Dataset search: a survey
Dataset search: a survey
Generating value from data requires the ability to find, access and make sense of datasets. There are many efforts underway to encourage data sharing and reuse, from scientific publishers asking authors to submit data alongside manuscripts to data marketplaces, open data portals and data communities. Google recently beta-released a search service for datasets, which allows users to discover data stored in various online repositories via keyword queries. These developments foreshadow an emerging research field around dataset search or retrieval that broadly encompasses frameworks, methods and tools that help match a user data need against a collection of datasets. Here, we survey the state of the art of research and commercial systems and discuss what makes dataset search a field in its own right, with unique challenges and open questions. We look at approaches and implementations from related areas dataset search is drawing upon, including information retrieval, databases, entity-centric and tabular search in order to identify possible paths to tackle these questions as well as immediate next steps that will take the field forward.
Dataset search · Dataset retrieval · Dataset · Information search and retrieval
1-22
Chapman, Adriane
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Simperl, Elena
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Koesten, Laura
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Konstantinidis, Georgios
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Ibanez Gonzalez, Luis
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Kacprzak, Emilia
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Groth, Paul
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Chapman, Adriane
721b7321-8904-4be2-9b01-876c430743f1
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67
Koesten, Laura
79e66d1b-2d8f-43df-a39b-60bc7749fb22
Konstantinidis, Georgios
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Ibanez Gonzalez, Luis
65a2e20b-74a9-427d-8c4c-2330285153ed
Kacprzak, Emilia
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Groth, Paul
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Chapman, Adriane, Simperl, Elena, Koesten, Laura, Konstantinidis, Georgios, Ibanez Gonzalez, Luis, Kacprzak, Emilia and Groth, Paul
(2019)
Dataset search: a survey.
The VLDB Journal, .
(doi:10.1007/s00778-019-00564-x).
Abstract
Generating value from data requires the ability to find, access and make sense of datasets. There are many efforts underway to encourage data sharing and reuse, from scientific publishers asking authors to submit data alongside manuscripts to data marketplaces, open data portals and data communities. Google recently beta-released a search service for datasets, which allows users to discover data stored in various online repositories via keyword queries. These developments foreshadow an emerging research field around dataset search or retrieval that broadly encompasses frameworks, methods and tools that help match a user data need against a collection of datasets. Here, we survey the state of the art of research and commercial systems and discuss what makes dataset search a field in its own right, with unique challenges and open questions. We look at approaches and implementations from related areas dataset search is drawing upon, including information retrieval, databases, entity-centric and tabular search in order to identify possible paths to tackle these questions as well as immediate next steps that will take the field forward.
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ChapmanDatasetSearchFinal
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Accepted/In Press date: 12 August 2019
e-pub ahead of print date: 24 August 2019
Keywords:
Dataset search · Dataset retrieval · Dataset · Information search and retrieval
Identifiers
Local EPrints ID: 433957
URI: http://eprints.soton.ac.uk/id/eprint/433957
ISSN: 1066-8888
PURE UUID: a367d245-023f-4a4d-82c9-6821ac3ef2a4
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Date deposited: 09 Sep 2019 16:30
Last modified: 16 Mar 2024 04:29
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Contributors
Author:
Laura Koesten
Author:
Georgios Konstantinidis
Author:
Luis Ibanez Gonzalez
Author:
Emilia Kacprzak
Author:
Paul Groth
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