1. ISO 19115 as the metadata standard for Statistics South Africa
ISO/TC 211 Workshop on Standards in Action
Stockholm, Sweden, 8 June 2005
ISO 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.

2. Overview Background Standard Investigation Findings
Implementation of ISO 19115
Development of capturing tool
Principles and Benefits

3. 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

4. Policies and Standards
DMID
Data Warehouse
Policies and Standards
Data
Repository
Central
Metadata
Repository
CaRS
Metadata
Repository

5. 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

6. Standards investigated
Metadata registries (ISO/IEC 11179)
Geographic information (ISO 19115)
Dublin Core Metadata Initiative (DCMI)
Data Documentation Initiative (DDI)

7. 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

8. 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

9. Dublin Core ISO 15836:2003 Focuses on data discovery
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

10. 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

11. 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)

12. 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

13. 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 compliant metadata tool will integrate with other systems in Stats SA
e.g. CaRS, ArcCatalog, NESSTAR, etc

14. Development of capturing tool

15. Principles and 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

16. Principles and 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

17. Thank you! Contact details: Antony Cooper
Joseph Lukhwareni
Sibongile Madonsela
Marius Cronje
Dineo Mokhuwa
Lucas Podile
Nishan Pillay
Thanyani Maremba
Mandla Masemula DMID, Stats SA
Thank you!
Contact details:
Antony Cooper
Phone: