A computational analysis of art historical linked data for assessing authoritativeness of attributions

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.

A Shape Expression approach for assessing the quality of Linked Open Data in libraries

“…Moreover, an extensible quality assessment framework which supports multiple metadata schemas describes the requirements that must be considered during the design of such software [47]. A previous computational analysis is based on art historical linked data to assess the authoritativeness of secondary sources recording artwork attributions [48].…”

Modeling Data Complexity in Public History and Cultural Heritage

“…Already the notion of the neutrality of data models is being challenged by proposals such as HICO 26 (Daquino and Tomasi 2015), 27 in order to deal explicitly with interpretation acts (hico:InterpretationAct as well as classes such as Criterion and Type) as fundamental tools for expressing provenance of semantic interpretations; similarly Mauth 28 (Daquino 2019) 29 is useful to express the authoritativeness of existing statements with explicit paternity, and to let final users become active parts of the description process.…”