Explicating knowledge on data models through domain specific languages

Abstract

Digital artifacts and metadata of the arts and humanities exhibit a wide spectrum of formats, structures and contexts, and hence a high level of heterogeneity. With particular respect of the characteristics of the application domain, we propose a concept on the basis of formal languages, which allows the separation of technical and contextual aspects of data modeling. Based on a developed framework, domain experts explicate knowledge about data in terms of domain specific languages and derived transformation functions. Independent of actual technical aspects of data transformation and integration (e.g. formats, access protocols, schema languages), experts of particular disciplines, collections or research questions can describe and define data models and relations in an extensive, declarative fashion—utilizing custom data models or standards as applicable. As implicit knowledge is continuously explicated within the data models, interpretations external to the generative context of data are facilitated—thereby promoting interoperability.