Experiential Observations: An Ontology Pattern-Based Study on Capturing the Potential Content within Evidences of Experiences

Author:

Antonini Alessio1ORCID,Adamou Alessandro2ORCID,Suárez-Figueroa Mari Carmen3ORCID,Benatti Francesca1ORCID

Affiliation:

1. The Open University

2. Max Planck Institute for Art History

3. Universidad Politécnica de Madrid

Abstract

Modelling the knowledge behind human experiences is a complex process: it should take into account, among others, the activities performed, human observations and the documentation of the evidence. To represent this knowledge in a declarative way means to support data interoperability in the context of cultural heritage artefacts, as linked datasets on experience documentation have started to appear. With this objective in mind, we describe a study based on an ontology design pattern for modelling experiences through observations, which are considered indirect evidence of a mental process (i.e., the experience). This pattern highlights the structural differences between types of experiential documentation, such as diaries and social media, providing a guideline for the comparability between different domains and for supporting the construction of heterogeneous datasets based on an epistemic compatibility. We have performed not only a formal evaluation over the pattern but also an assessment through a series of case studies. This approach includes (a) the analysis of interoperability among two case studies (reading through social media and historical sources); (b) the development of an ontology for collecting evidences of reading, which reuses the proposed pattern; and (c) the inspection of experience in humanities datasets.

Funder

Reading Europe—Advanced Data Investigation Tool

JPI Cultural Heritage

European Union Horizon 2020 Research and Innovation programme

Arts and Humanities Research Council

Agencia Estatal de Investigación del MINECO y Fondos FEDER

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Information Systems,Conservation

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