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1Daquino, M.: ¬A computational analysis of art historical linked data for assessing authoritativeness of attributions.
In: Journal of the Association for Information Science and Technology. 71(2020) no.7, S.757-769.
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.
2Daquino, M. ; Peroni, S. ; Shotton, D. ; Colavizza, G. ; Ghavimi, B. ; Lauscher, A. ; Mayr, P. ; Romanello, M. ; Zumstein, P.: ¬The OpenCitations Data Model.
Abstract: A variety of schemas and ontologies are currently used for the machine-readable description of bibliographic entities and citations. This diversity, and the reuse of the same ontology terms with different nuances, generates inconsistencies in data. Adoption of a single data model would facilitate data integration tasks regardless of the data supplier or context application. In this paper we present the OpenCitations Data Model (OCDM), a generic data model for describing bibliographic entities and citations, developed using Semantic Web technologies. We also evaluate the effective reusability of OCDM according to ontology evaluation practices, mention existing users of OCDM, and discuss the use and impact of OCDM in the wider open science community.
Inhalt: Erschienen in: The Semantic Web - ISWC 2020, 19th International Semantic Web Conference, Athens, Greece, November 2-6, 2020, Proceedings, Part II. Vgl.: DOI: 10.1007/978-3-030-62466-8_28.
Themenfeld: Citation indexing