Conservation Data Framework

Description

[ ] The Conservation Data Framework (CDF) is an open reference framework for the standardized collection and curation of conservation data. It combines a metadata schema with a controlled metadata vocabulary and a formal application ontology. This ontology translates conservation processes, materials, methods, and stakeholders into a consistent semantic model. As a flexibly adaptable framework, the Conservation Data Framework helps specialists make their data usable, interoperable, and citable over the long term.

The Framework supports the modeling of various types of conservation information regardless of the discipline (archaeology, paintings, textiles, historic building conservation/architecture, leather, etc.), including condition reports, analytical investigations, intervention records, tools and substances used as well as decision-making processes. In practice, this information is often fragmented across free-text reports, tables, or proprietary files. The Conservation Data Framework provides a common reference system that allows such data to be systematically structured, uniquely referenced, and linked together. Technically, the framework is based on open standards and established representation formats of the Semantic Web.

Users of the framework typically begin by entering conservation documentation in a structured manner within a form or application context, as demonstrated in the Conservation Documentation Mockup Page. As data is entered, technical terms from linked standard vocabularies are suggested, enabling data values related to materials, interventions, tools, and conditions to be uniquely identified and semantically linked. The resulting datasets can then be exported, integrated into other institutional systems, or published publicly. This enables cross-site analyses, comparative studies, and the aggregation of conservation information across collections, projects, and time periods. The particular added value of the Conservation Data Framework lies in the close integration of domain-specific modeling and formal knowledge representation within an open and collaboratively maintained framework. It not only enables structured documentation but also creates the conditions for sustainable data integration and the connectivity of conservation to higher-level infrastructures.