Towards a Similarity Algorithm for Controlled Vocabularies Within the Digital Humanities

With a growing amount and increasing complexity of data and metadata in the Digital Humanities, the use of semantic tools such as controlled vocabularies and taxonomies becomes more and more important to gain new research insights. Their use enables new research possibilities by introducing machine readable semantic links and standardised data and metadata. A validation and recommender system that ensures a quick development of high quality vocabularies is essential in such a scientific workflow. The base of this system is a similarity algorithm. State of the art algorithms and editors for controlled vocabularies do not meet the special requirements of the Digital Humanities domain. Therefore, this work proposes to fill the research gap in the Digital Humanities domain with a similarity algorithm and a recommender and validation system for controlled vocabularies. The methodology and evaluation for achieving this goal as well as preliminary results are presented in this contribution.