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.

Author information

Jian Qin
Syracuse University,
Miao Chen
Syracuse University, US
Xiaozhong Liu
Syracuse University, US
Andrea Kathleen Wiggins
Syracuse University, US

Cite this article

Qin, J., Chen, M., Liu, X., & Wiggins, A. (2010). Linking Entities in Scientific Metadata. International Conference on Dublin Core and Metadata Applications, 2010. https://doi.org/10.23106/dcmi.952109855

DOI : 10.23106/dcmi.952109855

CC-0 Logo Metadata and citations of this article is published under the Creative Commons Zero Universal Public Domain Dedication (CC0), allowing unrestricted reuse. Anyone can freely use the metadata from DCPapers articles for any purpose without limitations.
CC-BY Logo This article full-text is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license allows use, sharing, adaptation, distribution, and reproduction in any medium or format, provided that appropriate credit is given to the original author(s) and the source is cited.