Linkitup: Link Discovery for Research Data
| Authors | |
|---|---|
| Publication date | 2013 |
| Journal | AAAI Fall Symposium Series Technical Reports |
| Event | AAAI 2013 Fall Symposium Series: Discovery Informatics: AI Takes a Science-Centered View on Big Data |
| Volume | Issue number | FS-13-01 |
| Pages (from-to) | 28-35 |
| Organisations |
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| Abstract |
Linkitup is a Web-based dashboard for enrichment of research output published via industry grade data repository services. It takes metadata entered through Figshare.com and tries to find equivalent terms, categories, persons or entities on the Linked Data cloud and several Web 2.0 services. It extracts references from publications, and tries to find the corresponding Digital Object Identifier (DOI). Linkitup feeds the enriched metadata back as links to the original article in the repository, but also builds a RDF representation of the metadata that can be downloaded separately, or published
as research output in its own right. In this paper, we compare Linkitup to the standard workflow of publishing linked data, and show that it significantly lowers the threshold for publishing linked research data. |
| Document type | Article |
| Note | Proceedings title: Discovery Informatics: AI Takes a Science-Centered View on Big Data: Papers from the AAAI symposium Publisher: AAAI Publications ISBN: 978-1-57735-639-4 Editors: G.A.P.C. Burns, Y. Gil, Y. Liu, N. Villanueva-Rosales |
| Language | English |
| Published at | https://www.aaai.org/ocs/index.php/FSS/FSS13/paper/viewFile/7595/7491 |
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