About the project

The project InfInt set out for two main goals. The use of high resolution digital elevation models together with other available information to locate hence unknown prehistoric mining sites between the researched Bronze Age mining sites of Mitterberg, Kitzbühel and Schwaz-Brixlegg. Closing these gaps and dating the mining activities allows for retelling the story of prehistoric mining in the Eastern Alps and its spread through the Alps. With the research results for the Pinzgau and the Brixental two gaps in the research landscape for prehistoric mining could be closed and you find the results in the respective sections together with the methodologies that were used.

Map of the research area Brixental (B) and Viehhofen/Glemmtal (Pinzgau) (D) and well-known prehistoric mining districts in the Tyrol and Salzburg: A: Schwaz-Brixlegg, C: Kitzbühel-Jochberg, E: Mitterberg.
Map: ESRI/R. Lamprecht.

Prehistoric mining structures identified in high resolution digital elevation models.

 

The second goal was to develop a conceptual modelling approach how to represent the information created in an archaeological campaign that was documented according to the guidelines of the Federal Monuments Office of Austria. The conceptual model was based on CIDOC CRM and extensions for archaeological excavations, scientific observation and argumentation. The research results went into the further development of the CIDOC CRM and extensions through the CRM SIG. A workflow was created to transform tabular metadata based on the  Federal Monuments Office Guidelines to the conceptual model and implement them in a knowledge graph. RDFstar and Named graphs were used to represent more complex structures like relations of stratigraphic units and the processes that created them as well as provenance and argumentation patterns. Making the knowledge graph data available in a public information system for researchers and the public was a subgoal of this task.

Conceptual modelling approach

 

The conceptual modelling, the workflow to create RDF star data, the resulting knowledge graph and the implemented information systems are available in the respective sections.