Enable quality assessment of open dataActive
The proliferation of open data as a mean to foster open innovation processes towards improved or new products and services, to increase transparency and to perform self-empowered impact measurement of policies is dependent upon the Data Quality (DQ) of that which is released and being re-used. In order to sustainably raise DQ, measures need to be in place all along the data pipeline and not only at the providing front end. DQ improvement has to be considered as a process rather than a one-time measure. Some initial metrics to assess Data Quality that should be taken into consideration include: accuracy, applicability, understandability, relevance, availability, timeliness and primacy.
Global Open Data Index and Open Data Barometer: Both of these tools assess data quality according to standards put forth in best practices. Government should have greater involvement in shaping these tools, through engaging to ensure their datasets are correctly assessed or participating in assessment.
Open Definition: Open Knowledge International, along with the stewards of the open movement created the open definition to capture the principles of openness. Governments could annotate their datasets according to these principles online.
How to open up data, Open Data Handbook: This resource gives recommendations and examples of how to open up data according to the principles of openness. It is a valuable resource for governments implementing open data programs.Go to website