Can I believe what I see? Data visualization and trust in the humanities
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In: Interdisciplinary Science Reviews, Vol. 46, No. 4, 10.2021, p. 522-546.
Research output: Journal contributions › Journal articles › Research › peer-review
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TY - JOUR
T1 - Can I believe what I see? Data visualization and trust in the humanities
AU - Boyd Davis, Stephen
AU - Vane, Olivia
AU - Kräutli, Florian
PY - 2021/10
Y1 - 2021/10
N2 - Questions of trust are increasingly important in relation to data and its use. The authors focus on humanities data and its visualization, through analysis of their own recent projects with museums, archives and libraries internationally. Their account connects the specifics of hands-on digital humanities work to larger epistemological questions. They discuss the sources of potential mistrust, and examine how different expectations and assumptions emerge depending on the use and user of the data; they offer a simple schema through which the implications may be traced. It is argued that vital issues of trust can be engaged with through design, which, rather than being conceived as a cosmetic finish, is seen as contributing insights and questions that affect the whole process. The article concludes with recommendations intended to be useful in both theory and practice.
AB - Questions of trust are increasingly important in relation to data and its use. The authors focus on humanities data and its visualization, through analysis of their own recent projects with museums, archives and libraries internationally. Their account connects the specifics of hands-on digital humanities work to larger epistemological questions. They discuss the sources of potential mistrust, and examine how different expectations and assumptions emerge depending on the use and user of the data; they offer a simple schema through which the implications may be traced. It is argued that vital issues of trust can be engaged with through design, which, rather than being conceived as a cosmetic finish, is seen as contributing insights and questions that affect the whole process. The article concludes with recommendations intended to be useful in both theory and practice.
KW - bias
KW - certainty
KW - classification
KW - critical design
KW - Data visualization
KW - ethics
KW - GLAM
KW - interdisciplinarity
KW - interrogability
KW - naming
KW - omission
KW - precision
KW - scepticism
KW - Philosophy
UR - http://www.scopus.com/inward/record.url?scp=85117111211&partnerID=8YFLogxK
U2 - 10.1080/03080188.2021.1872874
DO - 10.1080/03080188.2021.1872874
M3 - Journal articles
AN - SCOPUS:85117111211
VL - 46
SP - 522
EP - 546
JO - Interdisciplinary Science Reviews
JF - Interdisciplinary Science Reviews
SN - 0308-0188
IS - 4
ER -