FAIR data for prehistoric mining archaeology.

Area of Science:

• Archaeology
• Digital Humanities
• Data Science

Background:

• Prehistoric mining archaeology generates complex data requiring standardized documentation.
• Existing data lacks interoperability and reusability, hindering interdisciplinary research.
• The Research Centre HiMAT and the DACH project focus on prehistoric copper production in the Alps.

Purpose of the Study:

• To develop and implement a FAIR data approach for prehistoric mining archaeology.
• To transform archaeological documentation into open and reusable data.
• To leverage semantic web standards and ontologies for data integration.

Main Methods:

• Application of the FAIR data principles (Findable, Accessible, Interoperable, Re-usable).
• Utilizing the CIDOC CRM ontology and semantic web standards for metadata creation.
• Employing the DARIAH Back Bone Thesaurus for mining archaeology-specific concepts.
• Transforming data into knowledge graphs and exporting to hierarchical/tabular formats.

Main Results:

• A methodology for creating FAIR data in prehistoric mining archaeology is presented.
• Metadata are generated using CIDOC CRM and deposited with documentation in the ZENODO repository.
• Knowledge graphs facilitate the representation of sites, objects, and their relationships.

Conclusions:

• The proposed approach enhances data discoverability, accessibility, and reusability.
• Standardized metadata and semantic web technologies improve data interoperability for cultural heritage.
• This work contributes to sustainable data management in archaeological research.