Best Practices/Open Data quality assessment

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Title

Open Data Quaity assessment

Short Description

There needs to be a (standard) way for measuring the published dataset quality

Why

A plan is essential in order to offer to reusers information about a dataset quality without them to make several checks in order to know if they can trust the information. Publishers need to know what quality dimension can they improve in order to take targeted actions on the single dataset publication pipeline

Intended Outcome

Users are able to trust/not trust dataset based on the quality assessment trhough metrics. Publishers understand what is required in terms of data quality, can identify the quality problems and solve them with the final scope of publishing high quality datasets

Possible Approach

Define a set of basic and measurable metrics to determine data quality in an objective way. (By now the most important, idetified in Timisoara, are (in order of importance): availability, processability, accuracy, timeliness and completeness )

How to Test

With quantitative, possibly standard metrics

Evidence

Quality assessment on OpenCoesione data, presentaiton in Samos: http://www.w3.org/2013/share-psi/workshop/samos/OpenCoesioneMonithon

Paper presented in Timisoara: https://www.w3.org/2013/share-psi/wiki/images/3/3e/AMI_proposal_Share-PSI_Timisoara_How_good_is_good_enough.pdf

Life Cycle Stage

Publishing

Tags

Open Data Quality

Status

Draft

Intended Audience

Related Best Practices

Best Practices/Feedback to Improve Quality .