Domain question-driven Linked Data modeling The case study of iconological studies

Currently, there is an increasing interest in experimenting with applications of computer science to humanistic disciplines. Although some domains successfully integrated some digital tools and techniques into their methods, other domains had a slower, narrower integration. This paper addresses the challenge of experimenting with the translation of qualitative research into a quantitative one by presenting the experience of the creation of a domain-specific Linked Open Data (LOD) dataset of iconographic and iconological art studies, namely, the Iconology Dataset. The peculiarity of the process adopted lies in its strong grounding in the theoretical framework of the domain, as it followed an ontological modeling according to the key theories proposed and a modeling and analysis through the scholars’ key research questions. For the sake of enhancing the transfer of the approach to other studies, we refined it in 5 phases and presented a general description of them. Due to its characteristics of lack of formalization and interdisciplinary nature, we argue that the approach developed for the iconographical-iconological research field can be relevant for the methodological transfer to other domains.