Multisensory Data Representation
Multisensory Data Representation is a data-driven art methodology that integrates and translates datasets into experiential outputs engaging multiple sensory modalities—such as auditory, tactile, olfactory, and visual—thereby distinguishing itself from unimodal data representations by enabling richer, embodied interpretations of data through cross-sensory perceptual mapping.
27
Publications
1.1K
Citations
90
Authors
47
Institutions
Publications per year
2017–2026
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Parents
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47
Munster Technological University
Cork, Ireland
2 h-index
2 publications
68 citations

Bauhaus-Universität Weimar
Weimar, Germany
2 h-index
2 publications
68 citations
California Southern University
Chandler, United States
2 h-index
2 publications
25 citations
Universitat de Barcelona
Barcelona, Spain
2 h-index
6 publications
75 citations
University of Southern California
Los Angeles, United States
2 h-index
2 publications
25 citations

Universitat Pompeu Fabra
Barcelona, Spain
2 h-index
2 publications
25 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
2 publications
118 citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
1 h-index
3 publications
75 citations
1–8 of 47
3 publications · 40 citations
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2 publications · 27 citations
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2 publications · 109 citations
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1 publications · 110 citations
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1 publications · 106 citations
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