FAIRification and Mapping of Controlled Vocabularies for the Preservation and Maintenance of Cultural Heritage
Description
In conservation science and heritage management, the inconsistent use of domain-specific terminology leads to significant problems in research data management. A community survey on research data management in conservation science [1] shows that only 27.5% of respondents use controlled vocabularies, and these remain primarily internally. A German-language, machine-readable, and openly accessible specialized vocabulary for archaeological conservation has been completely lacking until now. In heritage management authorities, controlled vocabularies are used 94.3% of the time, but these are predominantly internal. [2]
The TRAIL addresses these gaps by integrating the “SKOSified” specialized thesaurus for conservation from LEIZA [3] as well as, as an example, a thesaurus of dating periods based on the timeline of the GDKE [4] into the central vocabulary service DANTE. The prototype of a web application (“conserFAIRy”) [5] developed as part of the “SKOSification” process, which provides researchers with a low-threshold entry point for modeling their subject vocabularies according to SKOS, is to be further developed. During the duration of the TRAIL, the Cocoda software will be used to perform exemplary mappings to additional vocabularies. In doing so, fundamental methodological questions regarding domain-specific mapping will be examined: Are existing mapping properties sufficient? Can AI technologies and statistical methods support the mapping process? How can mapping decisions be documented transparently? To illustrate the benefits of controlled vocabularies, we will demonstrate the algorithmic processing of data using specialized vocabularies.
The TRAIL thus provides twofold added value: First, it provides a machine-readable specialised vocabulary for conservation that can be used directly via the DANTE API to describe restoration entities in internal data entry forms. This leads, on the one hand, to improved quality through consistent terminology use and the avoidance of typos, while simultaneously enhancing the discoverability and automatic processing of conservation research data in accordance with the FAIR principles. Second, reusable workflows and best-practice examples from the fields of heritage management and conservation are created, which can serve as blueprints for the entire community. The workflows address the development of FAIR vocabularies and their integration into central vocabulary servers, their use for tagging entities, as well as mapping to other controlled vocabularies.
[1] Fischer, K., & Witt, N. (2025). Zusammenfassung des Status Quo im Forschungsdatenmanagement für den Bereich der Konservierung-Restaurierung (Version v1). Zenodo. https://doi.org/10.5281/zenodo.17475354
[2] Puhl, A., Lefeldt, J., & Preiß, J. (2025). Fundstellen- und Denkmaldatenstandards in Deutschland. Whitepaper zur Umfrage (Arbeitstitel). (In Arbeit). Erste Ergebnisse sind als Poster veröffentlicht: Puhl, A., Lefeldt, J., & Preiß, J. (2025). Fundstellen- und Denkmaldatenstandards in Deutschland: Erste Eindrücke einer Umfrage. NFDI4Objects Community Meeting 2025, Bochum. Zenodo. https://doi.org/10.5281/zenodo.17143220.
[3] Fischer, K., & Lasse Mempel-Länger. (2025, September 25). Restaurierungswissen digital vernetzen - Von textlichen Dokumentationen zu maschinenlesbaren Begriffen. FORGE 2025 - Daten neu denken (FORGE 2025), Rostock. Zenodo.
https://doi.org/10.5281/zenodo.17202284
[4] Wilbertz, M., Göldner, R., VLAK-AIS (2014). Der „Zeitstrahl“ – Archäologische Datierungen in Deutschland“. Online: https://www.landesarchaeologien.de/fileadmin/mediamanager/004-Kommissionen/Archaeologie-und-Informationssysteme/Thesauri/Zeitstrahl_V01.pdf [abgerufen am 27.10.2025].
[5] FAIRifizierungsanwendung für Konservierungs- und Restaurierungsprozesse https://www.nfdi4objects.net/portal/services/fairifizierungsanwendung-für-konservierungs-und-restaurierungsprozesse/ [abgerufen am 29.10.2025].