CHAS: evaluating and analysing cultural heritage collections in one go
Collections of cultural heritage institutions are often formed over prolonged periods of time. Methods, norms and standards used for describing collections are therefore often heterogenous, within and between institutions. Consequently, it is difficult for curators and audiences at large to evaluate and assess cultural heritage collections. Questions like what is the gender division of artists within a collection, or in which time periods a collection was formed, are difficult to answer. Evaluating whether metadata contains contentious terms or references to outdated vocabularies is altogether out of scope.
To remedy this we propose the CHAS pipeline (Cultural Heritage ASsessor). CHAS first converts key fields from collection metadata to linked data using the Europeana Data Model's main contextual classes, and uploads it to the Dutch Cultural Heritage Agency triplestore. A sequence of federated queries aims to connect the collection to reference datasets like thesauri, and (historical) gazetteers. A Jupyter notebook then uses these queries to generate a collection report. This report provides statistics about the quality of the collection metadata, such as how many fields could be mapped to reference data. It also gives key insights such as its gender division, geographical distribution, the use of contested terms, and the potential to map keywords to thesauri. CHAS will enable cultural heritage institutions, or session participants, to easily evaluate their collections, and use this information to better inform their audience. Because of the quality metrics CHAS also promotes further standardisation and accessibility of cultural heritage data. Join to learn more.
