In distributed systems literature the orthogonal but interdependent characteristics of autonomy, distribution and heterogeneity are used to classify distributed systems. From a holistic perspective on the arts and humanities, collections have evolved over decades or centuries from highly autonomous disciplines and institutions and are widely spread, which resulted in heterogeneous perspectives and data models. Despite its negative notion as data integration problem, the term heterogeneity also symbolizes the diversity of research methodologies within the disciplines of the arts and humanities. Resolving heterogeneity hence implies an abstraction from the specifics that are valuable for focused disciplinary and interdisciplinary research projects.
Our approach presents a novel concept for data federation in the arts and humanities, which focuses the needs of research projects as well as interdisciplinary and broad use-cases. We especially address the reusability of explicated knowledge on correlations between schemata and digital collections and show where domain experts are required to bridge semantic gaps.