Alharbi, A. and Stevenson, R. orcid.org/0000-0002-9483-6006
(2019)
A dataset of systematic review updates.
In:
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval.
42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 21-25 Jul 2019, Paris, France.
ACM
, pp. 1257-1260.
ISBN 978-1-4503-6172-9
Abstract
Systematic reviews identify, summarise and synthesise evidence relevant to specific research questions. They are widely used in the field of medicine where they inform health care choices of both professionals and patients. It is important for systematic reviews to stay up to date as evidence changes but this is challenging in a field such as medicine where a large number of publications appear on a daily basis. Developing methods to support the updating of reviews is important to reduce the workload required and thereby ensure that reviews remain up to date. This paper describes a dataset of systematic review updates in the field of medicine created using 25 Cochrane reviews. Each review includes the Boolean query and relevance judgements for both the original and updated versions. The dataset can be used to evaluate approaches to study identification for review updates.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 The Authors. This is an author-produced version of a paper subsequently published in Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Systematic review; systematic review update; test collection; evaluation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 May 2019 13:46 |
Last Modified: | 02 Aug 2019 14:13 |
Status: | Published |
Publisher: | ACM |
Refereed: | Yes |
Identification Number: | 10.1145/3331184.3331358 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:146321 |