sharing experiences with mobile phone data collection in uganda flavia kyeyago ouma uganda bureau of...
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SHARING EXPERIENCES WITH MOBILE PHONE DATA
COLLECTION IN UGANDA
FLAVIA KYEYAGO OUMA
UGANDA BUREAU OF STATISTICS14th October 2015
REGIONAL WORKSHOP & CONFERENCE ON THE USE OF MOBILE TECHNOLOGIES FOR STATISTICAL PROCESSES; UNITED NATIONS CONFERENCE CENTER, ADDIS ABABA, ETHOPIA; 13-16 OCTONER 2015
CONTENTS Introduction
Pre Mobile CIS issues
Design & Methodology
Data collection and Extraction
Lessons
Benefits
Challenges
Conclusions
.
INTRODUCTION Mobile Data Collection (MDC) - use of mobile phones, tablets or PDAs for data collection.
Many platforms that can be used to design surveys to collect specific data i.e statistical
data, photographs, data from a preselection, voice recordings, GPS coordinates, etc.
Platforms vary in ease of use, cost, and features.
Some requirements that must be defined .
sample sizes, budgets, technology services
data quality requirements.
Variances in the interfaces, server side components like databases, data reporting
and management interfaces and available technology services and infrastructure
Mobile Data Collection Application Trends:
Development of Native applications installed on the data collection device
Use of USSD as the messaging framework to send the data to server via SMS
The use of the browser based software to collect and send data to an Application
server
INTRODUCTION In 2008 , GOU, started a programme called the Community
Information System (CIS) The main objective was to
collect Administrative data empower communities to make informed decisions using
readily available up to date information. The CIS was first implemented in 2009 in about 50 districts Multisectoral approach and UBOS was in charge of data
processing used paper based questionnaire and a system for data entry was developed However, there were many challenges experienced that included
technical and non technical issues that led to the exercise stalling
Pre Mobile CIS issues Infrastructure limitations no
electricity and room at Sub-counties
Limited HR for entry even at both Sub county & district level
Entry required long term employment not sustainable
Data delays and data obsolete yet wanted real time data for planning at that level
lack of integration of the data
- In 2011, the growing use of mobile phones pushed the IT team to innovate and experiment the use pf mobile phones on the CIS project
-The developed a web based solution which could be accessed through the web browsers that are native on the mobile phone
-Was done with the objective of introducing the alternative of MDC
-Reduce on some of the infrastructural limitations
Design & Methodology The Web application was designed by the IT Team at UBOS using previous
experience
This web interface is accessed through phones with web browsers.
Why Web - web is ubiquitous in nature and can be accessed by any device,
anywhere, anytime
Scope: 5 Modules with about 25 questionnaires, that included administrative
data on health, education, financial institutions, general operations
Technology and Application: mobile device phones with sim cards, Designed
using HTML5, CSS, PHP and Java Script for the front end & Mysql for the back
end.
Server was configured at UBOS § IT team monitored data transmission,
aggregation and extraction
Design & Methodology The conceptual stages involved
designing the form,
deploying the Form on the server,
deploying the form on the device,
collecting data, sending data to the server and
downloading the data from the server and analyzing the data.
the Client module - functionalities of getting blank forms from the web server to a mobile phone and also filling the forms and sending the forms to the server.
allows for setting logical question flow–thereby making non-applicable questions hidden from enumerator,
Administration Module : for data management , data reports, data exportation, data visualization
Data collection & Extraction Testing : 3 Districts (Urban/Rural)
Training : Done at the Sub county level
Staffing Enumerators – CDOs – Parish and Village
Supervisors – District Planners &
Population Officers
Supervisors – UBOS
Rolled out to date in about 12 districts
access to the application is done through the
browser, with user name & Password
Data is captured via the mobile client and
sent via the internet using mobile data
transmission technologies (edge or GSM) to a
central server at UBOS.
Once a user has filled in the questionnaire,
they are able to submit the data and get a
notification message that the data has been
submitted.
Validation is done on the phone before the
data is sent to the server.
No data is stored on the phone.
Set validation checks are programmed into the system for answers entered ( logic skips)
some data cleaning is already completed due to these features built into the system
system is real time it allows for prompt review of data quality and makes auditing much easier.
Data can be exported to different formats: CSV, Ms Excel
MCIS Project planning
Tasks Duration
Project Planning 6 months
Proof of Concept (3 districts) 3 weeks
Design & Testing by the UBOS IT team 10 weeks
Deployment and Training 5 days
Data Collection 10 days
Generate Draft Data Collection Report 2 days
Lessons Piloting and iteration are critical
Decide on the course of actions
target data collection efforts to the needs
and usage the CIS
eliminated the fears of the government
officials
Technology and Team
Composition of the team ( IT & Statisticians) .
Training and Support
4 days of In-depth training of enumerators
and supervisors (questionnaire/System/Trial )
and continuous support
.
Security
Data integrity and security
Project planning
The team should plan way in advance in
order to loose any time factors
System should be fully developed
before the actual data collection exercise
where possible
Learning curve
enumerators using the phone for data entry
For the development team
Benefits/ Results Reduced time
Faster, received in real time
of data collection impacting on presentation of findings
the combination of Data extraction and data entry Processes
Provision of real time data and improved data monitoring process
Reduced cost
reduced paper use , storage space and paper waste
More innovation which has lead to more capacity built and Adoption
More support from management, more awareness, training support
Sustainable system that can obtain data on a regular basis
.
Challenges Fears to move from PAPI to CAPI – keep adopting and improving
Lack of Policy on Mobile phone use -
Training the CDOs – slow learning curve, emphasize key point & give support
Internet Connectivity
Poor network coverage - change sim cards to the network that is available/
adding an offline mode .
Battery life
Phone batteries would not last the whole day
– charge with the local area centres and also some have backups and others
would use their phones.
using the in-built touch keypad
size of keypad especially for a very long questionnaire was seen a problem
Errors
small keys -correcting mistakes -decimal point
Data sharing to other MDAs is not yet very feasible
ConclusionsPolicy Issues
With the increasing data demands, NSOs should put in place policies that support mobile phones usage
Budgeting and planning for such projects is important
Capacity building and benchmarking should encouraged
Infrastructure issues
Network connectivity shortcomings – consider using off line platforms
Research on mobile GSM Terminals that can expand network coverage (PPPs)
Expand the use of Mobile phones to
Push for more support and collaboration from developing partners and TRIs
Do more research on the best platforms (Cross sectional and long term surveys)
Distinguish factors responsible for error rates
Measure the CBA by carrying out the same survey with both Paper & Mobile for comparison purposes
Data Management issues
Management of the full data production cycle to dissemination and archiving stages should considered
.