Expanding the Citation Graph for Data Citations

Peter Buneman; Dennis Dosso; Matteo Lissandrini; Gianmaria Silvello

Expanding the Citation Graph for Data Citations

Peter Buneman^*, Dennis Dosso^*, Matteo Lissandrini^*, Gianmaria Silvello^*

^*Corresponding author for this work

Research output: Contribution to journal › Conference article in Journal › Research › peer-review

21 Downloads (Pure)

Abstract

The Citation Graph (CG) is a computational artifact widely used to represent the domain of published literature. There is an increasing demand to treat the publication of data in the same way that we treat conventional publications. It should be possible to cite data for the same reasons that is is necessary to cite other publications. In this paper we see some of the limitations of the citation graph, and we discuss how some implementation-agnostic extensions may solve them, thus also allowing the introduction of data and the management of data citations within the CG.

Original language	English
Journal	CEUR Workshop Proceedings
Volume	3194
Pages (from-to)	276-283
Number of pages	8
ISSN	1613-0073
Publication status	Published - 2022
Event	30th Italian Symposium on Advanced Database Systems, SEBD 2022 - Tirrenia, Italy Duration: 19 Jun 2022 → 20 Jun 2022

Conference

Conference	30th Italian Symposium on Advanced Database Systems, SEBD 2022
Country/Territory	Italy
City	Tirrenia
Period	19/06/2022 → 20/06/2022

Bibliographical note

Funding Information:
The work was partially supported by the ExaMode project, as part of the European Union H2020 program under Grant Agreement no. 825292. Matteo Lissandrini is supported by the European Union H2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 838216. Peter Buneman was partly supported by the Huawei Edinburgh Research Laboratory.

Publisher Copyright:
© 2022 CEUR-WS. All rights reserved.

Keywords

Bibliometrics
Citation Graph
Data Citation

Access to Document

Open Access articleFinal published version, 1.03 MBLicence: CC BY 4.0

https://ceur-ws.org/Vol-3194/paper33.pdfLicence: CC BY 4.0

AUB Link

Search for the material in Aalborg University Library's search engine

Cite this

@inproceedings{3971b3ea8a6a4819bc7900728e48285f,

title = "Expanding the Citation Graph for Data Citations",

abstract = "The Citation Graph (CG) is a computational artifact widely used to represent the domain of published literature. There is an increasing demand to treat the publication of data in the same way that we treat conventional publications. It should be possible to cite data for the same reasons that is is necessary to cite other publications. In this paper we see some of the limitations of the citation graph, and we discuss how some implementation-agnostic extensions may solve them, thus also allowing the introduction of data and the management of data citations within the CG.",

keywords = "Bibliometrics, Citation Graph, Data Citation",

author = "Peter Buneman and Dennis Dosso and Matteo Lissandrini and Gianmaria Silvello",

note = "Funding Information: The work was partially supported by the ExaMode project, as part of the European Union H2020 program under Grant Agreement no. 825292. Matteo Lissandrini is supported by the European Union H2020 research and innovation program under the Marie Sk{\l}odowska-Curie grant agreement No 838216. Peter Buneman was partly supported by the Huawei Edinburgh Research Laboratory. Publisher Copyright: {\textcopyright} 2022 CEUR-WS. All rights reserved.; 30th Italian Symposium on Advanced Database Systems, SEBD 2022 ; Conference date: 19-06-2022 Through 20-06-2022",

year = "2022",

language = "English",

volume = "3194",

pages = "276--283",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

publisher = "CEUR Workshop Proceedings",

}

TY - GEN

T1 - Expanding the Citation Graph for Data Citations

AU - Buneman, Peter

AU - Dosso, Dennis

AU - Lissandrini, Matteo

AU - Silvello, Gianmaria

N1 - Funding Information: The work was partially supported by the ExaMode project, as part of the European Union H2020 program under Grant Agreement no. 825292. Matteo Lissandrini is supported by the European Union H2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 838216. Peter Buneman was partly supported by the Huawei Edinburgh Research Laboratory. Publisher Copyright: © 2022 CEUR-WS. All rights reserved.

PY - 2022

Y1 - 2022

N2 - The Citation Graph (CG) is a computational artifact widely used to represent the domain of published literature. There is an increasing demand to treat the publication of data in the same way that we treat conventional publications. It should be possible to cite data for the same reasons that is is necessary to cite other publications. In this paper we see some of the limitations of the citation graph, and we discuss how some implementation-agnostic extensions may solve them, thus also allowing the introduction of data and the management of data citations within the CG.

AB - The Citation Graph (CG) is a computational artifact widely used to represent the domain of published literature. There is an increasing demand to treat the publication of data in the same way that we treat conventional publications. It should be possible to cite data for the same reasons that is is necessary to cite other publications. In this paper we see some of the limitations of the citation graph, and we discuss how some implementation-agnostic extensions may solve them, thus also allowing the introduction of data and the management of data citations within the CG.

KW - Bibliometrics

KW - Citation Graph

KW - Data Citation

UR - http://www.scopus.com/inward/record.url?scp=85137422210&partnerID=8YFLogxK

M3 - Conference article in Journal

AN - SCOPUS:85137422210

SN - 1613-0073

VL - 3194

SP - 276

EP - 283

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 30th Italian Symposium on Advanced Database Systems, SEBD 2022

Y2 - 19 June 2022 through 20 June 2022

ER -

Expanding the Citation Graph for Data Citations

Abstract

Conference

Bibliographical note

Keywords

Access to Document

AUB Link

Other files and links

Fingerprint

Data citation and the citation graph

Cite this