OPEN DATA QUALITY
Like any other data-based offering, open data wins or loses, according to quality criteria, such as accuracy, completeness, consistency, and actuality. These criteria have to be met by the actual data, the datasets, the descriptive data, as well as the metadata. Additionally, Open Data credibility and transparency are crucial in order for Open Data to be trustworthy. Origin, originality, and data changes must be traceable and quality features testable.
Fraunhofer FOKUS is also working on automated approaches for dynamized checksums, the tracing of data transformations, as well as verification via guidelines, metrics and sampling. For this, the results from XMeld, XPlanung and HL7 will be used contextually. Furthermore, the link between the “influence of users groups” and “data quality” will be explored. For that testing and adjustment processes between public administration and user groups have to be examined.
The usability of data offered by enterprises, institutions and citizens is correlated to its actuality. In particular, we will evaluate methods to identify outdated data and enable us to assess its relevance (e.g., when compared to up-to-date data arising from information found via the World Wide Web).