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OVERVIEW OF ARCHIVING OF MICRODATA SILAS M. MULWA Kenya National Bureau of Statistics

OVERVIEW OF ARCHIVING OF MICRODATA SILAS M. MULWA Kenya National Bureau of Statistics United Nations Regional Seminar on Census Data Archiving for Africa Addis Ababa, 20-23 rd September 2011. OUTLINE. Definition of Micro-data Why disseminate Micro-data? Acquisition and preparation of data

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OVERVIEW OF ARCHIVING OF MICRODATA SILAS M. MULWA Kenya National Bureau of Statistics

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  1. OVERVIEW OF ARCHIVING OF MICRODATA SILAS M. MULWA Kenya National Bureau of Statistics United Nations Regional Seminar on Census Data Archiving for Africa Addis Ababa, 20-23rd September 2011

  2. OUTLINE • Definition of Micro-data • Why disseminate Micro-data? • Acquisition and preparation of data • Tools for Archiving of Micro-data • Dissemination of micro-data • Risks of disseminating microdata

  3. Definition of Micro-data Micro-data: are defined as files of records pertaining to individual respondent units (mainly through household interviews). Micro-data files for dissemination purposes may differ from those used within the KNBS; • all direct and indirect identifiers have may be removed through various anonymization processes • Micro-data as opposed to Macro-data contains records pertaining to individual firms/institutions or aggregated records at national or county levels.

  4. Why disseminate Data use? • To Broaden data use and reuse • To add value to data bringing subject matter knowledge to data analysis • To get feedback from the data users, which could be used to improve data quality and also improve data collection in the future.

  5. Why disseminate Data use? Cont’ • Foster diversity and deepen the quality of data analysis thereby extracting more information from the data. • Reduce duplication in data collection • Leveraging funding for statistics • Complying with a contractual or legal obligation e.t.c.

  6. Acquisition and preparation • Questionnaire Design and Sampling design • Data collection • Data is coded after collection • Data Capture • Draft Data is archived using tools • Data editing and derived variables created • Edited set is archived followed by anonymization

  7. Tools for Archiving of Micro-data 1.Data archiving has various components these includes; • Data documentation • Cataloguing • Data dissemination • Anonymization • Preservation. A combination of tools are required so as to construct all the components.

  8. Archiving tools cont’d KNBS has used both standard and non standard tools for data archiving. IHSN micro-data management Toolkit – It is a standard kit for documenting datasets in compliance with Data Documentation Initiative (DDI) and the Dublin Core Standards. KNBS has not used the toolkit to document census micro-data but 7 survey datasets have been documented and archived using this tool.

  9. Archiving tools cont’d NADA Is DDI standard compliant for archiving and dissemination. KNBS has not used the tool but it is building capacity on NADA Redatam – IMIS (integrated mult-sectoral information system) KNBS has used IMIS to store 1989, 1999 Census Microdata. Mainly it is used to query information and is web-based

  10. Archiving tools cont’d CSPRO and ICADE: • Not for archiving but for capturing and storage of census-data Micro-data, there is very little documentation apart from providing ASCII file structures

  11. DISEMINATION OF MICRO-DATA • Due to Technological advancement in ICT and increased demand for data, KNBS is changing the way of accessing and disseminating information to the users. • Traditionally KNBS has been using publications, seminars and workshops to release and disseminate survey and census data. • Census micro-data can be accessed and queried using IMIS.

  12. DISEMINATION OF MICRO-DATA cont’d • Offline Dissemination CDs, DVDs are used for data distribution Microdata after anonymisation process. Only 5% of Census data can be given to users on special request. • Mobile Dissemination: It was used to disseminate 2009 population census results.

  13. Risks of disseminating microdata Disclosure: • This is the risk of re-identification of particular individuals and is one of biggest challenges. • It can lead to violation of laws, lose of trust by the public and compromise quality Controversy of results: User may obtain different results from the one published by KNBS resulting to controversy and criticism

  14. END OF PRESENTATION

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