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.
Daquino, M. (2020). A computational analysis of art historical linked data for assessing authoritativeness of attributions. JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY, 71(7), 757-769 [10.1002/asi.24301].
A computational analysis of art historical linked data for assessing authoritativeness of attributions
Daquino, Marilena
2020
Abstract
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.File | Dimensione | Formato | |
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Daquino - A computational analysis of art historical linked data for assessing.pdf
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