Automating Data Citation: The eagle-i Experience

Abdussalam Alawini, Leshang Chen, Susan B. Davidson, Natan Portilho Da Silva, Gianmaria Silvello

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Data citation is of growing concern for owners of curated databases, who wish to give credit to the contributors and curators responsible for portions of the dataset and enable the data retrieved by a query to be later examined. While several databases specify how data should be cited, they leave it to users to manually construct the citations and do not generate them automatically. We report our experiences in automating data citation for an RDF dataset called eagle-i, and discuss how to generalize this to a citation framework that can work across a variety of different types of databases (e.g., relational or XML).

Original languageEnglish (US)
Title of host publication2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538638613
StatePublished - Jul 25 2017
Externally publishedYes
Event17th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017 - Toronto, Canada
Duration: Jun 19 2017Jun 23 2017

Publication series

NameProceedings of the ACM/IEEE Joint Conference on Digital Libraries
ISSN (Print)1552-5996


Other17th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017

ASJC Scopus subject areas

  • Engineering(all)


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