Data staR: Bridging XML and owl in science metadata management

Abstract

DataStaR is a science data "staging repository" developed by Albert R. Mann Library at Cornell University that produces semantic metadata while enabling the publication of data sets and accompanying metadata to discipline-specific data centers or to Cornell's institutional repository. DataStaR, which employs OWL and RDF in its metadata store, serves as a Web-based platform for production and management of metadata and aims to reduce redundant manual input by reusing named ontology individuals. A key requirement of DataStaR is the ability to produce metadata records conforming to existing XML schemas that have been adopted by scientific communities. To facilitate this, DataStaR integrates ontologies that directly reflect XML schemas, generates HTML editing forms, and "lowers" ontology axioms into XML documents compliant with existing schemas. This paper describes our approach and implementation, and discusses the challenges involved. © 2009 Springer-Verlag Berlin Heidelberg.