The purpose of the workshop is twofold: on the one hand, to gather original research work about both application and theoretical issues emerging in the elaboration of conceptual models, ontologies, and Semantic Web technologies for the Digital Humanities (DH) and, on the other hand, to collect studies on the philosophical and social impact of such models.

Concerning the former aim, a plethora of heterogeneous and multi-format data – including 3D models, photos, audio records, and documents on paper – is currently available in the Digital Humanities domain. Such huge amount of information, retrieved from different sources and contexts, disseminated in different and often isolated places, asks for principled methodologies and technologies to semantically characterize and possibly integrate data and data models for analysis, visualization, retrieval, and other purposes. Moreover, dedicated automated reasoning tools allow one to prove the consistency of conceptual models and to extract implicit information present in data to gain a deeper knowledge of the application domain at stake. Hence, research efforts towards the application or use of reasoning engines is of vital relevance.

With respect to the second aim, the workshop welcomes contributions that look at ontologies and conceptual models for the Digital Humanities from a broader philosophical or sociological perspective and contextualize them within the debate on digital technologies or models in philosophy or science and technology studies (STS). The contributions are expected to analyze ontologies and conceptual models for the Digital Humanities, i.e., to shed some light on the (social, economic, political, etc.) interests that drive the development and adoption of computer models in the Digital Humanities and the impact on the involved stakeholders and society at large.

The complementary character of these two kinds of contributions should allow both modelers and users to be more aware of the modeling choices behind models and applications and of the theories that constitute the background of such choices. This would enhance transparency and reliability of the adopted models and thus understanding and trust on the side of stakeholders and users.