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DIGITAL WORKFLOWS FOR A 3D SEMANTIC REPRESENTATION OF AN ANCIENT MINING LANDSCAPE

Authors: Gerald Hiebel; Klaus Hanke;

DIGITAL WORKFLOWS FOR A 3D SEMANTIC REPRESENTATION OF AN ANCIENT MINING LANDSCAPE

Abstract

Abstract. The ancient mining landscape of Schwaz/Brixlegg in the Tyrol, Austria witnessed mining from prehistoric times to modern times creating a first order cultural landscape when it comes to one of the most important inventions in human history: the production of metal. In 1991 a part of this landscape was lost due to an enormous landslide that reshaped part of the mountain. With our work we want to propose a digital workflow to create a 3D semantic representation of this ancient mining landscape with its mining structures to preserve it for posterity. First, we define a conceptual model to integrate the data. It is based on the CIDOC CRM ontology and CRMgeo for geometric data. To transform our information sources to a formal representation of the classes and properties of the ontology we applied semantic web technologies and created a knowledge graph in RDF (Resource Description Framework). Through the CRMgeo extension coordinate information of mining features can be integrated into the RDF graph and thus related to the detailed digital elevation model that may be visualized together with the mining structures using Geoinformation systems or 3D visualization tools. The RDF network of the triple store can be queried using the SPARQL query language. We created a snapshot of mining, settlement and burial sites in the Bronze Age. The results of the query were loaded into a Geoinformation system and a visualization of known bronze age sites related to mining, settlement and burial activities was created.

Subjects by Vocabulary

Library of Congress Subject Headings: lcsh:Applied optics. Photonics lcsh:Technology lcsh:T lcsh:TA1501-1820 lcsh:TA1-2040 lcsh:Engineering (General). Civil engineering (General)

Microsoft Academic Graph classification: Geographic information system World Wide Web Semantic computing SPARQL RDF Semantic Web business.industry Cultural landscape computer.file_format Data science Geography Semantic technology business computer Information integration

ACM Computing Classification System: InformationSystems_DATABASEMANAGEMENT

CIDOC CRM, 2016. CIDOC CRM Compatible models & Collaborations, http://www.cidoc-crm.org/collaborations (9.1.2017) Dariah EU, 2016. DARIAH Backbone Thesaurus (BBT) - Definition of a model for sustainable interoperable thesauri maintenance, Produced by the Thesaurus Maintenance Working Group, VCC3, DARIAH EU, http://83.212.168.219/DariahCrete/sites/default/files/dariah_bbt _v_1.2_draft_v4.pdf (4.1.2017) Doerr, M., 2006. Semantic Problems of Thesaurus Mapping.

Journal Of Digital Information, 1(8). Retrieved from https://journals.tdl.org/jodi/index.php/jodi/article/view/31/32 (3.11.2016) ISI, 2016. Karma: A Data Integration http://www.isi.edu/integration/karma/ (3.11.2016) Le Boeuf, P. Doerr, M. Ore, CH.E. Stead. S., 2016. Definition of the CIDOC Conceptual Reference Model, http://www.cidoccrm.org/official_release_cidoc.html (6.4.2016).

Pirkl, H., 1961. Geologie des Trias-Streifens und des Schwazer Dolomits sü dlich des Inn zwischen Schwaz und Wörgl (Tirol), Jahrbuch Geol. B. A. (1961), Bd. 104. 1. Heft, (Wien 1961) Poisel R.; Roth W.; Preh A.; Tentschert E.; Angerer H., 2002: The Eiblschrofen rock falls; interpretation of monitoring results of a complex rock structure. in J. Rybar, J.

Stemberk, P. WagnerLandslides: Proceedings of the First European Conference on Landslides, Prague, Czech Republic, 24-26 June 2002, Pages 449-454 2002, ISBN 9789058093936 Schibler, J., Breitenlechner, E., Deschler-Erb, S., Goldenberg, G., Hanke, K., Hiebel, G., . . . Oeggl, K., (2011). Miners and mining in the Late Bronze Age: A multidisciplinary study from Austria. Antiquity,85(330), 1259-1278.

doi:10.1017/S0003598X00062049 (14.06.2017) W3C, 2009. SKOS Simple Knowledge Organization System Reference. https://www.w3.org/TR/2009/REC-skos-reference20090818/ (19.6.2016) W3C, 2013. SPARQL 1.1 https://www.w3.org/TR/sparql11-overview/ (9.1.2017) W3C, 2014. Resource Description http://www.w3.org/RDF/ (19.6.2016)

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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    1
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Top 10%
Average
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