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Modeling semantically Enhanced Digital Edition of Accounts (MEDEA) for Discovery and Comparison on the Semantic Web
- Author(s):
- Clifford Anderson, Oyvind Eide, Anna Orlowska, Katrin Pindl, Kathryn Tomasek (see profile) , Georg Vogeler
- Date:
- 2016
- Subject(s):
- Scholarly electronic publishing, Editing, History, Ontology
- Item Type:
- Article
- Tag(s):
- Accounting, CIDOC-CRM, Historical Accounting, Linked Data, Web of Data, Digital scholarly editing
- Permanent URL:
- http://dx.doi.org/10.17613/z3tv-ep21
- Abstract:
- Historical accounting documents are a genre of texts that have considerable research potential if we treat them as humanities sources. MEDEA is a cooperative international project whose principal investigators recommend creating digital scholarly editions of accounts as a first step in a process that will open the information contained within them to the affordances of the Semantic Web. MEDEA researchers are at work on a bookkeeping ontology that can be used to intermediate between XML markup and exposing Linked Open Data as RDF. The information contained in the texts of accounts can then be used to explore humanities questions at levels from the granular or local to the regional or global. This paper reflects presentations from a multi-speaker session at DH2016 in which MEDEA participants discussed the kinds of humanities information found in accounts, the forms of electronic representation available for working with them, and an evolving bookkeeping ontology based on CIDOC-CRM.
- Notes:
- This paper reflects presentations from a multi-speaker session at the 2016 Digital Humanities conference in which MEDEA participants discussed the kinds of humanities information found in accounts, the forms of electronic representation available for working with them, and an evolving bookkeeping ontology based on CIDOC-CRM.
- Metadata:
- xml
- Status:
- Published
- Last Updated:
- 4 years ago
- License:
- All Rights Reserved
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Modeling semantically Enhanced Digital Edition of Accounts (MEDEA) for Discovery and Comparison on the Semantic Web