Case: The university's CMS provides information on courses of study, teachers and timetables. Further processing of this data into semantically enriched lists and explorative navigation through the system is not planned.
Solution: Data from the various information systems of an organization is mapped to a shared schema. This makes hidden relations accessible, data more contextualized and linked. All information is available via an enterprise search App.
Findings from the project: Mapping technologies for the transformation of relational data into RDF data can also be applied to data stored in CMS. However, the automatic mapping functions are not applicable because the databases are not normalized and the relevant productive data is bundled in a few semantically meaningless tables. The relations are implemented by proprietary indexes.
BMaKE