Linking subject labels in Cultural Heritage Metadata to MIMO vocabulary using CultuurLink

The Europeana Sounds 1 project aims to increase the amount of cultural audio content in Europeana. It also strongly focuses on enriching the metadata records that are aggregated by Europeana. To provide metadata to Europeana, Data Providers are asked to convert their records from the format and model they use internally to a specific profile of the Europeana Data Model 2 (EDM) for sound resources. These metadata include subjects, which typically use a vocabulary internal to each partner. The problem is that the values in subject fields come too often as simple literals (strings) that are specific to one (or a couple of) language(s) -the one(s) of the Data Provider. For Europeana to take full advantage of subjects from these vocabularies for purposes such as cross-lingual search, it is essential that they are connected with richer, multilingual data. A first solution to this problem is to semantically enrich metadata for individual cultural objects with links to concepts from a (multilingual) vocabulary (say, 'vocM'). Such new object-vocM links can be used to later provide more semantics and labels in multiple languages for search indexes or display functions. A second option is to perform alignment at the level of vocabularies, linking the elements of an original 1 http://www.europeanasounds.eu/

Linking Subject Labels in Cultural Heritage Metadata to MIMO Vocabulary using CultuurLink

International audienceThis paper focuses on exploring the feasibility of vocabulary alignment. This task is often deemed more successful when done manually by domain experts. However, it becomes too labour intensive for large vocabularies. Some tools have proposed a semiautomatic approach to make the task less labour-intensive yet still taking benefit from the user expertise required to assert the right alignments. We conducted an experiment with some Europeana Sounds Data Providers to use of a vocabulary alignment tool, CultuurLink4 , to identify alignments between the subject terms from local vocabulariesand a semantically richer target vocabulary