Recent technological developments have transformed access to art and art historical resources, with increasing volumes of both general and domain-specific structured data becoming available. Graph-based datasets and semantic web technologies offer fine-grained ways to represent interpretative nuances, enabling ontologies to reflect underlying domain theories. Building on these premises, this study investigates whether art historians’ interpretative methods become discernible when their interpretations are formally modeled through their theoretical frameworks.
We developed an ontology grounded in Erwin Panofsky’s theory (Sartini et al. 2023) and applied it to descriptions drawn from four of his major works (Baroncini 2024). This modeling allowed us to assess the extent to which Panofsky explicitly addresses artworks at his proposed three levels of interpretation (pre-iconographical, iconographical, and iconological). We further analyzed how the writing style and structure of each book influence the number of artworks described and the depth of their treatment, and the relationship between cited textual sources and the periods of the artworks discussed.
The results show that Panofsky provides interpretations across all three levels in only half of the cases. The quantity and granularity of descriptions vary notably between works, and references to classical textual sources increase significantly when artworks from the 1400–1600 period are addressed.
We argue that quantitatively analysing an art historian’s interpretative practice offers new insights into the methodological impact on historiographical outcomes. In this light, structured data and semantic modeling serve not merely as technical tools but as tools of hermeneutic inquiry in art historiography.