A Model for Fine-Grained Data Citation

Susan Davidson, Daniel Deutch, Tova Milo, Gianmaria Silvello

Research output: Contribution to journalConference articlepeer-review


An increasing amount of information is being collected in structured, evolving, curated databases, driving the question of how information extracted from such datasets via queries should be cited. Unlike traditional research products which have a fixed granularity, data citation is a challenge because the granularity varies. Different portions of the database, with varying granularity, may have different citations. Furthermore, there are an infinite number of queries over a database, so we cannot hope to explicitly attach a citation to every possible result set and/or query. We present the novel problem of automatically generating citations for general queries over a relational database, and explore a solution based on citation views, each of which attaches a citation to a view of the database. Citation views are then used to automatically construct citations for general queries.

Original languageEnglish
JournalCEUR Workshop Proceedings
StatePublished - 2017
Event25th Italian Symposium on Advanced Database Systems, SEBD 2017 - Squillace Lido, Italy
Duration: 25 Jun 201729 Jun 2017


FundersFunder number
Centre for Interdisciplinary Research in Rehabilitation
H2020 European Research Council1636/13, 291071
Peter Maccallum Cancer Centre
Center for Modelling and Simulation in the BiosciencesNSF IIS 1302212, NSF ACI 1547360, NIH 3-U01-EB-020954-02S1

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