Document - Heterotoki: Non-structured and heterogeneous terminology alignment for Digital Humanities data producers

2019

Conference article Open Access

Heterotoki: Non-structured and heterogeneous terminology alignment for Digital Humanities data producers

Lame M., Pittet P., Ponchio F., Markhoff B., Sanfilippo E. M.

Artificial intelligence Decision support systems Ontology Semantics Terminology Digital humanities Open data

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.

Source: CEUR WORKSHOP PROCEEDINGS, pp. 37-48. Rome, Italy, 3 June, 2019

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BibTeX entry

@inproceedings{oai:it.cnr:prodotti:424048,
	title = {Heterotoki: Non-structured and heterogeneous terminology alignment for Digital Humanities data producers},
	author = {Lame M. and Pittet P. and Ponchio F. and Markhoff B. and Sanfilippo E.  M.},
	booktitle = {CEUR WORKSHOP PROCEEDINGS, pp. 37-48. Rome, Italy, 3 June, 2019},
	year = {2019}
}