1preferred supplier of quality statistics iso 19115 as the metadata standard for statistics south...
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1Preferred supplier of quality statistics
ISO 19115 as the metadata standard for Statistics South Africa
Joseph Lukhwareni, Sibongile Madonsela,Antony Cooper1, Marius Cronje, Dineo Mokhuwa,Lucas Podile, Nishan Pillay, Thanyani Maremba
and Mandla Masemula
Data Management and Information Delivery Project (DMID), Statistics South Africa
1 CSIR, South Africa. Presenting author.
ISO/TC 211 Workshop on Standards in ActionStockholm, Sweden, 8 June 2005
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Overview Background Standard Investigation Findings Implementation of ISO 19115 Development of capturing tool Principles and Benefits
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Background Statistics South Africa (Stats SA)
National Department Official statistics agency for South Africa
Vision is to be the preferred supplier of quality statistics
Data Management and Information Delivery project (DMID) Building a data warehouse for Stats SA
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DMID
Central Metadata
Repository
CaRSMetadata
Repository
Data Repository
Data Warehouse
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Current metadata situation Originating components structure and
store metadata according to different standards and procedures. This results in: Limited analysis and comparability of data Inconsistent access to and use of data Lack of consistent standard Weakness in version control Lack of or inadequate metadata Rules on archiving are inconsistent or non-
existent
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Standards investigated Metadata registries (ISO/IEC 11179) Geographic information (ISO 19115) Dublin Core Metadata Initiative
(DCMI) Data Documentation Initiative (DDI)
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ISO/IEC 11179 Information technology – Metadata registries
(MDR) Describes what a metadata registry should
contain For concepts and definition formulation Does not describe metadata per se For the developers of metadata standards Not for those who record and use metadata
Currently used by other stats agencies Australian Bureau of Statistics & Statistics Canada
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ISO 19115 Geographic information – Metadata Provide rules for extensions and profiles
Guidance on extending metadata, implementing and managing metadata
Hierarchical levels of metadata Free text elements may include multiple
instances in different languages Comprehensive dataset metadata profile Code lists used extensively to remove bias Used by geographic and non-geographic
organisations
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Dublin Core ISO 15836:2003
Information and documentation – The Dublin Core metadata element set
Focuses on data discovery Initially developed for document-like objects
(librarian) Many element refinements (qualifiers) Largely free text 15 core metadata elements
Title, Creator, Subject, Description, Publisher, Contributor, Date, Type, Format, Identifier, Source, Language, Relation, Coverage, Rights
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DDI Data Documentation Initiative (DDI) Standard for technical documentation
describing social and behavioural data Over 300 tags Largely free text Content, presentation, transport and
preservation of documentation for datasets DDI specification is written in XML Document Type Definition (DTD) and XML
Schema (XSD) v2.0 published 2003-07-15
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Implementation of ISO 19115 Decided to profile SANS 1878
South African spatial metadata standard Itself a profile of ISO 19115
Piloted Profile in Stats SA Geography (Census 2001 Enumeration
Area) Economic Statistics (Survey of
Employment and Earning) Social Statistics (Labour Force Survey)
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Implementation of ISO 19115 Pilot indicated the need to extend
the Profile for statistical elements Used examples from other
international Stats Agencies to add the extended elements
Elements were further tested at an internal workshop
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Development of capturing tool Investigate the available open source and off-
the-shelf solutions e.g. M3Cat, NESSTAR, Metamaker, Metalite,
ArcCatalog Developed evaluation criterion Recommended in-house development of tool
Interface modelled after Metalite ISO 19115-compliant metadata tool will
integrate with other systems in Stats SA e.g. CaRS, ArcCatalog, NESSTAR, etc
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Development of capturing tool
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Principles and Benefits
Principles Benefits
Data and Metadata stored in a central place
Allow improved access to data and metadata
Content structure conforms to standard
Improved analysis and comparability of data
Metadata managed with a life-cycle focus (metadata flow within the statistical process)
Metadata is more coherent and relevant across datasets
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Principles and Benefits
Principles Benefits
Metadata structure should be strongly linked to datasets
Easy to navigate between data and metadata
There will be registration process (workflow) associated with each metadata element
Results in clear ID of ownership, approval status, date of operation, i.e. accountability improves and quality of metadata improves
17Preferred supplier of quality statistics
Thank you!
Contact details:Antony CooperEmail: [email protected]: +27 12 310 8548
Joseph LukhwareniSibongile MadonselaMarius CronjeDineo MokhuwaLucas PodileNishan PillayThanyani MarembaMandla Masemula
DMID, Stats SA