Open Data Policy Guidelines » Guideline 28
Create processes to ensure data quality
Data quality will not be ensured through data release alone: efforts need to be made to keep the data up-to-date, accurate, and accessible. Data release should be approached as an iterative and ongoing process. As soon as sensitive information and security concerns are met, data should be released and regularly updated as it improves and grows. Data with serious accuracy and quality concerns should be adequately documented to avoid creating confusion or misinformation. Similarly, public data reporting streams separate from what's used within government should be avoided whenever possible, as redundant or parallel data streams create opportunities for data quality to falter. Each update should include clear and complete metadata (including a conspicuous contact person), group datasets where appropriate, and address concerns noted via a prominent feedback mechanism.
- New York: Open NY One Year Report, 2014
- Oakland: Toward Collaborative Transparency, 2014
- Chicago: Open Data Annual Report, 2013
- Philadelphia: New Opportunities for Data Publishing, 2013
- New York City: Digital Leadership Roadmap, 2013
Examples of language for this guideline:
Here are examples of the language for this guideline as included in policies on this site. Please note that the selections of text below are imperfect, and you should check out their source policies to read them in context.