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A computational analysis of art historical linked data for assessing authoritativeness of attributions
Author(s) -
Daquino Marilena
Publication year - 2020
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.24301
Subject(s) - attribution , ranking (information retrieval) , computer science , ontology , field (mathematics) , the arts , information retrieval , data science , quality (philosophy) , process (computing) , psychology , epistemology , social psychology , philosophy , mathematics , political science , pure mathematics , law , operating system
In this article a comparative analysis of art historical linked open data are presented. The result of the analysis is a conceptual framework of Information Quality (IQ) measures designed for validating contradictory sources of attribution on the basis of a documentary, evidence‐based approach. The aim is to develop an ontology‐based ranking model for recommending artwork attributions and support historians and catalogers' decision‐making process. The conceptual framework was evaluated by means of a user study and the evaluation of a web application leveraging the aforementioned ranking model. The results of the survey demonstrate that the findings satisfy users' expectations and are potentially applicable to other types of information in the arts and humanities field.