Full Paper

Linking Entities in Scientific Metadata

  • Jian Qin 1
  • Miao Chen 2
  • Xiaozhong Liu 2
  • Andrea Kathleen Wiggins 2
  • 1 Syracuse University
  • 2 Syracuse University, United States
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Open access CC BY 4.0
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Abstract

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.

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Article details

Published
Section
Full Papers
DOI
10.23106/dcmi.952109855
License
CC BY 4.0 · open access

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dcterms:title
Linking Entities in Scientific Metadata
dcterms:creator
Qin, Jian
Chen, Miao
Liu, Xiaozhong
Wiggins, Andrea Kathleen
dcterms:date
2010-09-20
dcterms:identifier
doi:10.23106/dcmi.952109855
dcterms:subject
scientific metadata
ecological data
metadata for data sets
dcterms:publisher
Dublin Core Metadata Initiative
dcterms:type
Text
dcterms:language
en
dcterms:rights
CC BY 4.0