Capturing the semantics of smell: The Odeuropa data model for olfactory heritage information

Lisena, Pasquale; Schwabe, Daniel; van Erp, Marieke; Troncy, Raphaël; Tullett, William; Leemans, Inger; Marx, Lizzie; Ehrich, Sofia Colette

ESWC 2022, Extended Semantic Web Conference, May 29-June 2, 2022, Hersonissos, Greece / Also published in LNCS, Vol. 13261

Best Resource Paper Award

Smells are a key sensory experience. They are part of a multibillion euro industry and gaining traction in different research fields such as museology, art, history, and digital humanities. Until now, a semantic model for describing smells and their associated experiences was lacking. In this paper, we present the Odeuropa data model for olfactory heritage information. The model has been developed in collaboration with olfactory

and art historians. Our model can express the various stages in a smell's lifetime { creation, being experienced, deodorisation { and their relation to locations, times and the agents that interact with them.

Detail

Document

DOI

BIBTEX

Type:

Conference

City:

Hersonissos

Date:

2022-05-29

Department:

Data Science

Eurecom Ref:

6856

© Springer. Personal use of this material is permitted. The definitive version of this paper was published in ESWC 2022, Extended Semantic Web Conference, May 29-June 2, 2022, Hersonissos, Greece / Also published in LNCS, Vol. 13261 and is available at : https://doi.org/10.1007/978-3-031-06981-9_23