Towards a Benchmark Dataset for the Digital Humanities

Applications of ontology matching such as ontology engineering, information sharing or query answering are of growing importance in the field of Digital Humanities (DH). To gain knowledge about suitable ontology matching tools for DH research, a successful evaluation of these is crucial. Unfortunately, there exist no reference alignment datasets that address DH-specific requirements such as support of multiple (historic) languages, domain-specific terms and an easily applicable data format. Therefore, we propose the creation of a dataset as base for a future DH OAEI track which uses knowledge bases and expert surveys as reference alignment sources. Using surveys leads to a graduated scale of term similarity and association, which makes advanced evaluation metrics possible.