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Data Citation: Giving Credit Where Credit is Due

Authors:

Abdussalam Alawini,

Susan B. Davidson,

Gianmaria SilvelloAuthors Info & Claims

SIGMOD '18: Proceedings of the 2018 International Conference on Management of Data

Pages 99 - 114

https://doi.org/10.1145/3183713.3196910

Published: 27 May 2018 Publication History

Abstract

An increasing amount of information is being published in structured databases and retrieved using queries, raising the question of how query results should be cited. Since there are a large number of possible queries over a database, one strategy is to specify citations to a small set of frequent queries - citation views - and use these to construct citations to other "general" queries. We present three approaches to implementing citation views and describe alternative policies for the joint, alternate and aggregated use of citation views. Extensive experiments using both synthetic and realistic citation views and queries show the trade-offs between the approaches in terms of the time to generate citations, as well as the size of the resulting citation. They also show that the choice of policy has a huge effect both on performance and size, leading to useful guidelines for what policies to use and how to specify citation views.

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Cited By

Lotta ASilvello G(2023)How to Cite a Web Ranking and Make it FAIRLinking Theory and Practice of Digital Libraries10.1007/978-3-031-43849-3_6(65-78)Online publication date: 22-Sep-2023
https://doi.org/10.1007/978-3-031-43849-3_6
Alawini ARao PZhou LKang LHo P(2022)Teaching Data Models with TriQLProceedings of the 1st International Workshop on Data Systems Education10.1145/3531072.3535320(16-21)Online publication date: 12-Jun-2022
https://dl.acm.org/doi/10.1145/3531072.3535320
Dosso DDavidson SSilvello G(2022)Credit distribution in relational scientific databasesInformation Systems10.1016/j.is.2022.102060109:COnline publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1016/j.is.2022.102060
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cover image ACM Conferences

SIGMOD '18: Proceedings of the 2018 International Conference on Management of Data

May 2018

1874 pages

ISBN:9781450347037

DOI:10.1145/3183713

General Chairs:
Gautam Das
University of Texas at Arlington, USA
,
Christopher Jermaine
Rice University, USA
,
Philip Bernstein
Microsoft Research, USA

Copyright © 2018 ACM.

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Badge change: Article originally badged under Version 1.0 guidelines https://www.acm.org/publications/policies/artifact-review-badging

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Published: 27 May 2018

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SIGMOD/PODS '18: International Conference on Management of Data

June 10 - 15, 2018

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SIGMOD '18 Paper Acceptance Rate 90 of 461 submissions, 20%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

Lotta ASilvello G(2023)How to Cite a Web Ranking and Make it FAIRLinking Theory and Practice of Digital Libraries10.1007/978-3-031-43849-3_6(65-78)Online publication date: 22-Sep-2023
https://doi.org/10.1007/978-3-031-43849-3_6
Alawini ARao PZhou LKang LHo P(2022)Teaching Data Models with TriQLProceedings of the 1st International Workshop on Data Systems Education10.1145/3531072.3535320(16-21)Online publication date: 12-Jun-2022
https://dl.acm.org/doi/10.1145/3531072.3535320
Dosso DDavidson SSilvello G(2022)Credit distribution in relational scientific databasesInformation Systems10.1016/j.is.2022.102060109:COnline publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1016/j.is.2022.102060
Buneman PDosso DLissandrini MSilvello G(2021)Data citation and the citation graphQuantitative Science Studies10.1162/qss_a_001662:4(1399-1422)Online publication date: 1-Dec-2021
https://doi.org/10.1162/qss_a_00166
Buneman PChristie GDavies JDimitrellou RHarding SPawson ASharman JWu Y(2020)Why data citation isn't working, and what to do about itDatabase10.1093/databa/baaa0222020Online publication date: 12-May-2020
https://doi.org/10.1093/databa/baaa022
Dosso DSilvello G(2020)Data credit distribution: A new method to estimate databases impactJournal of Informetrics10.1016/j.joi.2020.10108014:4(101080)Online publication date: Nov-2020
https://doi.org/10.1016/j.joi.2020.101080
Fabris EKuhn TSilvello G(2020)Nanocitation: Complete and Interoperable Citations of NanopublicationsDigital Libraries: The Era of Big Data and Data Science10.1007/978-3-030-39905-4_18(182-187)Online publication date: 22-Jan-2020
https://doi.org/10.1007/978-3-030-39905-4_18
Wu YAlawini ADeutch DMilo TDavidson S(2019)ProvCiteProceedings of the VLDB Endowment10.14778/3317315.331731712:7(738-751)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.14778/3317315.3317317
Chapman ASimperl EKoesten LKonstantinidis GIbáñez LKacprzak EGroth P(2019)Dataset search: a surveyThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-019-00564-x29:1(251-272)Online publication date: 24-Aug-2019
https://dl.acm.org/doi/10.1007/s00778-019-00564-x
Fabris EKuhn TSilvello G(2019)A Framework for Citing NanopublicationsDigital Libraries for Open Knowledge10.1007/978-3-030-30760-8_6(70-83)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1007/978-3-030-30760-8_6
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