Supply & Quality of Data

[tgherzog]

Tim needs to talk to Will to get a structure for this.

[tgherzog]

Here is the existing text with notes:

• Data Quality Standards
  Basic Examples:
  • World Bank Microdata Practices & Tools -- Methodologies for microdata
  • United Nations List of Statistical Standards *-- a catalog of a) statistical classifications, b) definitions & concepts, and c) methodologies and procedures
  • IHSN Microdata Management Toolkit -- this is Nesstar: a software tool
  • NADA -- this is a software tool
  • Data Documentation Initiative -- this is a metadata standard
• Useful tools to review, refine, clean, analyze, visualize and publish data -- lots of cool data wrangling tools: scraper wiki, python, R, that lot
• Data Portal Quick-Setup Guides by data.gov.uk -- pertains generally to how datasets are managed and administered within a portal
• Manual for statistical disclosure control (data anonymization) for microdata -- anonymization of statistics
• Software plus manual for data anonimization of table data -- looks like it duplicates the previous bullet
• World Economic Forum study 'Rethinking Personal Data: Strengthening Trust'
• Anonymization Guide from the UK's Information Commissioner's Office -- anonymization of data generally (not just statistics)
• Primer on Machine Readability for Online Documents and Data -- this is more apropo in Open Data Defined, so I put a link there

[tgherzog]

Here are some relevant links from http://data.worldbank.org:

• Data Overview
• International System
• Methodologies
• Principles Governing Our Statistical Data - based on UN's Good Practices on National Official Statistics and Principles Governing International Statistical Activities

Data Quality & Effectiveness

http://data.worldbank.org/about/data-overview/data-quality-and-effectiveness

General Data Dissemination System (GDDS)

The GDDS is a framework for assessing national statistical systems and promoting improved dissemination and effectiveness that has been developed by the International Monetary Fund (IMF), in close collaboration with the World Bank. It (i) encourages countries to improve the quality of official statistics; (ii) provides a framework for evaluating need for data improvement and setting priorities for statistical development; and (iii) guides participating countries in the public dissemination of comprehensive, timely, accessible and reliable economic, financial and socio-demographic statistics.

Data Quality Assessment Framework (DQAF)

The DQAF has been developed by the IMF, in collaboration with the World Bank, as a methodology for assessing data quality that brings together best practices and internationally accepted concepts and definitions in statistics, including those of the United Nations Fundamental Principles of Official Statistics and the GDDS. It facilitates a comprehensive view of data quality, one that recognizes interrelations, including tradeoffs, among elements of quality and allows emphases to vary across data categories and uses/users.

[tgherzog]

Suggestions from Amparo

• Guidance for non-Stats data
• Metadata - standards, etc
• Anonymization
• Standards, by data type:
  • contracting
  • budget data
  • Geospatial
• How to select data (which fruits are low-hanging)?
  • Link to country pages from WDI, UN, etc

[lindaklinger]

Tim, let's discuss how you'd like to proceed with this.

[lindaklinger]

Finished with first round of edits for Intro, General Standards, Data Standards, Contracts, Budget, Transport, Aid, and Microdata. Questions: 1. Is the Budget transition statement (before the bullets) accurate? 2. Two questions re: Transport are bracketed with asterisks in text. 3. Suggest you review Microdata for accuracy, although I did not find it opaque. 4. Why is Geospatial in such large font -- shouldn't this be a second-level head?

[tgherzog]

Thanks. I've reviewed the sections you've added and made some changes and additions. The focus of each of these sections should be available guidance and standards for producing data, not so much the objectives and goals of the organizations themselves.

[lindaklinger]

Reviewed and edited National Accounts, Geospatial, Metadata, Data Governance, and Anonymization (Microdata was already edited, but I reviewed all sections again and did make very minor refinements and corrections to a few). Looks good. Highlighted a question for you in Governance, Project Open Data: Does "non-open" data mean "close" data?

[tgherzog]

I'll try to clarify the language summarizing the implementation guide.

@lindaklinger - from now on, can you please mark editorial comments using simple italics, i.e., bracketed with underscores or single asterisks. This makes them easier to find. Brackets or question marks are inconsistent. Italics, on the other hand, show up as bright yellow in the toolkit. Thanks.