Creating lightweight ontologies for dataset description practical applications in a cross-domain research data management workflow

Abstract

The description of data is a central task in research data management. Describing datasets requires deep knowledge of both the data and the data creation process to ensure adequate capture of their meaning and context. Metadata schemas are usually followed in resource description to enforce comprehensiveness and interoperability, but they can be hard to understand and adopt by researchers. We propose to address data description using ontologies, which can evolve easily, express semantics at different granularity levels and be directly used in system development. Considering that existing ontologies are often hard to use in a crossdomain research data management environment, we present an approach for creating lightweight ontologies to describe research data. We illustrate our process with two ontologies, and then use them as configuration parameters for Dendro, a software platform for research data management currently being developed at the University of Porto.