This paper discusses promises and pitfalls of linking historical data on cultural events. Events play a key role in historical scholarship, and have gained even more urgency with the increasing importance of digital humanities. Many such projects on events, however, employ them as devices to structure data collections and do not explicitly aim to develop analytical frameworks in relation to data collection and modeling. In this paper, we discuss the conceptual and practical requirements for such a framework on the basis of pilot projects on Dutch cinematic, musical, and theatrical events across the period 1600-2000.
A systematic analysis of cultural events requires a data structure that allows for querying the connections between people, places, time, genres, titles etc.. Many datasets on historical European music, theatre, and film are now publicly available online. The ones that contain programming information are, at least to some extent, already event-based. In theory they invite researchers to systematically analyze historical cultural life internationally, cross-sectorally, and within broader local contexts. However, developing a data model that allows for analyses across time, place, and cultural activities across different data sets is highly complex. The data are heterogeneous in scale and scope, and normalizing across datasets is tricky.
Harmonizing and linking all the relevant datasets is therefore impossible, but fortunately the structure of linked data provides a way to query heterogeneous data without enforcing an overarching ontology. Moreover, for comparative and cross-sectoral research, the event data can be linked internally as well as to external knowledge bases by means of shared vocabularies. We further demonstrate that conceptualizing cultural events such as concerts or theatrical performances in a linked data framework is not just a technical solution. This approach acknowledges the performative and interactive nature of cultural products and activities within their broader historical contexts.