Linking Entities in Scientific Metadata

Linked entity data in metadata records builds a foundation for semantic web. Even though metadata records contain rich entity data, there is no linking between associated entities such as persons, datasets, projects, publications, or organizations. We conducted a small experiment using the dataset collection from the Hubbard Brook Ecosystem Study (HBES), in which we converted the entities and their relationships into RDF triples and linked the URIs contained in RDF triples to the corresponding entities in the Ecological Metadata Language (EML) records. Through the transformation program written in XML Stylesheet Language (XSL), we turned a plain EML record display into an interlinked semantic web of ecological datasets. The experiment suggests a methodological feasibility in incorporating linked entity data into metadata records. The paper also argues for the need of changing the scientific as well as general metadata paradigm. 1. Research Problem The term scientific metadata is often used to refer to the data describing the datasets collected or generated from scientific research. A large number of scientific metadata standards and conventions exist in major disciplinary fields, e.g., the Content Standards for Digital Geospatial Metadata (CSDGM