An approach to model archaeological data and create RDF from spreadsheets

Gerald Hiebel presents an approach to create RDF data that uses Excel spreadsheets for data entry, a Postgres database for data transformations and semantic tools, like Karma or OntoRefine, for RDF creation. For Thesaurus creation, mind mapping software has additionally been used to ease the creation of a hierarchical structure of terms. The entire approach was executed with data from the project “Prehistoric Copper Production in the Eastern and Central Alps” by the research centre HIMAT (History of Mining Activities in Tyrol and adjacent areas) of the Archaeological Department of the University of Innsbruck. The data were collected during several scientific research campaigns and are related to prehistoric mining activities in the eastern Alps of Austria. The documentations were done according to the guidelines of the Austrian Federal Monuments Office (BDA – Bundesdenkmalamt). As the data are of archaeological nature, the methodologies and guidelines of ARIADNE (Advanced Research Infrastructure for Archaeological Data Networking in Europe) were already used to process the data for making them FAIR.

For the creation of the metadata for all generated and deposited files and research documents, the CIDOC CRM ontology with its extension CRMsci and CRMarchaeo were used. CRMsci was used to model physical things and scientific observations and CRMarchaeo to model the documentation of archaeological excavations. Concepts specific to Mining Archaeology research are organised with the DARIAH Back Bone Thesaurus (https://www.backbonethesaurus.eu/), a model for sustainable interoperable thesauri maintenance, developed in the European Union Digital Research Infrastructure for the Arts and Humanities (DARIAH). SKOS (Simple Knowledge Organization System) was used to organise our vocabularies, another semantic web standard for sharing and linking knowledge organisation systems such as thesauri, taxonomies, classification schemes and subject heading systems. In a further step to use the created data for aggregation in ARIADNE it was necessary to map the concepts used in the research data to the concepts of the Getty AAT (https://www.getty.edu/research/tools/vocabularies/aat/) and PeriodO (https://perio.do).