NSDIs in developing countries:

Fourteen measurable key variables have been selected by following the research steps as presented in Figure 2. These variables are: (1) availability of digital data, (2) capacity building, (3) willingness to share, (4) human capital, (5) SDI awareness, (6) delivery mechanism, (7) funding, (8) leadership, (9) vision, (10) institutional arrangements, (11) socio-political stability, (12) interoperability, (13) metadata (availability), and (14) initiatives connected to SDI in the respective country. As presented in previous section (7.6), almost all of the variables are specifically important for developing countries (with exception of (3), (6), (10), (13), and (14)). It is suggested that NSDI coordinators in developing countries take the critical key variables for assessment into consideration during initiation and development. Looking critically and carefully at the selected key variables may enrich and enhance the establishment and development of NSDIs in developing countries. In addition, the following results were obtained as well: A list of variables to assess NSDIs:

A considerable number of scientific articles describing already existing NSDI assessment frameworks have been reviewed critically during this research. Based on the review, a table with a large number of variables (94) to assess NSDIs has been developed (Table 2, page 11) A list of measurable feasible variables for the assessment of NSDIs in developing countries:

Based on the case study country research (literature, Internet, interviewing national coordinators), the list of initially identified variables has been checked carefully. This resulted in a reduced list of 49 feasible variables to assess NSDIs in developing countries (Table 6, page 53). A list of common case study variables to assess NSDIs in developing countries:

The analysis and comparison of the different SDI components of the six case study countries and the identification of criteria for the selection of case study variables, assisted to reduce the list of feasible variables to a common set case study variables (Table 7, page 55). A list of expert variables:

A selected group of SDI experts has been consulted to validate the resulting list of case study variables. SDI experts have been asked to give their opinion on the ten most important assessment



variables for developing countries out of the list of feasible variables. The opinions of the experts have been compared with each other and ranked. A set of most frequently selected expert variables has subsequently been selected (Table 8, page 58). Based on the comparison and matching of the case study variables with the expert variables, a common set of measurable key variables could be selected, which is the main result of this research. Better understanding of the NSDIs in Latin America, Asia and Africa:

The NSDI developments in the three continents under investigation (Latin America, Asia and Africa) have been reviewed; which resulted in a better insight in the differences and similarities between the continents. Checking and reviewing the NSDIs in the continents based on literature review also gave an indication of the criteria for the selection of those variables that are most important for assessment. Better understanding of NSDIs in case study countries:

With the assistance of the assessment variables, the NSDIs of the case study countries have been critically investigated. A better understanding of the NSDIs in Colombia, Cuba, Nepal, Indonesia, Nigeria and Ethiopia has been achieved. The differences and similarities between the initiatives and the driving forces behind the initiatives have become apparent. The understanding of these issues can assist in the improvement of the implementation of NSDIs.

Chapter 8: Conclusions and recommendations 65

8 Conclusions and recommendations

8.1 Conclusions The main research question of the thesis was formulated as follows: ‘How to select a common set of measurable key variables that can be utilised to assess NSDIs in developing countries?’ Based on a number of research steps as presented in the flow-chart of Figure 2 (page 7), and described in this thesis, 14 variables could finally be selected as key variables: (1) availability of digital data, (2) capacity building, (3) willingness to share, (4) human capital, (5) SDI awareness, (6) delivery mechanism, (7) funding, (8) leadership, (9) vision, (10) institutional arrangements, (11) socio-political stability, (12) interoperability, (13) metadata (availability), and (14) initiatives connected to SDI in the respective country. To answer the main research question, a number of sub-questions had to be answered (Chapter 1, section 1.4) 1. How is an NSDI defined? The definition of an NSDI, used throughout this research, was presented in Chapter 3, section 3.2, and is: ‘the national SDI is an initiative intended to create an enabling environment for a wide variety of users to access and retrieve complete and consistent datasets with national coverage in an easy and secure way – the national SDI forms a fundamental framework to exchange data across many agencies and disciplines (Rajabifard et al., 2003)’. 2. What are the variables (and criteria) to assess NSDIs – based on existing assessment procedures

and frameworks? The variables were presented in Chapter 2, section 2.2 (Table 2, page 11). The initial list of 94 identified variables formed the basis and starting point of this MSc research. 3. How to assess and compare the NSDIs of the case study countries based on the listed variables? The method of assessment and comparison was explained in detail in Chapter 2 (Research methodology). In summary, by critically reviewing existing assessment frameworks, a considerable number of initial variables that can be utilised to assess NSDIs were identified (94 identified variables). The specific, measurable, attainable and trackable variables were filtered out of the list of identified variables to progress to the feasible variables (49 feasible variables). Following on from the review of the NSDI initiatives in the three continents and the critical analysis and comparison of the case study countries, a set of common and relevant case study variables was derived (29 case study variables). Subsequently, a selected group of SDI experts was consulted to give their opinion on the most important variables for assessment of NSDIs in developing countries. These expert variables were compared and matched with the earlier defined case study variables. Resulting from the comparison, a set of 14 key variables for NSDI assessment in developing countries was selected. The actual assessment and comparison took place in Chapters 4, 5, and 6. All the assessment and comparison tables can be found in the Appendix. 4. How to decide on the criteria for selection of the key variables in order to assess NSDIs in

developing countries? Criteria for selection of key variables were based on the literature review as presented in Chapter 3 and on the analysis and comparison of the variables of the different case study countries (sections 4.5, 5.5, and 6.5).


As previously mentioned in Chapter 1, the purpose of determining key variables is to support effectiveness throughout the processes of planning, implementation, monitoring, reporting and evaluation – that is, throughout the full spectrum of results-based management (UNDP, 2006). Looking at the selected set of key variables one may conclude that the selected ones are crucial for the enhancement and innovation of NSDIs in developing countries in a more strategic and operational way. It is therefore suggested that NSDI coordinators in developing countries take the key variables for assessment into consideration. By doing so, their NSDIs may be enhanced.

8.2 Recommendations Considering the dynamic environment of an NSDI, evaluation of NSDI-programmes at different moments in time is considered as very important. Due to the limited time frame of this research, during the case study country research, only one moment in time has been taken into consideration (December 2005 or January 2006). During this research, the number of initially identified variables has been reduced based on case study country research. It is thinkable that if different countries had been selected, another outcome with respect to the key variables possibly could have been achieved. Other variables could have been removed from the initial list, so the final outcome could have been different. For validation purposes, experts were asked to select the 10 most important variables for NSDI assessment in developing countries out of the list of 49 feasible variables (see also Figure 2, page 7). It is thinkable as well if more and/or different experts had been consulted, other key variables could have come forward as very important. It might also be that another result could have been achieved if the SDI experts had given their opinion on the initial list of 94 identified variables. Hence the overall results may be subjective. However, the research methodology adopted for this study and the embedding of the study in literature keeps these risks within acceptable limits. Looking at the selected key variables, one could conclude that the selected variables are crucial for the enhancement and innovation of NSDIs in developing countries in a more strategic and operational way. The expert variables are in line with the case study variables. Assessment variables have been gathered from different scientific studies. During the brainstorm session, scientific articles with different assessment angles have been reviewed. Some of the variables appeared to be more difficult to measure and to compare with each other than others. As can be noticed in Table G (Appendix), variables are qualitative (‘yes/no’, ‘categories’ etc.) or quantitative (‘amounts’, ‘numbers’ etc.). The combination of both qualitative and quantitative variables in the table complicates the actual comparison of the separate SDI components of the case study countries with each other. For comparison of the variables in the different SDI components of the case study countries, an index could have been used. To assign weights to the many different variables and the separate SDI components is not an easy task. Since each country is unique in historical, legal, economic, technological, cultural and institutional terms, one variable might have more weight in one country than in the other. Furthermore, not all information on the variables per SDI component is retrieved and/or available. Another method to reduce the number of variables and to detect structure in the relationships between variables is factor analysis. Seeing the large number of identified variables, the variety in measurement modes (qualitative, quantitative), and the limited time available, this research has not looked at factor analysis techniques. From above-described discussion, the following recommendations for further research can be given: In the near future, similar research with respect to the case study countries could be carried out to

better capture and understand critical changes in the variables. Furthermore, the investigation of


other developing countries could be taken into consideration in order to check if other variables would come forward as very important.

It could be explored if other techniques such as an index or factor analysis to reduce the number of variables and to detect structure in the relationships between variables, that is to classify variables, give another result (in other words: another set of key variables).

References 69

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References 74

Appendices 75

Appendices Definitions of NSDI variables Tables with descriptions of:

Colombia Table A Cuba Table B Nepal Table C Indonesia Table D Nigeria Table E Ethiopia Table F

Table with possible answers variables: Table G Tables with comparison of NSDI components (country / continent):

Data component Table H People component Table I Access network component Table J Policy component Table K Standards component Table L Other component Table M

Table with consulted SDI experts: Table N Table with answers SDI experts: Table O

Appendices 76

Definitions of NSDI variables By Lukasz Grus & Lyande Eelderink Data component: Core data sets: presence of a common ingredient in the construction of national and global SDI's to provide common data collection schemas (Nebert, 2004). For example these can be elevation data, topographic data, cadastral data etc. Data format: according to Groot and McLaughlin (2000) - data format (standards group) can be divided in: (1) geospatial data format – digital (raster/vector) or analogue and maybe data extensions (e.g. .shp, tiff, etc.), (2) data content/data dictionary standards, (3) data coding and classification standards, (4) data exchange format standards, and (5) metadata standards. Data maintenance: the frequency of taking care of (maintaining) the data. Data quality: according to ISO 2002, quality is the totality of characteristics of a product that bear on its ability to satisfy stated and implied needs (‘fitness for use’). Elements of spatial data quality are: (1) lineage, (2) positional accuracy, (3) attribute accuracy, (4) logical accuracy, (5) completeness, (6) semantic accuracy, (7) usage, (8) purpose, (9) constraints, (10) temporal quality, (11) variation in quality, (12) meta-quality, and (13) resolution. Data accuracy: degree of uncertainty, error. Part of ‘data quality’. Data updating: timeliness of data within (N)SDI. For example, legal requirements for frequency of data updating. (Spatial) resolution: describes how much detail in an image is visible to the human eye. High-resolution images are sharp and more details are visible. Part of ‘data quality’. (from: http://www.chin.gc.ca/English/Digital_Content/Small_Museum/glossary_main.html). Language: language used in data description e.g. map legend (language national language, in English or in multiple languages). Digital data availability: availability of data in digital format (or data available in analogue format). Relevance: importance and significance of the spatial data in solving common users' problems. Reliability: data trustworthiness, dependent on data producer status, conformance to common standards. Data content: the content (completeness) of the data sets. Part of ‘data quality’. Uniform reference system: is spatial data referenced to the same nationwide reference system. People component: Driving forces: reason(s) why the particular NSDI initiatives emerged. Examples of driving forces can be multiple: promoting national competitiveness and productivity, to support economic growth, environmental protection, better governmental planning and development, natural resources management, better coordination in dealing with emergences, keeping data, military reasons, SDI initiatives imposed by others, executive order of the government body etc. Definition of core dataset: existence (preferably in legislative/governmental documents) of the strict definition of national core datasets.

Appendices 77

Language: availability of NSDI documentation in national language, in English or in multiple languages. Number and type of suppliers: number and type of organisations that produce and deliver data to NSDI. Number and type of users: number and type of users of NSDI resources and services. Number and type of institutes: number and type of institutes participating in NSDI initiative. Capacity building: improvements in the ability of all involved parties to perform appropriate tasks within the broad set of principles of that particular SDI initiative (Rajabifard, 2002). Existence of the elements required for building SDI: awareness of stakeholders about the importance of capacity building for NSDI, management, organisational ability to change, education, research, and organisation of conferences, seminars and workshops, technology etc. Education: availability of education on SDI in the country. SDI (GIS) related conferences/journals: availability of and access to conferences and journals on SDI. Research: availability of research programmes to support the NSDI initiative. User’s satisfaction: degree of contentedness of NSDI resources and services. User's involvement: involvement of users in creation and use of NSDI resources and services. Private/commercial participation: the extent to which private bodies are involved in NSDI creation, supply and utilisation. Awareness: decision makers and (end)users knowledge about NSDI benefits, potentials and its importance for the society. Human capital: existence of qualified staff capable to lead and work in NSDI initiatives. SDI culture: refers to success, partnerships, trust and professionalism of existing NSDI initiatives. Involvement of professional organisations (e.g. NGO etc.): involvement of advisory organisations in the NSDI building process. Size of user's involvement: number of users involved in NSDI initiative. Willingness to share data: nation's culture of sharing information. For example this characteristic may be reflected by Hofstede's index masculinity vs. femininity (Hofstede, 1980). Uncertainty avoidance: society's ability to deal with uncertain situations. This element may refer to uncertainty avoidance index (Hofstede, 1980) and characterizes the tolerance of society towards uncertainty and ambiguity. Access network component: Delivery mechanism (availability, search & procedures): spatial data can be delivered in 4 ways (Crompvoets, 2006): (1) prototype (metadata security check has to be arranged), (2) non-standardized metadata (graphical presentation - jpeg, bitmap, etc - as a subset of described dataset), (3) standardized metadata, and (4) data. Data can be also transmitted via e-mail or via OGC's standard Web Feature Service.

Appendices 78

Network architecture: the structure of an existing communications network, including the physical configuration, facilities, operational structure, operational procedures, and the data formats in use (from: Federal Standard 1037C: http://www.its.bldrdoc.gov/fs-1037/fs-1037c.htm). Data volume / data sets: number of datasets existing in NSDI. Response time: time between ordering the data and getting them ready to use and/or response time on a query within delivery mechanism (e.g. portal). Number of visitors: this variable indicates the use of national clearinghouse to access spatial data by end user (Crompvoets, 2006) by measuring number of visitors. Number of web references: this variable measures the popularity (use) of the clearinghouse over the Internet. It measures the number of links to homepage of the national clearinghouse that can be checked by the search engines (Crompvoets, 2006). Number of languages used: this variable refers to number of languages used in a national clearinghouse. Frequency of web updates: duration between the day of the last web update and the date of the measurement. Status: distinguished as three classless – (1) project, (2) product-portal and (3) clearinghouse (Crompvoets, 2006). Preview possibility: this characteristic refers to the possibility of previewing data before retrieving them. Implementation body: refers to who(m) is implementing and is responsible for implementation of NSDI supporting technology. E-business: level of business processes that are powered by information systems (especially by web-based services). Performance: the power of existing technology to fulfil the task (accomplishment, usefulness). Reliability: the degree to which end-users trust NSDI related technology; technology's vulnerability to failures; credibility of access network. Policy component: Executing coordinating body: presence, position and character of the body that is responsible for executing and coordinating of implementation of policies related to NSDI. SDI directive: existence of NSDI legislative act. Freedom of information act: level of accessibility to government-held information. Funding: funding model, stability, amount, and source. Intellectual property: property that can be protected under law, including copyrightable works, ideas, discoveries, and inventions. Copyright: the existence of a legal act regulating the exclusive right of a creator to reproduce, prepare derivative works, distribute, perform, display, sell, lend or rent their creations (from: http://www.stfrancis.edu/cid/copyrightbay/bg002.htm). Legal regulations concerning intellectual property (referring to spatial databases, information). Privacy: regulations concerning protecting private information included in spatial data.

Appendices 79

Pricing: regulations concerning prices of access to public information. Institutional arrangements for suppliers/users/value adders: organisational regulations between suppliers/users/value adders to arrange issues related to the exchange, access, and use of spatial data. Access privileges: any restrictions towards access to spatial data. Legal arrangements for suppliers/users/value adders: legal regulations between suppliers/users/value adders to arrange issues related to the exchange, access, and use of spatial data. Leadership: presence, importance, authority, type of leading NSDI player. Vision: existence of long-term, political NSDI vision. Partnership arrangement: existence of and regulations between stakeholders participating in NSDI initiative. Public/private partnership: existence of and regulations between public and private stakeholders participating in NSDI initiative. Data collection body: presence, number and character of bodies collecting and delivering spatial data and information. Membership in regional organization: membership (participation) of NSDI in any regional SDI initiatives. Liability: the legal responsibility of particular body for participation, implementation and coordination of SDI activities. Commercialization of data: is data sold at a price or can it be exchanged and accessed for free. Number and type of data that can be produced by private companies and type of data which production is restricted only to governmental bodies. Policy of preview: the right of the customer to preview data before purchasing/retrieving. Nature of spatial information market: qualities and characteristics of spatial information market. E-government existence: use of ICT in delivering governmental products and services to citizens and industry in particular country. Socio-political stability: general stability of the country in terms of political (vulnerability to wars, uprisings, radical political changes) or sociological (polarization of society, level of antagonistic ethnic groups living close to each other) issues. Standards component: Data transfer: standard designed to support the transfer of different types of spatial data. Metadata: availability of metadata standards approved for NSDI. Type and use of metadata standard: type and use of the agreed upon standard for metadata. Services: agreement of GIS software users/producers on using common web services standards (e.g. OGC-standards).

Appendices 80

Interoperability: the ability to successfully understand and share various data, software, and hardware across a broad spectrum of organisations and users level of interoperability between SDI nodes (producers, users). WMS: the presence of OGC standard Web Mapping Service in the access technology (OGC, 2001). WFS: the presence of OGC standard Web Mapping Service in the access technology (OGC, 2002). WPS: the presence of the OGC standard Web Processing Service in the access technology (OGC, 2005). WCS: the presence of the Web Coverage Service in the access technology (OGC, 2003). Others component: SDI coverage: coverage level of SDI technology (local, national etc.). Status: pilot, implementation or established. Development approach: driving forces, aim, reasoning. E.g. bottom-up or top-down. Decentralization/centralization: organisational structure of SDI system; characterizes if SDI is developing mainly on national, regional or local level. Communication channels: the arrangement of the communication between the different stakeholders in the initiative. SDI's complexity: understanding SDI initiatives must take into their account their multi-faceted nature. For example, the different facets do not add up, SDIs are dynamic (verb not a noun). From: De Man, 2006. Hierarchy: top-down, bottom-up, heterarchy, anarchy. SDI's maturity: the more coherent the community, the more likely it will be that the SDI development is successful. Four stages of development are defined (Kok and Van Loenen, 2004): (1) stand-alone stage, (2) exchange stage, (3) intermediary stage, and (4) network stage. SDI's history: year of first SDI initiative. SDI's impact visibility: social, economical impact; realising the importance of SDI by companies or society. Initiatives connected with SDI: visibility of connection of various initiatives (environmental, economical, safety) with SDI (GIS) technologies. For example, use of GIS and SDI technologies in various environmental protection initiatives. NSDI definition: existence of common SDI definition written in legislative act. Main problem/challenges with SDI: identified problems when dealing with SDI (narratives), how people deal with these problems. References: Crompvoets, J., 2006. National Spatial Clearinghouses – worldwide development and impact. PhD thesis, University of Wageningen, The Netherlands. Glossary websites (Last accessed: May 2006): http://www.chin.gc.ca/English/Digital_Content/Small_Museum/glossary_main.html

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http://www.its.bldrdoc.gov/fs-1037/fs-1037c.htm http://www.stfrancis.edu/cid/copyrightbay/bg002.htm Groot, R., McLaughlin, J., 2000, Geospatial data infrastructure. Concepts, cases, and good practice. Hofstede, G., 1980, Culture's Consequences: International Differences in Work-related Values, Sage Publications. ISO (International Standardisation Organisation), 2002. ISO 19113:2002 Geographic information - Quality principles, 29 p. Kok, B., and Loenen van, B., 2005. How to assess the success of National Spatial Data Infrastructures? Computers, environment and urban systems vol. 19, pp. 699 – 717. Man de, W.H.E., 2006. Understanding SDI; complexity and institutionalization. International Journal of Geographical Information Science. Vol. 20, No. 3, March 2006, pp. 329 – 343. Nebert, D., D., 2004, SDI Cookbook. OGC, 2001, Web Map Service Implementation Specification. OGC, 2002, Web Feature Service Implementation Specification. OGC, 2003, Web Coverage Service. OGC, 2005, Web Processing Service Specification. Rajabifard, A., 2002, Diffusion of Regional Spatial Data Infrastructures: with particular reference to Asia and Pacific Region., PhD thesis, Department of Geomatics, Faculty of Engineering, The University of Melbourne, Melbourne, Australia.

Appendices 82

Table A: Description of the Colombian NSDI COLOMBIA

Data component Core data sets

Topographic base maps of IGAC Topographic maps of the 32 provinces, incl. eco tourism, tourist attractions, hydrography Boundaries Transportation Geodetic Control Ortho-images Geographic Names Land Coverage Cadastre Soils (different scales and levels of coverage)

Data format DXF, GENERATE, E00 Maintenance Public institutions are still consolidating the GIS platform to produce digital data, the main goals are oriented to produce new data Quality

There is a national standard NTC 5043 – spatial data quality principles Actually, different institutions only apply accurate parameters to assess data quality

Accuracy Depends on data scale Updating – adding of new data According to local projects and user needs Resolution Different scales and levels of coverage

Not mentioned via access network, but see http://www.procig.org/downloads/colombia03.pdf for an overview of scales Language Spanish only Availability digital data sets Digital data is available, e.g. in the web sites of the participating institutions, metadata of the most products can be found Relevance

High, as a fundamental component of the National Information System, ICDE is recognised as the reference information to decision making at geospatial level

Reliability No information available Data content No information available Uniformity (country reference system)

MAGNA SIRGAS, compatible with GRS80

People component Driving forces (data acquisition, SDI)

Definition of strategies that organise the production and distribution of geographic information in Colombia Establishment of cooperation between producers and users of geographic information Document produced data and facilitate the access Improvement of decision making process Harmonise information systems and interoperability

Definition of core data sets The basic data necessary to support decision making and national development = fundamental framework Language Spanish Nr. and type of suppliers

Ministerio del Medio Ambiente DANE

Appendices 83

Departamento Nacional de Planeacion IGAC IDEAM ICP-ECOPETROL INGEOMINAS FEDERACAFE

Nr. and type of users

Institutional users Public users Private users No information available on numbers

Nr. of participating institutes in network

9 – however: all levels of the institutes are participating (from local to national)

Capacity building (information dissemination, short courses and workshops, research and facilitation)

Centre of Research and Development on Geographic Information, CIAF, is in charge of carrying out technical projects, training courses and cooperation agreements

Education (type, availability) SDI short course and metadata short course via CIAF Quite a number of university degrees on geoinformatics etc. is offered in Colombia

SDI (GIS) related conferences/journals/ stakeholders

GSDI 5 took place in Colombia (2001) Semana de Geomática, 2005 Aniversario CIAF cada año

Research (to support NSDI) ICDE is following an approach of research and technology transfer from national, regional and global research User satisfaction (SDI & approach)

Improving – data availability is better now, users have access to digital data

User involvement

Users are not directly involved in the initiative Through the website of IGAC, users are asked if they are satisfied with the current portal

Private/commercial participation The private sector is involved in helping to produce and/or update geographic data for the Colombian NSDI, the commercial sector is also hired to install, operate, and maintain the network infrastructure and/or to disseminate data

Awareness (spatial data, SDI concept)

In the 1990s, awareness started to grow Now, most of public institutions know about ICDE and its importance

Human capital Good, well-trained people are available SDI culture

Most of the public institutions know about ICDE No information available on the private sector

Involvement professional organisations (NGOs etc.)

Not yet

Size of user involvement Not yet established Willingness to share data No information available Uncertainty avoidance No information available Access network component Delivery mechanism (availability, search & procedures)

Each participating institution has its own delivery mechanism

Appendices 84

Network architecture (type, telecommunications, Internet)

Local Area Network (LAN) inside institutions and Internet

Data volume / data sets No recent information available 38 (Crompvoets, data 2005)

Response time IGAC: extremely slow Nr. of visitors No information available Nr. of web references No recent information available

14 (Crompvoets, data 2005) Nr. of language used IGAC: only available in Spanish, English button does not work Frequency of web updates No information available Status

Project Participating institutes show data via their respective web sites, a system to link the servers is not yet realised

Preview possibility

IGAC: Yes

Implementing body IGAC as the coordinator body E-business None Performance (usefulness) IGAC: a preview possibility is available, metadata can be retrieved but does not seem to be complete

The portal is very slow Reliability The portal is very slow and sometimes does not respond to a query – not very reliable Policy component Executing coordinating body ‘Infraestructura Colombiana de Datos Espaciales (ICDE)’ under supervision of IGAC, www.icde.org.co SDI directive (existence)

No formal mandate exists IGAC is leading the formalisation of the NSDI and promoting a high level declaration

SDI directive (freedom of info act / copyright)

Not available, although institutions have to sell products and services in order to finance data production Data property is clearly defined in contracts and agreements

Funding (source)

IGAC is planning to propose an international credit contract with a multilateral organisation in order to finance ICDE and production of cartography and cadastre

Funding (amount) No information available Funding (model) Besides the loan (as mentioned in source), no information available Funding (stability) No information available

Most likely not very stable Intellectual property Intellectual property is clearly defined in contracts and institutional agreements Privacy No formal agreements to address privacy Pricing (data & access to services)

No formal agreements to address pricing In practice: digital data is sold at prices ranging from 1 to 5% of the production cost, analogue data is sold at the cost of duplication, private firms charge about 130% of the production cost

Institutional arrangements for suppliers/users/value-adders

The suppliers have come to an agreement (http://www.icde.org.co/productores.htm) No information available on users etc.

Access privileges No formal agreements to address access privileges Legal arrangement for suppliers/users/value-adders

http://www.icde.org.co/productores.htm No further information available

Appendices 85

Leadership (who, power)

There is no formal mandate to build the ICDE IGAC guides the process

Vision (political, long-term) High-level support seems to be the major area requiring further efforts Partnership arrangements No information available Public/private partnerships No information available Data collection body

Not defined Institutions produce data according their mission

Member of regional organisation PC IDEA Liability No information available Commercialisation of data Digital data is sold at prices ranging from 1 to 5% of the production cost, analogue data is sold at the cost of duplication, private firms

charge about 130% of the production cost Policy of preview No information available Nature of spatial information market

Quite a large market

E-government existence

Yes: More information on: http://www.gobiernoenlinea.gov.co/home_ciudadanos.aspx

Socio-political stability Unstable Standards components Data transfer A working group on standards including metadata has been established Metadata (availability)

A national geographic metadata standard was defined in March 1999, based on ISO & FGDC IGAC developed a metadata engine to create, edit, validate and publish metadata Up to now (2006), ICDE institutions have created about 180.000 metadata units

Type and use of metadata standard (ISO, CEN, FGDC)

NTC 4611, based on ISO and FGDC

Services

Metadata search Data download Data visualisation

Interoperability

Not implemented A spatial object catalogue is being developed by IGAC – to be discussed with different institutions

WMS Not available WFS Not available WPS Not available WCS Not available Others component SDI coverage (local, global) National coverage

Status

Project / Implementation The incipient partnerships must be strengthened and coordinated – a national coordination centre must be established (Arias, 2006) Institutions have developed technical components as part of their own information system projects and strategies

Appendices 86

Development approach (bottom-up, top-down)

Bottom-up: no formal mandate, however, the government agencies decided to work together Now IGAC is promoting high level support to ensure top-down support and to institutionalise relationships (Arias, 2006)

Decentralization / centralization Decentralization – focusing on institutional responsibilities and efforts to build ICDE Communication channels Mainly institutional communication (Arias, 2006) SDI’s complexity Complex in a way that no mandate of the government is in place – institutions should link their servers Hierarchy (vertical & horizontal relationships)

Both, between technical areas and institutions, from high level to technical level (Arias, 2006)

SDI’s maturity

In between ‘exchange stage’: focus on standardisation and datasets and ‘intermediary stage’: awareness for cooperation Actually, ICDE is focusing its efforts on policy formulation (Arias, 2006)

SDI’s history (years of existence)

1995: IGAC developed a geographic object classification scheme At the same time, ECOPETROL started to focus on standards and metadata Both initiatives pushed forward the creation of a national committee understanding the need for homogeneous and consistent data 1998: government agencies in charge of GI production agreed to work jointly to define policies, guidelines and strategies to foster the production and publication of geographic data 2000: main producer institutions agreed to build ICDE and PC IDEA (SDI for America) 2004: Government created the commission for information policy and data management called ‘COINFO’

SDI’s impact visibility ICDE has struggled to gain visibility – currently the public institutions know and understand the importance (Arias, 2006) Initiatives connected to SDI (country’s activity)

‘GIS for national land use planning’ – in cooperation with ASDI (Swedish cooperation)

NSDI definition (goal)

A set of policies, standards, organisations and technology working together to produce, share, and use geographic information about Colombia in order to support national sustainable development

Main challenge (e.g. implementation or maintenance)

Organisational issues: no formal mandate to build the ICDE Institutions continue to focus on the development of GI suitable for their own needs Policy issues: no formal agreements to address privacy, access, use, pricing, and liability User needs: a user needs study does not exist Cost-benefit: little information is available regarding the costs and benefits of geographic data in decision-making

Appendices 87

Table B: Description of the Cuban NSDI CUBA


Administrative boundaries Hydrography Inhabited areas and urban settlements Elevation Roads and geographic names There is not yet an official declaration of IDERC’s core data sets

Data format CARIS, AutoCad, MapInfo Maintenance

Depending on demand of clients (including the State) A strategy of maintenance is being included as part of the National Commission of the IDERC

Quality

The quality is associated to the procedures and technology established in the cartography industry (not well established) Standards should be incorporated in the future to assure quality

Accuracy No information available Updating – adding of new data An inventory of existing spatial data is being undertaken (by institution and by territory/Province) as part of the work of the Commission of

IDERC in order to increase the availability (adding) of new data in the SDI Resolution

1:250,000 1:100,000 1:5,000 (Urban settlements and main cities) 1:2,000 (Havana City)

Language Spanish only Availability digital data sets

1:250,000 (Complete) 1:100,000 (Complete) 1:5,000 (Urban settlements and main cities) 1:2,000 (Havana City) Not yet all data is available in digital format It is not exactly known which data is available in digital format

Relevance No information available Reliability No information available Data content No information available Uniformity (country reference system)

So far just the National Mapping Agency is providing data to the IDERC, so there is uniformity (Cuban North – South) Measurements should be adopted in the future to keep uniformity when other providers begin to supply data


The government Agreement to establish the National Commission of IDERC is the most relevant factor for NSDI development in Cuba (Delgado, 2006)

Definition of core data sets There is no official declaration of IDERC’s core data sets yet Language Spanish Nr. and type of suppliers 1 – The Hydrographic and Geodetic Service

Appendices 88

Nr. and type of users Government Enterprises Academy (GeoPortal users) No information available on numbers


24 ministries


Workshops are being organised regularly (e.g. with IGAC, US University, Wageningen University)

Education (type, availability) A large university on geoinformatics is currently being initiated The IT education (programming) is lacking, GI education is available


GEOMATICA: bi-annual congress, including activities (workshops, conferences, round tables, etc.) of SDI Workshops (one/two per year) into the framework of the work of the IDERC

Research (to support NSDI)

A group of researchers belonging to GEOCUBA is working on SDI themes such as: SDI Evaluation and Cost/Benefits Geospatial Semantics New SDI services Spatial Data Warehouse SDI Applications (sustainable development, environmental management, forestry, disaster management)

User satisfaction (SDI & approach)

Limited, portal offers few services and applications to municipalities and other institutions

User involvement

Limited The communication strategy of the CIDERC would like to increase involvement of users

Private/commercial participation Not relevant (The political system – socialism) Awareness (spatial data, SDI concept)

Not enough Since 4 years, several conferences and workshops have been given to political and technical sectors There is now (after IDERC) a strategy to disseminate SDI culture in the society

Human capital

There is capacity to improve the human capital So far there are around 10 persons with good skills into the SDI theme, and around 40 with moderate skills

SDI culture See awareness Involvement professional organisations (NGOs etc.)

IDERC is integrated by 21 organs of the Central Administration and the State, the Parliament is also included

Size of user involvement No information available – not measured yet (Delgado, 2006) Willingness to share data No information available – not evaluated yet (Delgado, 2006) Uncertainty avoidance No information available Access network component Delivery mechanism (availability, search & procedures)

National Geospatial Portal http://www.iderc.co.cu/, including a Catalogue Service, but so far just from one provider (Hydrographic and Geodetic Service / GEOCUBA)

Appendices 89


There is a Central Server administrated remotely by data owners The Server is ready for connection to other Web Map Servers

Data volume / data sets

Geographic names Population Topographic Maps (1:250,000, 1:100,000) Plannimetric Maps (1:5,000)

Response time Has not been evaluated yet Nr. of visitors ~1500 visitors per month (evaluated in June 2005) Nr. of web references More than 50 Nr. of language used Spanish only Frequency of web updates Every three months Status Product-portal Preview possibility Yes, interactive map Implementing body Hydrographic and Geodetic Service

(CIDERC) E-business

Yes: (http://bazar.cuba.cu/geocuba/)

Performance (usefulness) Although no evaluation of usefulness has been carried out, the Geographic Dictionary is being used by many people, even working in other sectors in the country; such as investment, telecommunications, etc. (Delgado, 2006)

Reliability Has not been evaluated yet Policy component Executing coordinating body National Commission of the Spatial Data Infrastructure of the Republic of Cuba (CIDERC) SDI directive (existence)

Yes The CIDERC initiative has a President, a Coordination Body and an Executive Secretary


Not established yet

Funding (source)

Government International funds (CYTED, UN)

Funding (amount) Equivalent to 300,000 USD per year (updating and adding of new data are not included) Funding (model) No information available Funding (stability) The amount is stable (at the moment) Intellectual property No information available Privacy No information available Pricing (data & access to services)

No information available



Access privileges No information available Legal arrangement for suppliers/users/value-adders


Leadership (who, power) Hydrographic and Geodetic Service

Appendices 90

Vision (political, long-term) IDERC Strategy – until 2010 Partnership arrangements No information available Public/private partnerships Not relevant Data collection body Traditional data collection entities (National Mapping Agency – Hydrographic and Geodetic Service, and others) Member of regional organisation PC IDEA Liability No information available Commercialization of data Not relevant Policy of preview No information available Nature of spatial information market


E-government existence No information available Socio-political stability Good (Delgado, 2006) Standards component Data transfer Standardisation is a challenge in Cuba; data is produced in different formats Metadata (availability)

Poor availability at present There is a strategy to increase the availability


ISO 19115

Services

WMS, WFS, Catalogue Service Applications: Generic Viewer, Geographic Dictionary, and Population

Interoperability OGC conformance WMS Yes WFS Yes WPS Yes WCS Yes Others component SDI coverage (local, global) National coverage Status Implementation stage Development approach (bottom-up, top-down)

Top-down

Decentralization / centralization Centralization opening to decentralization Communication channels

There is a strong investment in communication in the country There is a national backbone and other kinds of communication channels It should be improved in the near future

SDI's complexity Not too complex (Delgado, 2006) Hierarchy (vertical & horizontal relationships)

‘Under construction’

SDI's maturity In between ‘exchange stage’: focus on standardisation and datasets and ‘intermediary stage’: awareness for cooperation SDI's history (years of existence)

The beginning is fuzzy The first actions began in 1999 (the Hydrographic and Geodetic Service identified the need to develop an NSDI), but the government

Appendices 91

Agreement was approved in 2005 SDI's impact visibility Has not been evaluated yet Initiatives connected to SDI (country’s activity)

National Society Information Programme


Opens the policies, technologies, standards and human resources needed for the effective collection, administration, access, delivery and use of spatial data at national level to take economic, political and social decisions on sustainable development


At present: the implementation, for the future: the maintenance Human resources to further develop the infrastructure Organisational arrangements (policy) Funding

Appendices 92

Table C: Description of the Nepalese NSDI NEPAL

Data component Core data sets Topographic base maps of Survey Department (SD)

Ortho photos of SD Socio-economic and demographic data of Central Bureau of Statistics (CBS)

Data format Most of the GIS users use ESRI software, therefore the ArcGIS format is used Maintenance During the period 1992 – 2001, a complete set of new topographic maps were published by SD Quality SD and CBS survey data are based on generally accepted quality standards. Other organisation data are mostly prepared for particular

applications Accuracy SD data are based on generally accepted accuracy standards. Other organisation data are mostly prepared for particular applications Updating – adding of new data Populating data itself is the main concern, updating not prioritised yet Resolution

Ortho photos: 1:5,000 and 1:10,000 Topographic maps: 1:25,000, 1:50,000, 1:100,000, 1:250,000, 1:500,000, 1:1M

Language English Availability digital data sets

Not all participating agencies have data available in digital format Data of SD (topographic maps, orthophotos) is available in digital format

Relevance No information available Reliability No information available Data content No information available Uniformity (country reference system)



Realisation of wasting a considerable sum of limited resources in the (duplicated) creation of geo-spatial data Mandate of government (2002) Assistance of EC Drive for new public management

Definition of core data sets

Topographic data based on topographic base maps Socio-economic/ demographic data based on census

Language English Nr. and type of suppliers Few government agencies provide digital data

Many others do not have data in digital form Nr. and type of users

Several users have been identified so far by the SD, coming from sectors such as: student/research, water sector, environment sector, infrastructure, geological survey, forestry, telecommunications, utilities


Thirty-nine (39): Survey Department, Central Bureau of Statistics, Ministry of Local Development, Ministry of Agriculture, Ministry of Population and Environment, Ministry of Health and 33 district level offices

Capacity building (information The importance of capacity building is realised

Appendices 93

dissemination, short courses and workshops, research and facilitation)

Awareness is gradually growing among decision-makers

Education (type, availability) No adequate focus on NSDIs within University system, GIS education is not satisfactory Education SDI (GIS) related conferences / journals stakeholders

Not specifically on SDI (on GIS yes)

Research (to support NSDI) No research programme available User satisfaction (SDI & approach)

The user community has not been involved so far

User involvement The user community has not been involved but the importance is realised Private/commercial participation Private/commercial participation not yet established, limited private market Awareness (spatial data, SDI concept)

A low level exists with decision-makers regarding the potential benefits of SDIs Awareness is available with those who studied abroad (started lobbying)

Human capital GIS professionals are available No adequate focus on NSDIs within University system, GIS education is not satisfactory

SDI culture The level of awareness and understanding is still very low Involvement professional organisations (NGOs etc.)

None

Size of user involvement No involvement of users although several users are identified (from individual students and researchers to power companies, etc.) Willingness to share data The willingness to share is slowly growing – SD gives base maps to everybody Uncertainty avoidance No information available Access network component Delivery mechanism (availability, search & procedures)

No clearinghouse available yet – working towards ‘product portal’, see: http://www.dosm.gov.np


Internet/ intranet based on radio communication, LAN, and RAS

Data volume / data sets 4 to 5 GB 13 datasets (Crompvoets, data 2005)

Response time 1 to 2 days (of SD) Nr. of visitors Not known Nr. of web references Not known (Chhatkuli 2006)

6 (Crompvoets, data 2005) Nr. of language used 1 (= English) Frequency of web updates Suppliers can enter metadata (login required) – no information available on frequency Status Project: building on the portal Preview possibility No (just metadata) Implementing body

The Survey Department realises the need of a clearinghouse but encountered that such effort requires consensus among the data producers, which is not yet reached At present a metadata clearinghouse is in place

E-business No E-business

Appendices 94

Performance (usefulness) Not good, the internet page (portal) often does not work Reliability Not good, the internet page (portal) often does not work Policy component Executing coordinating body

Survey Department (SD) of the Ministry of Land Reform and Management (National Mapping Agency)

SDI directive (existence)

Yes Critical note SD: ‘A continued political, administrative and technological commitment is necessary It is not always easy to maintain a policy continuity in a developing country like Nepal’


Inter-organisational workgroup on copyrights has been established Permission of SD is necessary for publishing maps, SD makes topographic base maps available without any hindrance

Funding (source) The programme was established in 2002 and had the support from the European Commission during the first three years Now: government of Nepal funding (HMGN)

Funding (amount) Partly funded by the European Commission during the first three years (€ 540,000) Funding (model) Project funding by EC now taken over by HMGN Funding (stability)

Project funding + donor money now taken over by HMGN Stability is unlikely

Intellectual property

‘Policy should be formulated such that authentic, authorised, reliable and up-to-date geo-information is available to users freely, easily, and readily’

Privacy Policy yet to be formalised Pricing (data & access to services)

Inter-organisational workgroup on pricing and commercialisation (not on access) has been established


A proper institutional framework is considered very challenging and difficult: a structure has been suggested but does not seem to be in place

Access privileges At the moment, a metadata clearinghouse is available – accessible to everybody Legal arrangement for suppliers/users/value-adders

Inter-organisational workgroup institution/ legal issues established

Leadership (who, power) SD: most articles on the Nepalese NSDI are written by Mr Chhatkuli, the director of the NGII programme Vision (political, long-term)

His Majesty's Government of Nepal (HMGN) issues plans of five years The importance of the geographic information infrastructure is realised in the 10th plan (2002-2007)

Partnership arrangements Partnership arrangement between several agencies (see stakeholders) Public/private partnerships

Additional focus has been given to public/private partnerships, even involving the community An example is given for cadastral survey projects, where the beneficiaries could directly see the involvement

Data collection body Survey Department Member of regional organisation PCGIAP, GSDI, ISCGM, FIG, AARS, GEO Liability No information available Commercialisation of data Inter-organisational workgroup on pricing and commercialisation (not on access) has been established Policy of preview No information available Nature of spatial information market

The geospatial private market is very limited

E-government existence None Socio-political stability Unstable

Appendices 95

Standards component Data transfer Inter-organisational workgroup on standards has been established Most of the participating agencies do not have data in digital format - if

digital data exists, a significant amount of time is required to bring them in sharable form Metadata (availability)

Metadata system is in place and some data (mainly of SD) is already available Continuation efforts for populating the system is in progress


The importance is being realised, FGDC adopted

Services None Interoperability

Lack of standardisation and a system of data exchange: results in the duplication of efforts and the generation of a huge degree of redundant data

WMS No WFS No WPS No WCS No Others component SDI coverage (local, global) Only national (mainly topographic) maps are available Status

The ‘National Geographic Information Infrastructure’ (NGII) programme was established in 2002 and had the support from the European Commission during the first three years It has been launched with limited participation; it is considered to be in a ‘pilot-phase’


A bottom-up approach is followed in Nepal: making the best use of already available data, technology and the institutional framework

Decentralisation / centralisation No information available Communication channels

The Survey Department realises problems related to horizontal communication within the public sector The existence, communication and diffusion of GIS knowledge among end-users, technical professionals and decision-makers are crucial but not yet happening

SDI’s complexity No information available Hierarchy (vertical & horizontal relationships)



In the period 1992-1997, the creation of many spatial databases started From 1997 to 2002, the focus on geo-information increased In 2002, the need for an SDI was mentioned in the national plan document for the first time

SDI's impact visibility No information available Initiatives connected to SDI (country’s activity)



To strengthen planning and resource management through the development of a geographic information infrastructure for the access of geographic and related data for decision-making


Proper institutional setup, common standards, SDI culture, sustainability

Appendices 96

Table D: Description of the Indonesian NSDI INDONESIA

Data component Core data sets Geodetic data

Topographic data Cadastral data Bathymetric data Thematic data in four classes: land resources, forest resources, water resources, geology and mineral resources

Data format ESRI Maintenance

A data management mechanism has been developed for agencies to develop / maintain their data in such way that databases are of good quality, well maintained and nationally integrated

Quality Good quality: see above Accuracy No information available Updating – adding of new data Updating is done by authorised institute; frequency is not known Resolution Different scales and coverages Language Bahasa Indonesian Availability digital data sets Most data is available in digital format Relevance No information available Reliability No information available Data content No information available Uniformity (country reference system)



Reaching of synergy among all government institutions, private sector, universities, NGOs, and the community To optimise community participation in spatial data acquisition and dissemination in order to support economy growth, increase of social conditions and the environment All government institutions to put into practice good governance

Definition of core data sets No information available Language Bahasa Indonesian / English Nr. and type of suppliers

3 (Crompvoets, data 2005) Bakosurtanal, Centre for Soil and Agro-climatic Research and Centre of Data and Information of the Department of Regional Settlement and Infrastructures

Nr. and type of users No information available Nr. of participating institutes in network

3


A forum on human resources has been established, an inventory is being carried out Bakosurtanal has the mandate to increase the capability of SDI human resources Bakosurtanal conducts workshops to regional high rank officials to create SDI awareness Cooperation between institutions in improving human resources capability is needed by providing regular training and education

Education (type, availability) Short courses and courses at bachelor level are available

Appendices 97




A forum on research and development has been established A provincial research council will be defined Research results should be directed to support the decision making process in the management of natural resources and environmental management



User involvement No information available Private/commercial participation

Work related to the geodetic control network, base maps etc. is contracted to private organisations The private sector participates in the NSDI discussions

Awareness (spatial data, SDI concept)

Commitment is still low but knowledge about SDIs is gained Little understanding within the provincial and local government – the understanding is necessary because the development will be funded by all Indonesian governments Most data is developed for own use, no awareness of dissemination to others

Human capital The quantity and quality of human resources are inadequate – development of Human Resources is necessary SDI culture No information available Involvement professional organisations (NGOs etc.)


Size of user involvement No information available Willingness to share data Most data is produced for own use, no awareness of disseminating to others Uncertainty avoidance No information available Access network component Delivery mechanism (availability, search & procedures)

Bakosurtanal, National Coordinating Agency for Surveys and Mapping (www.bakosurtanal.go.id) – now metadata is available through the access system


A number of metadata servers that are interconnected forming a network; an additional server operates as a network gateway (metadata gateway server) TCP/IP protocol / Z39.50 protocol

Data volume / data sets No recent information available 38 datasets (Crompvoets, data 2005)

Response time Rather slow Nr. of visitors 4841 p/month (Crompvoets, data 2005) Nr. of web references No recent information available

14 (Crompvoets, data 2005) Nr. of language used Bahasa Indonesian Frequency of web updates No information available Status

Clearinghouse A lack of human resources, ICT network facility, institutional policies and guidance is noticed (Coordination meeting May 2005)

Preview possibility Yes (ArcIMS) Implementing body Bakosurtanal

Appendices 98

E-business None Performance (usefulness)

The access network is slow and sometimes does not respond to a query Bakosurtanal received a grant to improve the portal

Reliability Reliability of portal is not very high Policy component Executing coordinating body Bakosurtanal, National Coordinating Agency for Surveys and Mapping

(www.bakosurtanal.go.id) SDI directive (existence) Yes SDI directive (freedom of info act / copyright)

Maps and databases are protected by copyright up to 50 years from the first publication

Funding (source)

Government funding for the acquisition, storage, and retrieval of spatial data + http://www.mofa.go.jp/policy/oda/longlist/indonesia.html Assistance of Japanese Ministry of Foreign Affairs is to be expected – US$ 100.40 million

Funding (amount)

No information available Grant 100.40 million

Funding (model) Project funding Funding (stability) Unlikely Intellectual property Maps and databases are protected by copyright – issue is under discussion – guidance (at national level) is under construction

(see also Section 5.3.5) Privacy Maps and databases are protected by copyright Pricing (data & access to services)

Most government data is made available on the basis of replacing the basic cost for data reproduction Prices from data under custody of the private sector varies from company to company



Access privileges No arrangements Legal arrangement for suppliers/users/value-adders

No arrangements in place (see articleAbdulharis et al., 2005)

Leadership (who, power) Bakosurtanal Vision (political, long-term)

A long time vision (2005-2020) is present (for example the implementation of clearinghouses at different levels and the maintenance of fundamental data)

Partnership arrangements No information available Public/private partnerships No information available Data collection body Bakosurtanal Member of regional organisation Indonesia has been actively participating in the Permanent Committee on GIS for Asia and the Pacific, and GSDI Liability No information available Commercialization of data No information available Policy of preview No information available Nature spatial information market No information available E-government existence A presidential instruction has been issued concerning the involvement of ICT in the implementation of good governance: all government

Appendices 99

agencies have to implement E-government Socio-political stability Unstable Standards component Data transfer Standards have been implemented for maps, metadata, database, format exchange Metadata (availability) Yes – but inappropriate in almost all data producing institutes (‘still voluntary’) Type and use of metadata standard (ISO, CEN, FGDC)

FGDC

Services None Interoperability Data spread out in many institutes, not yet all using standards (although regulations are present), integration/interoperability still difficult WMS No WFS No WPS No WCS No Others component SDI coverage (local, global) National Status Implementation Development approach (bottom-up, top-down)

Top-down

Decentralization / centralization No information available Communication channels No information available SDI's complexity No information available Hierarchy (vertical & horizontal relationships)



1985 – 1998: Implementation of pseudo SDI (land and marine) 1995: Adoption of unified geocentric datum 1993 – 2000: Implementation of digital mapping (land and marine) 2001 – 2004: 1st Phase SDI: (establishment secretariat, annual coordination meetings, standards, guidance for custodianship, prototype clearinghouse) 2005 – 2020: 2nd Phase SDI: ‘Availability of prime data which can be easily accessed by community of users and easily integrated in one effective national standard’ Promoting to government, launching clearinghouse, capacity building, promoting public private partnership, continuation of development of national standard, cooperation between central / local government, university and private sector

SDI's impact visibility No information available Initiatives connected to SDI (country’s activity)

Bakosurtanal received a considerable grant from the Japanese government

NSDI definition (goal) To make available and accessible fundamental datasets within the Indonesian territory described by a national standard Main challenge (e.g. implementation or maintenance)

Getting recognition from government and parliament, maintaining the commitment (programme, human resources and funding), getting inter-institutional commitment, creation of regulation

Appendices 100

Table E: Description of the Nigerian NSDI NIGERIA


Geodetic control database Topographic database / DEM (1:25,000 and 1:50,000) Digital imagery and image maps Administrative boundaries Cadastral databases Transportation data Hydrographic data Land use/cover data Geological database Demographic database (Not yet all available in digital format)

Data format At the moment, data is mostly acquired and stored in analogue format Maintenance Most of the datasets are outdated – conversion of 1:50,000 is ongoing but revision is required Quality Dealt with by working group on standards Accuracy Topographic database / DEM (1:25,000 and 1:50,000) Updating – adding of new data

Updating of datasets on a continuous basis but no later than five years after production If data is updated, the lead organisation has to be informed within 30 days and update the data within 7 days Archived data is time-stamped

Resolution 1:25,000 and 1:50,000 Language English Availability digital data sets

At the moment, GI is acquired and stored in analogue format with few digital datasets such as orthophoto and ortho-images in some states and organisations

Relevance Data is very relevant for decision-making purposes Reliability No information available Data content No information available Uniformity (country reference system)

In terms of the geodetic coordinate system coverage, the Survey Departments have not yet covered the country effectively The absence of a national geoid has hampered the realisation of the full potentials of the benefits of satellite imagery Harmonisation, extension and wholesome adjustment of existing network in progress


(1) Need to adopt policies for promoting greater awareness and public access to standard and coordinated geo-spatial data production, management and dissemination by all sectoral institutions (2) Successful launch of Nigeria’s Earth Observation Satellite (NigeriaSat-1) and the impact on development activities has served as a catalyst to the NSDI development (3) New Partnership for Africa’s Development (NEPAD) – provision of relevant GI to facilitate national development and regional integration (4) Call of UNECA to establish SDI

Appendices 101

(5) ICT – as it permits GI sharing and growth Definition of core data sets

Dataset with national coverage needed consistently by more than one government agency in order to achieve their objectives or a dataset that cannot be derived from another dataset and other agencies derive significant benefit from using it

Language English Nr. and type of suppliers

An inventory is currently going on In the NGDI committee: 27 members of different organisations are selected (NASRDA, universities, poly/mono technics, state representatives, private/NGO sector, federal ministries)

Nr. and type of users

An inventory is currently going on, mainly government organisations (Ministry of Agriculture and Rural Development, Minister of Defence, Ministry of Environment, Ministry of Science and Technology, Ministry of Solid Minerals, Ministry of Water Resources, Ministry of Works)


All the GI services producers and users at national, state and local government levels Approximate number shall be known after inventory of GI resources and organisations


A working group on capacity building and awareness has been established to encourage: Basic training, promotion of research, promotion on awareness, reviewing geoinformatics curricula, promotion of institutional reforms etc.

Education (type, availability)

Despite the developments, availability of properly trained personnel is still a problem – review of geoinformatics curricula is being encouraged by the working group on capacity building and awareness


A regional workshop on SDI took place in Nigeria in November 2005 NGDI Stakeholders workshop in February 2003 NigeriaSat-1 Workshop in 2004 National SDI Workshop for Surveyors General by RECTAS in October 2003


Research has been stimulated by the launch of NigeriaSat-1 Research is also stimulated by the working group on capacity building and awareness


Not yet measured

User involvement

Yes A Users Requirement Survey and Analysis is currently being carried out alongside an awareness campaign

Private/commercial participation Yes Awareness (spatial data, SDI concept)

A working group on capacity building and awareness has been established Training workshops are being organised to familiarise the stakeholders on the project

Human capital Well-trained staff is required SDI culture The awareness level and understanding is slowly increasing Involvement professional organisations (NGOs etc.)

A committee on NGDI has been established to guide the establishment and implementation of the NGDI in line with the GI Policy – 4 members of professional organisations are part of the committee

Size of user involvement A Users Requirement Survey and Analysis is currently being carried out Willingness to share data There is no law in place to share data and/or submit data to a Central Government Agency Uncertainty avoidance No information available Access network component Delivery mechanism (availability, search & procedures)

www.nasrda.org

Appendices 102

No clearinghouse / access network available yet A working group on clearinghouse and metadata has been established Telecommunication /electricity power facilities are still problematic and might cause difficulties to the project


The intention is to put in place a high-speed and high-bandwidth backbone carrier as the main gateway and master server and implement a database server at each NGDI node

Data volume / data sets Final output of user requirement survey and analysis expected to give information Response time Not available yet Nr. of visitors Not available yet Nr. of web references Not available yet Nr. of language used English Frequency of web updates Not available yet Status Access network not available yet – project stage Preview possibility Not available yet Implementing body NASRDA E-business Not available yet Performance (usefulness) Not available yet Reliability Not available yet Policy component Executing coordinating body

National Space Research and Development Agency (NASRDA) – www.nasrda.org – of the Ministry of Science and Technology NASRDA appointed the Regional Centre for Training in Aerospace Surveys (RECTAS) as the project consultant for implementation of the NSDI project A Users Requirement Survey and Analysis is currently being carried out alongside an awareness campaign

SDI directive (existence)

In process; GI Policy by Ministry of Science and Technology (September, 2003), drafted by 10 GI experts from academia, stakeholder Ministries, and GI related community in the private sector


Focus of working group on legal issues

Funding (source)

2.5% of annual budget 10% of National Ecological Fund 0.5% of profit-after-tax of private organisations All income generated from access charge and data sales International funding and grants (not yet received so far) – the Economic Commission for Africa (ECA) has committed technical manpower and funds to help African countries who embark on implementation of NSDI Working group on Sustainability & Funding set-up

Funding (amount) Presently through national budget of NASRDA Funding (model) Mainly government Closer to cost recovery Funding (stability) A working group on sustainability and funding has been established Intellectual property Focus of working group on legal issues Privacy Focus of working group on legal issues Pricing (data & access to Focus of working group on sustainability and funding:

Appendices 103

services)

For community data, the guidelines are as follows: Research/education: subsidised rate of no more than 50% of cost of production Government to government: only cost of production and dissemination Commercial/private: not less than cost of production and dissemination


Dealt with by working group on legal issues

Access privileges

Two types: Restricted access – data that relate to national security Community access – data that can be accessed freely without restriction

Legal arrangement for suppliers/users/value-adders

A working group on legal issues has been established

Leadership (who, power) The Federal Ministry of Science and Technology and the NASRDA Vision (political, long-term) ‘To enhance GI for the alleviation of poverty and improvement of quality of life’ Partnership arrangements Focus of working group on legal issues Public/private partnerships Not yet Data collection body NASRDA and other mandated agencies for geo data collection e.g. Office of Surveyor General of the Federation Member of regional organisation UNECA Liability No information available Commercialisation of data Dealt with by working group on legal issues Policy of preview Dealt with by working group on legal issues Nature of spatial information market


E-government existence Gradually coming up Socio-political stability Unstable Standards component Data transfer A working group on standards has been established Metadata (availability)

A working group on clearinghouse and metadata has been established Striving to use ISO metadata standard


ISO after endorsement by the Standard Organisation of Nigeria (SON)

Services Usual GI services expected Interoperability Focus of working group on standards WMS Not available yet WFS Not available yet WPS Not available yet WCS Not available yet Others component SDI coverage (local, global) National Status Project stage

Appendices 104


Mainly top-down being driven by a national GI policy

Decentralisation / centralisation Decentralisation scheme Communication channels Infrastructure: telephone density is poor but one of the better in Africa

The tele-density is increasing rapidly after the introduction of GSM services Communication between organisations is minimal Communication between governments is minimal

SDI's complexity Not information available yet Hierarchy (vertical & horizontal relationships)

Both are encouraged in the organisational set-up with membership from local to national levels

SDI's maturity ‘Exchange stage’: focus on standardisation and datasets SDI's history (years of existence)

The first initiatives started between 1996 and 1997. A National Committee was established by the Ministry of Science and Technology in September 2002 The GI Policy was submitted to the Ministry in September 2003 The 27-member NGDI Committee was set-up in 2004 and six sub-committees (working groups) were established

SDI's impact visibility

A GI Policy has been drafted with contributions from stakeholders including an international workshop; the policy is an essential backbone for the realisation of the NGDI When analysing against the developments at regional level in Africa, the Nigerian approach may serve as one of the best practices


Very active: participation in conferences (GSDI), organisation of workshops etc.


The collected datasets should be put to the maximum possible uses by publicising their existence and making them easily available to the widest possible audience


Funding; passage of policy into bill; capacity building

Appendices 105

Table F: Description of the Ethiopian NSDI * ETHIOPIA

Data component Data is mainly available in analogue format; working hard on the conversion from analogue to digital format People component The SDI concept is not well understood in Ethiopia Access network component No access network is available Policy component The Ethiopian Mapping Agency (EMA) is responsible No formal mandate exists Standards component Awareness on the importance of metadata standards exists because of the ENRAEMED initiative (http://geoinfo.uneca.org/geoinfo/ethiopia/index.html); however not all stakeholders complete forms ENRAEMED makes use of ISO and FGDC standards Others component An NSDI workshop was organised in 2002 by EMA in cooperation with UNECA The GSDI secretariat also conducted a workshop on metadata / clearinghouses / web-mapping in 2002 The NSDI initiative is in the stand-alone stage: SDI has no priority at all

* Although all possible channels in Ethiopia have been approached (EMA, UNECA, contacts WUR and contacts ITC), unfortunately little information on the Ethiopian NSDI has been received.

Appendices 106

Table G: Possible answers to assessment variables (of identified variables Table 2)

SDI COMPONENTS Data Pre-defined answer (for comparison purposes) Core data sets Defined / not defined Data format

Digital format: ESRI Other

Analogue format Maintenance Yes / No Quality Good / acceptable / not good Accuracy

Yes / No → Standards for accuracy No standards for accuracy

Updating – adding of new data Yes / No Resolution

Descriptions High / low

Language

Language of country Additional language (English)

Availability digital data sets Considerable / some / none Relevance Relevant / not relevant Reliability Reliable / not reliable Data content Descriptions Uniformity (country reference system) Yes / No People Pre-defined answer Driving forces (data acquisition, SDI) Descriptions Definition of core data sets Yes / No Language

Language of country Additional language (English)

Nr. and type of suppliers # and type Nr. and type of users # and type Nr. of participating institutes in network # Capacity building (information dissemination, short courses and workshops, research and facilitation)

Yes / No

Education (type, availability) Type and availability SDI (GIS) related conferences/journals/ stakeholders

Yes / No

Research (to support NSDI) Yes / No User satisfaction (SDI & approach) Good / moderate / bad User involvement Yes / No

VAR

IAB

LES

Private/commercial participation Yes / No

Appendices 107

Awareness (spatial data, SDI concept) Good / moderate / bad Human capital (resources) Sufficient / not sufficient SDI culture Understanding / moderate understanding / no understanding Involvement professional organisations (NGOs etc.)

Yes / No

Size of user involvement Size Willingness to share data Yes / moderate / no Uncertainty avoidance Description Access network Pre-defined answer Delivery mechanism (availability, search & procedures)

Yes / No


Type of architecture

Data volume / data sets Volume + number Response time

Time Fast / moderate / slow

Nr. of visitors # Nr. of web references # Nr. of language used # Frequency of web updates Frequency Status

None Project Product portal Clearinghouse

Preview possibility Yes / No Implementing body Present / not present E-business Yes / No Performance (usefulness) Good / reasonable / bad Reliability Good / reasonable / bad Policy component Pre-defined answer Executing coordinating body

Yes / No → Present / not present

SDI directive (existence) Yes / No SDI directive (freedom of info act / copyright)

Yes / No

Funding (source) Yes / No Funding (amount) Amount Funding (model) Model Funding (stability) Yes / No / not likely Intellectual property

Yes / No → Arranged / not arranged

Appendices 108

Privacy


Pricing (data & access to services)




Access privileges


Legal arrangement for suppliers/users/value-adders


Leadership (who, power) Present / not present Vision (political, long-term) Yes / No Partnership arrangements Yes / No →

Arranged / not arranged Public/private partnerships


Data collection body Present / not present Member of regional organisation Yes / No Liability


Commercialization of data


Policy of preview Yes / No Nature of spatial information market Large / average / small E-government existence Yes / No Socio-political stability Stable / moderate / unstable Standards Pre-defined answers Data transfer Arranged / not arranged Metadata (availability) Yes / Partly / No Type and use of metadata standard (ISO, CEN, FGDC)

ISO / CEN / FGDC / other

Services Yes / No Interoperability Yes / No WMS Yes / No WFS Yes / No WPS Yes / No WCS Yes / No Others Pre-defined answers SDI coverage (local, global) National / global Status

Pilot Implementation Established

Appendices 109


Bottom-up / top-down

Decentralization / centralization Decentralization / centralization Communication channels Good / acceptable / not good SDI's complexity Very complex / complex / not complex Hierarchy (vertical & horizontal relationships)

Vertical / horizontal / both

SDI's maturity Stand-alone stage Exchange stage Intermediary stage Network stage

SDI's history (years of existence) Description SDI's impact visibility Visible / in between not visible Initiatives connected to SDI (country’s activity)

Description

NSDI definition (goal) Description Main challenge (e.g. implementation or maintenance)

Challenges

Appendices 110

Table H: Comparison of data component between case study countries DATA COMPONENT LATIN AMERICA ASIA AFRICA VARIABLES COLOMBIA CUBA NEPAL INDONESIA NIGERIA ETHIOPIA Core data sets Defined / not defined

Defined Defined Defined Defined Defined No information available

Data format Digital format: ESRI Other

Analogue format

ESRI: E00 Other: DXF,

Generate

Other: CARIS, AutoCad, MapInfo

ESRI ESRI Analogue format Analogue format

Maintenance Yes / No

No

Yes No Yes No No

Quality Good / acceptable / not good

Good Acceptable Acceptable Good Analogue format: acceptable


Accuracy Yes / No → Standards for accuracy No standards for accuracy

Yes

No Yes No information available

Yes No information available

Updating – adding of new data Yes / No

Yes No No Yes Converted data: Yes

No

Resolution Descriptions High / low

Different scales and levels of

coverage: high and low

Different scales and levels of

coverage: high and low

Different scales and coverage: high and low

Different scales and coverage: high and low

Two scales No information available

Language Language of country Additional language (English)

Language of country (Spanish)


Additional language: English

Language of country (Bahasa

Indonesian)



Availability digital data sets Considerable / some / none

Considerable Some

Some Some Some - none Some - none

Relevance Relevant / not relevant

Relevant No information available



Available data: relevant


Appendices 111

Reliability Reliable / not reliable







Data content Descriptions







Uniformity (country reference system) Yes / No

Yes Yes Yes Yes No No information available

Appendices 112

Table I: Comparison of people component between case study countries PEOPLE COMPONENT LATIN AMERICA ASIA AFRICA VARIABLES COLOMBIA CUBA NEPAL INDONESIA NIGERIA ETHIOPIA Driving forces (data acquisition, SDI) Descriptions

Strategies that organise production / distribution of GI Cooperation between producers and users Documentation produced data and facilitation of access Improvement decision making harmonisation Harmonisation / interoperability

Mandate government

Realisation in wasting limited resources in the duplicated creation Mandate government EC assistance Drive for new public management

Synergy among all stakeholders Optimise community participation in spatial data acquisition and dissemination Good governance

Need to adopt policies greater awareness and access Launch satellite Facilitation national development and regional integration Call of UNECA ICT

UNECA

Definition of core data sets Yes / No

Yes No Yes No Yes No information available

Language Language of country Additional language (English)




Language of country (Bahasa

Indonesian)



Nr. and type of suppliers # and type

9 Government

1 Government

No information available on

numbers

3 Government

27 Government, universities,

private sector / NGOs

3 Government

Nr. and type of users # and type


numbers Institutional,

public, private


numbers Public, private,

educational sector


numbers Public, private,

educational sector


numbers


numbers


numbers

Appendices 113

Nr. of participating institutes in network #

9 24 39 3 No information available on numbers yet

3

Capacity building (information dissemination, short courses and workshops, research and facilitation) Yes / No

Yes Yes No Yes No No information available

Education (type, availability) Type and availability (good / moderate / not good)

Short course University degrees

Good availability

University degrees

Moderate availability

University degrees No good

availability

Moderate availability

University degrees No good

availability


SDI (GIS) related conferences/journals/ stakeholders Yes / No

Yes Yes No No information available

Yes No

Research (to support NSDI) Yes / No

Yes Yes No No Yes No

User satisfaction (SDI & approach) Good / moderate / not good

Moderate Not good Not good No information available


Not good

User involvement Yes / No

No No No No information available on

numbers

Yes No

Private/commercial participation Yes / No

Yes No No Yes Yes No

Awareness (spatial data, SDI concept) Good / moderate / not good

Moderate Moderate Moderate Moderate Moderate Not good

Human capital (resources) Sufficient / not sufficient

Sufficient Not sufficient Not sufficient Not sufficient Not sufficient Not sufficient

SDI culture Understanding / moderate understanding / no understanding

Moderate Moderate No understanding No information available on

numbers

Moderate No understanding

Appendices 114

Involvement professional organisations (NGOs etc.) Yes / No

No No No No information available on

numbers

Yes No

Size of user involvement Size

Not yet established

Not yet established

Not yet established


numbers


numbers

Not yet established

Willingness to share data Yes / moderate / no



numbers

Moderate No No No

Uncertainty avoidance Description







Appendices 115

Table J: Comparison of access network component between case study countries ACCESS NETWORK COMPONENT LATIN AMERICA ASIA AFRICA VARIABLES COLOMBIA CUBA NEPAL INDONESIA NIGERIA ETHIOPIA Delivery mechanism (availability, search & procedures) Yes / No

Yes Yes Yes Yes No No

Network architecture (type, telecommunications, Internet) Type of architecture

LAN inside institutions and

Internet

Central server administered

remotely by data owners

Internet/intranet based on LAN,

RAS

Interconnected metadata

servers; and additional server

as network gateway

Intention to put a high speed and high bandwidth backbone and

implement servers at nodes

Not yet established

Data volume / data sets Volume + number


4 data sets No information

available on volume

4 to 5 GB No information available

Not yet established

Not yet established

Response time Time Fast / moderate / slow

No exact information available

Slow

No exact information available Moderate

Slow Moderate to slow Not yet established

Not yet established

Nr. of visitors #


Approx. 1500 per month


Approx. 4841 per month

Not yet established

Not yet established

Nr. of web references #


More than 50 No information available


Not yet established

Not yet established

Nr. of language used #

1 1 1 1 Not yet established

Not yet established

Frequency of web updates Frequency


Every 3 months No information available


Not yet established

Not yet established

Appendices 116

Status None Project Product portal Clearinghouse

Project Product portal Product portal Clearinghouse Not yet established

Not yet established

Preview possibility Yes / No

Yes Yes No Yes Not yet established

Not yet established

Implementing body Present / not present

Present Present Present Present Not yet established

Not yet established

E-business Yes / No

No Yes No No Not yet established

Not yet established

Performance (usefulness) Good / reasonable / bad

Reasonable Reasonable Bad Moderate to bad Not yet established

Not yet established

Reliability Good / reasonable / bad

Reasonable Reasonable Bad Moderate to bad Not yet established

Not yet established

Appendices 117

Table K: Comparison of policy component between case study countries POLICY COMPONENT LATIN AMERICA ASIA AFRICA VARIABLES COLOMBIA CUBA NEPAL INDONESIA NIGERIA ETHIOPIA Executing coordinating body Yes / No → Present / not present

Present (no official

appointment)

Present Present Present Present Present

SDI directive (existence) Yes / No

No Yes Yes Yes No (in process)

No

SDI directive (freedom of info act / copyright) Yes / No

No Not yet established

No Yes No (in process)

No

Funding (source) Yes / No

Yes Yes Yes Yes No (in process)


Funding (amount) Amount


US$ 300,000 per year


EC contribution first 3 years: €

540,000


Grant expected: US$ 100.40

million

No (in process)


Funding (model) Model



Project funding Project funding Cost recovery No information available

Funding (stability) Yes / No / not likely

Not likely Yes Not likely Not likely Not likely No information available

Intellectual property Yes / No → Arranged / not arranged

Arranged No information available

Arranged Not arranged Not arranged (in process)


Privacy Yes / No → Arranged / not arranged

Not arranged No information available

Not yet established

Arranged Not arranged (in process)


Appendices 118

Pricing (data & access to services) Yes / No → Arranged / not arranged


Not yet established

Not arranged Not arranged (in process)


Institutional arrangements for suppliers/users/value-adders Yes / No → Arranged / not arranged

Arranged (for suppliers)


Not yet established


Not arranged (in process)

Not arranged

Access privileges Yes / No → Arranged / not arranged


Arranged Not arranged Not arranged (in process)

Not arranged

Legal arrangement for suppliers/users/value-adders Yes / No → Arranged / not arranged



Not yet established

Not yet established


Not arranged

Leadership (who, power) Present / not present

Not present Present Present Present Present Present

Vision (political, long-term) Yes / No

No No No Yes No No

Partnership arrangements Yes / No → Arranged / not arranged



Arranged No information available


Not arranged

Public/private partnerships Yes / No → Arranged / not arranged


Not relevant Not yet established



Data collection body Present / not present

Not present Present Present Present Present No information available

Member of regional organisation Yes / No

Yes Yes Yes Yes Yes Yes

Liability Yes / No → Arranged / not arranged







Appendices 119

Commercialization of data Yes / No → Arranged / not arranged

Arranged Not relevant Not yet established



Not arranged

Policy of preview Yes / No






Not arranged

Nature of spatial information market Large / average / small

Large No information available

Small No information available



E-government existence Yes / No

Yes Yes No Yes Yes No information available

Socio-political stability Stable / moderate / unstable

Unstable Stable

Unstable Unstable Unstable Unstable

Appendices 120

Table L: Comparison of standard component between case study countries STANDARD COMPONENT LATIN AMERICA ASIA AFRICA VARIABLES COLOMBIA CUBA NEPAL INDONESIA NIGERIA ETHIOPIA Data transfer Arranged / not arranged

Arranged Not arranged Not arranged Arranged Not arranged Not arranged

Metadata (availability) Yes / Partly / No

Yes Partly Partly Partly No Partly ENRAEMED

Type and use of metadata standard (ISO, CEN, FGDC) ISO, CEN, FGDC, other

NTC 4611 based on ISO and

FGDC

ISO FGDC FGDC ISO ISO and FGDC

Services Yes / No

Yes Yes No No information available

Not yet established

Not yet established

Interoperability Yes / No

No Yes No No No No

WMS Yes / No

No Yes No No No No

WFS Yes / No

No Yes No No No No

WPS Yes / No

No Yes No No No No

WCS Yes / No

No Yes No No No No

Appendices 121

Table M: Comparison of other component between case study countries OTHER COMPONENT LATIN AMERICA ASIA AFRICA VARIABLES COLOMBIA CUBA NEPAL INDONESIA NIGERIA ETHIOPIA SDI coverage (local, global) National / global

National National National National National National

Status Pilot Implementation Established

Implementation Implementation Pilot Implementation Pilot Pilot

Development approach (bottom-up, top-down) Bottom-up / top-down

Bottom-up Top-down Bottom-up Top-down Top-down Top-down

Decentralization / centralization Decentralization / centralization

Decentralization Centralization No information available


Decentralization No information available

Communication channels Good / acceptable / not good

Acceptable Acceptable Not good No information available



SDI's complexity Very complex / complex / not complex

Complex Not too complex No information available




Hierarchy (vertical & horizontal relationships) Vertical / horizontal / both

Both No information available



Both encouraged No information available

SDI's maturity Stand-alone stage Exchange stage Intermediary stage Network stage

Exchange stage (in between

exchange and intermediate)







Exchange stage Stand-alone stage

SDI's history (years of existence) Description

From 1995 From 1999 From 2002 From 1993 From 1997 From 2002

SDI's impact visibility Visible / in between / not visible

In between No information available



In between Not visible

Appendices 122

Initiatives connected to SDI (country’s activity) Description

GIS for land use planning with

ASDI

National Society Information Programme


Grant from Japanese

government

Actively participating in

conferences etc.


NSDI definition (goal) Description

A set of policies, standards,

organisations and technology

working together to produce,

share, and use geographic

information about Colombia in order

to support national

sustainable development

Opens the policies,

technologies, standards and

human resources needed for the

effective collection,

administration, access, delivery

and use of spatial data at national

level to take economic,

political and social decisions on sustainable development

To strengthen planning and

resource management through the

development of a geographic information

infrastructure for the access of

geographic and related data for decision-making

To make available and

accessible fundamental

datasets within the Indonesian

territory at a national standard

The collected datasets should

be put to the maximum

possible users by publicising their existence and making them

easily available to the widest possible audience


Main challenge (e.g. implementation or maintenance) Challenges

Organisational, policy, user-need,

cost-benefit

Implementation and maintenance,

organisational, funding, human

resources

Proper institutional set-

up, common standards, SDI

culture, sustainability

Recognition, commitment,

inter-institutional commitment and

creation of regulation

Funding, passage of policy into bill, capacity building


Appendices 123

Table N: Consulted SDI experts Expert # 1 Abdulharis, Rizqi ([email protected]) Former student TUD, The

Netherlands Expert # 2 Alegria, Luis ([email protected])

Rodrigo Barriga Vargas ([email protected]) Instituto Geográfico Militar – Chile

Expert # 3 Arias, Lilia Patricia ([email protected]) IGAC – Colombia Expert # 4 Borrero, Santiago ([email protected]) Instituto Panamericano de

Geografía e Historia Expert # 5 Bregt, Arnold ([email protected]) WUR, The Netherlands Expert # 6 Broucke van den, Danny

([email protected]) Leuven University – Belgium

Expert # 7 Chhatkuli, Raja Ram ([email protected]) National Geographic Information Infrastructure Programme – Nepal

Expert # 8 Crompvoets, Joep ([email protected]) WUR, The Netherlands Expert # 9 Delgado, Tatiana ([email protected]) GeoCuba – Cuba Expert # 10 Ezigbalike, Chukwudozie ([email protected])

no response UNECA, Ethiopia

Expert # 11 Georgiadou, Yola ([email protected]) ITC, The Netherlands Expert # 12 Kufoniyi, Jide ([email protected]) RECTAS – Nigeria Expert # 13 Lance, Kate ([email protected]) ITC, The Netherlands Expert # 14 Loenen van, Bastiaan ([email protected]) TUD, The Netherlands Expert # 15 Masser, Ian ([email protected]) Expert # 16 Morales, Javier ([email protected]) ITC, The Netherlands Expert # 17 Nebert, Doug ([email protected]) FGDC, USA Expert # 18 Onsrud, Harlan ([email protected])

no response University of Maine, USA

Expert # 19 Orshoven van, Jos ([email protected])

University Leuven – Belgium

Expert # 20 Puntodewo, S.S.O. ([email protected]) no response

BAKOSURTANAL – Indonesia

Expert # 21 Purnawa, Bebas ([email protected]) BAKOSURTANAL – Indonesia

Expert # 22 Rajabifard, Abbas ([email protected]) University of Melbourne,Australia

Expert # 23 Rodriguez Pabon, Orlando ([email protected])

Brunet, Lebel, Leger et Associes Inc., Canada

Expert # 24 Vries de, Walter ([email protected]) ITC, The Netherlands Expert # 25 Wehn de Montalvo, Uta ([email protected])

no response TNO, The Netherlands

Expert # 26 Zevenbergen, Jaap ([email protected]) TUD, The Netherlands

Appendices 124

Table O: Results of questionnaire SDI experts Expert # 1 2 3 4 5 6 7 8 9 11 12 13 14 15 16 17 19 21 22 23 24 26 Nr

Feasible variables per SDI component:

Data component (1) Data format + + 2 (2) Maintenance + + 2 (3) Quality + + + + + 5 (4) Updating – adding of new data + + + + 4 (5) Language (data format etc.) 0 (6) Availability digital data sets + + + + + + + + + + + + + + + 15 People component (7) Driving forces (data acquisition, SDI) + + 2 (8) Language 0 (9) Nr. and type of suppliers + + 2 (10) Nr. and type of users + + + + + 5 (11) Capacity building (information dissemination, short courses, workshops, research & facilitation)

+ + + + + + + + + + + +

+ 13

(12) Education (type, availability) + 2 (13) Research (to support NSDI) + 1 (14) User satisfaction (SDI & approach) + + 2 (15) User involvement + + + + 4 (16) Private /commercial participation + + 2 (17) Awareness (spatial data, SDI concept) + + + + + + + + 8 (18) Human capital (human resources) + + + + + + + + + 9 (19) SDI culture + + + + 4 (20) Willingness to share data + + + + + + + + + + 10 Access network (21) Delivery mechanism (availability, search & procedures) + + + + + + + + 8 (22) Response time 0 (23) Nr. of visitors 0 (24) Nr. of language used 0 (25) Preview possibility 0 (26) E-business 0 (27) Performance (usefulness) + + + + + 5

Appendices 125

(28) Reliability + + + + + + 6 Policy (29) SDI directive (existence) + + + + + 5 (30) Funding + + + + + + + + + + + + + + 14 (31) Institutional arrangements (for suppliers/users/value-adders) + + + + + + + + + 9 (32) Legal arrangement (for suppliers/users/value-adders) + + + + + 5 (33) Leadership + + + + + + + + + + + 11 (34) Vision (political, long-term) + + + + + + + + + + 10 (35) Partnership arrangements + + + + 4 (36) Public/private partnerships + + 2 (37) E-government existence + + 2 (38) Socio-political stability + + + + + + + 7 Standards (39) Data transfer + + + + + 5 (40) Metadata (availability) + + + + + + + + 8 (41) Services + + 2 (42) Interoperability + + + + + + + + + 9 Other (43) Development approach (bottom-up, top-down) + + 2 (44) Decentralization / centralization + + + 3 (45) Communication channels + + + + + 5 (46) SDI's complexity 0 (47) SDI's maturity 0 (48) SDI's impact visibility + + + + 4 (49) Initiatives connected to SDI (country’s activity) + + + + + + + + 8

towards key variables to assess national spatial data ......nebert, jos van orshoven, bebas purnawa,...

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