SchemaDB: A Dataset for Structures in Relational Data

Cody Christopher; Kristen Moore; David Liebowitz

doi:10.1007/978-981-19-8746-5_17

SchemaDB: A Dataset for Structures in Relational Data

Cody Christopher^*, Kristen Moore, David Liebowitz

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review

Abstract

In this paper we introduce the SchemaDB dataset; a collection of relational database schemas in both sql and graph formats. Databases are not commonly shared publicly for reasons of privacy and security, and so the corresponding schema for these databases are often not available for study. Consequently, an understanding of database structures in the wild is lacking, and most easily found examples of schema found publicly belong to common development frameworks or are derived from textbooks or engine benchmarks. SchemaDB contains 2,500 samples of relational schema found in public code repositories which have been standardised to MySQL syntax. We provide our gathering and transformation methodology, summary statistics, structural analysis, and discuss potential downstream research tasks in several domains.

Original language	English
Title of host publication	Data Mining
Subtitle of host publication	20th Australasian Conference, AusDM 2022 Western Sydney, Australia, December 12–15, 2022 Proceedings
Editors	Laurence A.F. Park, Simeon Simoff, Heitor Murilo Gomes, Maryam Doborjeh, Yee Ling Boo, Yun Sing Koh, Yanchang Zhao, Graham Williams
Place of Publication	Singapore
Publisher	Springer Science+Business Media B.V.
Pages	233-243
Number of pages	11
ISBN (Electronic)	978-981-19-8746-5
ISBN (Print)	9789811987458
DOIs	https://doi.org/10.1007/978-981-19-8746-5_17
Publication status	Published - 2022
Externally published	Yes
Event	20th Australasian Data Mining Conference, AusDM 2022 - Western Sydney, Australia Duration: 12 Dec 2022 → 15 Dec 2022

Publication series

Name	Communications in Computer and Information Science
Volume	1741 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	20th Australasian Data Mining Conference, AusDM 2022
Country/Territory	Australia
City	Western Sydney
Period	12/12/22 → 15/12/22

Access to Document

10.1007/978-981-19-8746-5_17

Cite this

Christopher, C., Moore, K., & Liebowitz, D. (2022). SchemaDB: A Dataset for Structures in Relational Data. In L. A. F. Park, S. Simoff, H. M. Gomes, M. Doborjeh, Y. L. Boo, Y. S. Koh, Y. Zhao, & G. Williams (Eds.), Data Mining: 20th Australasian Conference, AusDM 2022 Western Sydney, Australia, December 12–15, 2022 Proceedings (pp. 233-243). (Communications in Computer and Information Science; Vol. 1741 CCIS). Springer Science+Business Media B.V.. https://doi.org/10.1007/978-981-19-8746-5_17

Christopher, Cody ; Moore, Kristen ; Liebowitz, David. / SchemaDB : A Dataset for Structures in Relational Data. Data Mining: 20th Australasian Conference, AusDM 2022 Western Sydney, Australia, December 12–15, 2022 Proceedings. editor / Laurence A.F. Park ; Simeon Simoff ; Heitor Murilo Gomes ; Maryam Doborjeh ; Yee Ling Boo ; Yun Sing Koh ; Yanchang Zhao ; Graham Williams. Singapore : Springer Science+Business Media B.V., 2022. pp. 233-243 (Communications in Computer and Information Science).

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abstract = "In this paper we introduce the SchemaDB dataset; a collection of relational database schemas in both sql and graph formats. Databases are not commonly shared publicly for reasons of privacy and security, and so the corresponding schema for these databases are often not available for study. Consequently, an understanding of database structures in the wild is lacking, and most easily found examples of schema found publicly belong to common development frameworks or are derived from textbooks or engine benchmarks. SchemaDB contains 2,500 samples of relational schema found in public code repositories which have been standardised to MySQL syntax. We provide our gathering and transformation methodology, summary statistics, structural analysis, and discuss potential downstream research tasks in several domains.",

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author = "Cody Christopher and Kristen Moore and David Liebowitz",

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Christopher, C, Moore, K & Liebowitz, D 2022, SchemaDB: A Dataset for Structures in Relational Data. in LAF Park, S Simoff, HM Gomes, M Doborjeh, YL Boo, YS Koh, Y Zhao & G Williams (eds), Data Mining: 20th Australasian Conference, AusDM 2022 Western Sydney, Australia, December 12–15, 2022 Proceedings. Communications in Computer and Information Science, vol. 1741 CCIS, Springer Science+Business Media B.V., Singapore, pp. 233-243, 20th Australasian Data Mining Conference, AusDM 2022, Western Sydney, Australia, 12/12/22. https://doi.org/10.1007/978-981-19-8746-5_17

SchemaDB: A Dataset for Structures in Relational Data. / Christopher, Cody; Moore, Kristen; Liebowitz, David.
Data Mining: 20th Australasian Conference, AusDM 2022 Western Sydney, Australia, December 12–15, 2022 Proceedings. ed. / Laurence A.F. Park; Simeon Simoff; Heitor Murilo Gomes; Maryam Doborjeh; Yee Ling Boo; Yun Sing Koh; Yanchang Zhao; Graham Williams. Singapore: Springer Science+Business Media B.V., 2022. p. 233-243 (Communications in Computer and Information Science; Vol. 1741 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review

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Christopher C, Moore K, Liebowitz D. SchemaDB: A Dataset for Structures in Relational Data. In Park LAF, Simoff S, Gomes HM, Doborjeh M, Boo YL, Koh YS, Zhao Y, Williams G, editors, Data Mining: 20th Australasian Conference, AusDM 2022 Western Sydney, Australia, December 12–15, 2022 Proceedings. Singapore: Springer Science+Business Media B.V. 2022. p. 233-243. (Communications in Computer and Information Science). doi: 10.1007/978-981-19-8746-5_17