Linking entities in scientific metadata

Jian Qin, Miao Chen, Andrea Wiggins, Xiaozhong Liu

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Linked entity data in metadata records builds a foundation for the 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 for change in the scientific as well as the general metadata paradigm.

Original languageEnglish (US)
Pages (from-to)128-136
Number of pages9
JournalProceedings of the International Conference on Dublin Core and Metadata Applications
StatePublished - Dec 1 2010
Event10th International Conference on Dublin Core and Metadata Applications, DC-2010 - Pittsburgh, PA, United States
Duration: Oct 20 2010Oct 22 2010

Keywords

  • Ecological data
  • Metadata for data sets
  • Scientific metadata

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Software

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