Conference Paper/Proceeding/Abstract 759 views 177 downloads
"Share and Enjoy": Publishing Useful and Usable Scientific Models
Proceedings of 7th IEEE/ACM International Conference on Utility and Cloud Computing, Pages: 957 - 961
Swansea University Author: Tom Crick
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DOI (Published version): 10.1109/UCC.2014.156
Abstract
The reproduction and replication of reported scientific results is a hot topic within the academic community. The retraction of numerous studies from a wide range of disciplines, from climate science to bioscience, has drawn the focus of many commentators, but there exists a wider socio-cultural pro...
Published in: | Proceedings of 7th IEEE/ACM International Conference on Utility and Cloud Computing |
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ISBN: | 978-1-4799-7881-6 |
Published: |
London, UK
IEEE
2014
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Online Access: |
https://ieeexplore.ieee.org/document/7027623/ |
URI: | https://cronfa.swan.ac.uk/Record/cronfa43392 |
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2023-01-11T14:20:03Z |
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2022-12-18T17:44:51.9537245 v2 43392 2018-08-14 "Share and Enjoy": Publishing Useful and Usable Scientific Models 200c66ef0fc55391f736f6e926fb4b99 0000-0001-5196-9389 Tom Crick Tom Crick true false 2018-08-14 SOSS The reproduction and replication of reported scientific results is a hot topic within the academic community. The retraction of numerous studies from a wide range of disciplines, from climate science to bioscience, has drawn the focus of many commentators, but there exists a wider socio-cultural problem that pervades the scientific community. Sharing code, data and models often requires extra effort, this is currently seen as a significant overhead that may not be worth the time investment. Automated systems, which allow easy reproduction of results, offer the potential to incentives a culture change and drive the adoption of new techniques to improve the efficiency of scientific exploration. In this paper, we discuss the value of improved access and sharing of the two key types of results arising from work done in the computational sciences: models and algorithms. We propose the development of an integrated cloud-based system underpinning computational science, linking together software and data repositories, tool chains, workflows and outputs, providing a seamless automated infrastructure for the verification and validation of scientific models and in particular, performance benchmarks. Conference Paper/Proceeding/Abstract Proceedings of 7th IEEE/ACM International Conference on Utility and Cloud Computing 957 961 IEEE London, UK 978-1-4799-7881-6 8 12 2014 2014-12-08 10.1109/UCC.2014.156 https://ieeexplore.ieee.org/document/7027623/ 7th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2014) COLLEGE NANME Social Sciences School COLLEGE CODE SOSS Swansea University 2022-12-18T17:44:51.9537245 2018-08-14T15:45:07.5975557 Faculty of Humanities and Social Sciences School of Social Sciences - Education and Childhood Studies Tom Crick 0000-0001-5196-9389 1 Benjamin A. Hall 2 Samin Ishtiaq 3 Kenji Takeda 4 0043392-11092018064937.pdf 1409.0367v2.pdf 2018-09-11T06:49:37.0200000 Output 146075 application/pdf Accepted Manuscript true 2018-09-11T00:00:00.0000000 true eng |
title |
"Share and Enjoy": Publishing Useful and Usable Scientific Models |
spellingShingle |
"Share and Enjoy": Publishing Useful and Usable Scientific Models Tom Crick |
title_short |
"Share and Enjoy": Publishing Useful and Usable Scientific Models |
title_full |
"Share and Enjoy": Publishing Useful and Usable Scientific Models |
title_fullStr |
"Share and Enjoy": Publishing Useful and Usable Scientific Models |
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"Share and Enjoy": Publishing Useful and Usable Scientific Models |
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"Share and Enjoy": Publishing Useful and Usable Scientific Models |
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Tom Crick |
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description |
The reproduction and replication of reported scientific results is a hot topic within the academic community. The retraction of numerous studies from a wide range of disciplines, from climate science to bioscience, has drawn the focus of many commentators, but there exists a wider socio-cultural problem that pervades the scientific community. Sharing code, data and models often requires extra effort, this is currently seen as a significant overhead that may not be worth the time investment. Automated systems, which allow easy reproduction of results, offer the potential to incentives a culture change and drive the adoption of new techniques to improve the efficiency of scientific exploration. In this paper, we discuss the value of improved access and sharing of the two key types of results arising from work done in the computational sciences: models and algorithms. We propose the development of an integrated cloud-based system underpinning computational science, linking together software and data repositories, tool chains, workflows and outputs, providing a seamless automated infrastructure for the verification and validation of scientific models and in particular, performance benchmarks. |
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2014-12-08T19:43:18Z |
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