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"Can I Implement Your Algorithm?": A Model for Reproducible Research Software / Tom Crick; Benjamin A. Hall; Samin Ishtiaq

2nd Workshop on Sustainable Software for Science: Practice and Experiences

Swansea University Author: Crick, Tom

Abstract

The reproduction and replication of novel results has become a major issue for a number of scientific disciplines. In computer science and related computational disciplines such as systems biology, the issues closely revolve around the ability to implement novel algorithms and approaches. Taking an...

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Published in: 2nd Workshop on Sustainable Software for Science: Practice and Experiences
Published: New Orleans, USA 2014
Online Access: https://arxiv.org/abs/1407.5981
URI: https://cronfa.swan.ac.uk/Record/cronfa43757
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spelling 2018-10-15T14:49:20Z v2 43757 2018-09-11 "Can I Implement Your Algorithm?": A Model for Reproducible Research Software Tom Crick Tom Crick true 0000-0001-5196-9389 false 200c66ef0fc55391f736f6e926fb4b99 9971fd6d74987b78a0d7fce128f8c721 z93Ri4T5hwMLTfh+6XG11n2HZhUyFASdV1DFdgIIhKs= 2018-09-11 EDUC The reproduction and replication of novel results has become a major issue for a number of scientific disciplines. In computer science and related computational disciplines such as systems biology, the issues closely revolve around the ability to implement novel algorithms and approaches. Taking an approach from the literature and applying it to a new codebase frequently requires local knowledge missing from the published manuscripts and project websites. Alongside this issue, benchmarking, and the development of fair --- and widely available --- benchmark sets present another barrier.In this paper, we outline several suggestions to address these issues, driven by specific examples from a range of scientific domains. Finally, based on these suggestions, we propose a new open platform for scientific software development which effectively isolates specific dependencies from the individual researcher and their workstation and allows faster, more powerful sharing of the results of scientific software engineering. Conference contribution 2nd Workshop on Sustainable Software for Science: Practice and Experiences New Orleans, USA 16 11 2014 2014-11-16 https://arxiv.org/abs/1407.5981 2nd Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2) College of Arts and Humanities School of Education CAAH EDUC None None 2018-10-15T14:49:20Z 2018-09-11T07:45:25Z College of Arts and Humanities College of Arts and Humanities Tom Crick 0000-0001-5196-9389 1 Benjamin A. Hall 2 Samin Ishtiaq 3 0043757-11092018074653.pdf 1407.5981v2.pdf 2018-09-11T07:46:53Z Output 215055 application/pdf VoR true Updated Copyright 15/10/2018 2018-09-11T00:00:00 true eng
title "Can I Implement Your Algorithm?": A Model for Reproducible Research Software
spellingShingle "Can I Implement Your Algorithm?": A Model for Reproducible Research Software
Crick, Tom
title_short "Can I Implement Your Algorithm?": A Model for Reproducible Research Software
title_full "Can I Implement Your Algorithm?": A Model for Reproducible Research Software
title_fullStr "Can I Implement Your Algorithm?": A Model for Reproducible Research Software
title_full_unstemmed "Can I Implement Your Algorithm?": A Model for Reproducible Research Software
title_sort "Can I Implement Your Algorithm?": A Model for Reproducible Research Software
author_id_str_mv 200c66ef0fc55391f736f6e926fb4b99
author_id_fullname_str_mv 200c66ef0fc55391f736f6e926fb4b99_***_Crick, Tom
author Crick, Tom
author2 Tom Crick
Benjamin A. Hall
Samin Ishtiaq
format Conference contribution
container_title 2nd Workshop on Sustainable Software for Science: Practice and Experiences
publishDate 2014
institution Swansea University
college_str College of Arts and Humanities
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url https://arxiv.org/abs/1407.5981
document_store_str 1
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description The reproduction and replication of novel results has become a major issue for a number of scientific disciplines. In computer science and related computational disciplines such as systems biology, the issues closely revolve around the ability to implement novel algorithms and approaches. Taking an approach from the literature and applying it to a new codebase frequently requires local knowledge missing from the published manuscripts and project websites. Alongside this issue, benchmarking, and the development of fair --- and widely available --- benchmark sets present another barrier.In this paper, we outline several suggestions to address these issues, driven by specific examples from a range of scientific domains. Finally, based on these suggestions, we propose a new open platform for scientific software development which effectively isolates specific dependencies from the individual researcher and their workstation and allows faster, more powerful sharing of the results of scientific software engineering.
published_date 2014-11-16T06:10:37Z
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