publication . Conference object . 2019

Heterotoki: Non-Structured and Heterogeneous Terminology Alignment for Digital Humanities Data Producers

Lamé, M.; Pittet, P.; Federico Ponchio; Markhoff, B.; Sanfilippo, E. M.;
Open Access English
  • Published: 03 Jun 2019
  • Publisher: HAL CCSD
Abstract
International audience; In this paper, we present an online communication-driven decision support system to align terms from a dataset with terms of another dataset (standardized controlled vocabulary or not). Heterotoki differs from existing proposals in that it takes place at the interface with humans, inviting the experts to commit on their definitions, so as to either agree to validate the mapping or to propose some enrichment to the terminologies. More precisely, differently to most of existing proposals that support terminology alignment, Heterotoki sustains the negotiation of meaning thanks to semantic coordination support within its interface design. This negotiation involves domain experts having produced multiple datasets.
Subjects
free text keywords: [SHS]Humanities and Social Sciences, [INFO.INFO-WB]Computer Science [cs]/Web, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [SHS.ARCHEO]Humanities and Social Sciences/Archaeology and Prehistory, [SHS.HIST]Humanities and Social Sciences/History, Artificial intelligence, Decision support systems, Ontology, Semantics, Terminology, Digital humanities, Open data, Artificial intelligence, Decision support systems, Ontology, Semantics, Terminology, Digital humanities, Open data
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