The University of Southampton
University of Southampton Institutional Repository

A query log analysis of dataset search

A query log analysis of dataset search
A query log analysis of dataset search
Data is one of the most important digital assets in the world and its availability on the web is increasing. To use it effectively, we need tools that can retrieve the most relevant datasets to match our information needs. Web search engines are not well suited for this task, as they are designed primarily for documents, not data. In this paper, we present the first query log analysis for dataset search, based on logs of four national open data portals. Our aim is to gain a better understanding of the typical users of these portals and the types of queries they issue, and frame the findings in the broader context of dataset search. The logs suggest that queries issued on data portals differ from those issued to web search engines in their length and structure. From the analysis we could also infer that the portals are used exploratively, rather than to answer focused questions. These insights can inform the design of more effective dataset retrieval technology, and improve the user experience of data portals.
0302-9743
429-436
Springer
Kacprzak, Emilia
fdc38ad7-6879-4769-ad65-5d3582690af2
Koesten, Laura M.
79e66d1b-2d8f-43df-a39b-60bc7749fb22
Ibáñez, Luis-Daniel
65a2e20b-74a9-427d-8c4c-2330285153ed
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67
Tennison, Jeni
abfdd103-6089-427d-babb-56448595f2fa
Cabot, J.
De Virgilio, R.
Torlone, R.
Kacprzak, Emilia
fdc38ad7-6879-4769-ad65-5d3582690af2
Koesten, Laura M.
79e66d1b-2d8f-43df-a39b-60bc7749fb22
Ibáñez, Luis-Daniel
65a2e20b-74a9-427d-8c4c-2330285153ed
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67
Tennison, Jeni
abfdd103-6089-427d-babb-56448595f2fa
Cabot, J.
De Virgilio, R.
Torlone, R.

Kacprzak, Emilia, Koesten, Laura M., Ibáñez, Luis-Daniel, Simperl, Elena and Tennison, Jeni (2017) A query log analysis of dataset search. In, Cabot, J., De Virgilio, R. and Torlone, R. (eds.) Intelligent End User Development Platform Towards Enhanced Decision-Making. (Web Engineering, , (doi:10.1007/978-3-319-60131-1_29), 10360) Cham. Springer, pp. 429-436. (doi:10.1007/978-3-319-60131-1_29).

Record type: Book Section

Abstract

Data is one of the most important digital assets in the world and its availability on the web is increasing. To use it effectively, we need tools that can retrieve the most relevant datasets to match our information needs. Web search engines are not well suited for this task, as they are designed primarily for documents, not data. In this paper, we present the first query log analysis for dataset search, based on logs of four national open data portals. Our aim is to gain a better understanding of the typical users of these portals and the types of queries they issue, and frame the findings in the broader context of dataset search. The logs suggest that queries issued on data portals differ from those issued to web search engines in their length and structure. From the analysis we could also infer that the portals are used exploratively, rather than to answer focused questions. These insights can inform the design of more effective dataset retrieval technology, and improve the user experience of data portals.

Full text not available from this repository.

More information

e-pub ahead of print date: 1 June 2017
Published date: 2017

Identifiers

Local EPrints ID: 438923
URI: http://eprints.soton.ac.uk/id/eprint/438923
ISSN: 0302-9743
PURE UUID: 742598c1-66dd-46dc-bc6d-f96c9a8890cd
ORCID for Elena Simperl: ORCID iD orcid.org/0000-0003-1722-947X

Catalogue record

Date deposited: 27 Mar 2020 17:30
Last modified: 20 May 2020 00:42

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×