Automating data citation: the eagle-i experience

Proc ACM/IEEE Joint Conf Digit Libr. 2017 Jun:2017:10.1109/JCDL.2017.7991571. doi: 10.1109/JCDL.2017.7991571. Epub 2017 Jul 27.

Abstract

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, XML, and RDF). We also describe how a database administrator would use this framework to automate citation for a particular dataset.