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Best practices/Enable quality assessment of open data
Share-PSI 2.0 Best Practice
Source:
- Best Practices/Open Data quality assessment
- Minutes of the discussion How good is good enough?
- Best Practices/Using Business Process Paradigm For Open Data Lifecycle Management
Contents
Outline of the best practice
The goal is to improve the trust in government by enabling quality assessment and/or providing evidence about the quality of the published information (data)
Management summary
Challenge
Understand what is required in terms of data quality and define a set of basic and measurable metrics to determine data quality in an objective way.
Solution
Implement a dataset publication pipeline that besides the original data publish also quality assessment data. The data can be published following the 5 star model. Quality check is applied for the final data (that is published), but also for the process of publishing the data (see Best Practices/Using Business Process Paradigm For Open Data Lifecycle Management).
Best Practice identification
Why is this a Best Practice? What’s the impact of the Best Practice
As a results of this practice, re-users will trust the published data and will not need quality assessment services on consumers side.
Links to the PSI Directive
Why is there a need for this Best Practice?
To support re-use, creation of commercial services, opening new jobs, etc.
What do you need for this Best Practice?
- tools for quality assessment
- tools for checking the quality of the publication process
- open data certificates, see e.g. the ODI approach
Applicability by other Member States
The Open Data Institute suggests that publishers certifies the data they publish e.g. check their open data against the ODC questionnaire (for more info about the approach, click here). The approach is applicable across Europe, see the list of certified datasets.
Contact info
- For editorial issues: valentina.janev@institutepupin.com