Europeana enriches its data providers’ metadata by automatically linking text strings found in the metadata to controlled terms from Linked Open dataset or vocabularies. This process of “augmenting” the source metadata with additional terms is called semantic enrichment.
The enrichment process can be summarised to two main steps:
For more details refer to the Europeana Semantic Enrichment Framework
Example of a Europeana record semantically enriched (or contextualisation) with concepts terms from DBpedia. A man building a wig on to the head of a woman on a kind of scaffolding; another woman wearing a tall wig looks on, Wellcome Trust: http://www.europeana.eu/portal/record/9200105/BibliographicResource_3000006114081.html
The Europeana Data Model (EDM) gives support for contextual resources — the so-called ‘semantic layer', including concepts from ‘value vocabularies' like thesauri, authority lists, classifications, either coming from the network of Europeana's providers or from third-party data sources. This means that data providers are strongly encouraged to include links from open and multilingual vocabularies in the metadata you send to Europeana following the EDM recommendations for metadata on contextual resources.
Europeana has developed a small tool that ‘dereferences' the URIs, i.e., that fetches all the multilingual and semantic data that are published as Linked Open Data for vocabulary concepts and other contextual resources on third-party services. Europeana currently dereferences several vocabularies from internationally established initiatives or more specific projects, which you can use as well. The vocabulary mappings to EDM and configuration files used for dereferencing are available on GitHub. If you would like to have your own Linked Open Data vocabulary dereferenced, please mention it to your Europeana contact.
The selection of of the datasets you will perform enrichment with is a crucial step to improve the quality of the enrichment or the overall metadata. We recommend to follow the following steps during your selection:
More details and examples of targets datasets and vocabularies can be found in this document.