Disciplinary differences of software use and impact in scientific literature

Software plays an important role in the advancement of science. Software developers, users, and funding agencies have deep interests in the impact of software on science. This study investigates the use and impact of software by examining how software is mentioned and cited among 9548 articles published in PLOS ONE in 12 defined disciplines. Our results demonstrate that software is widely used in scientific research and a substantial uncitedness of software exists across different disciplines. Findings also show that the practice of software citations varies noticeably at the discipline level and software that is free for academic use is more likely to receive citations than commercial software.

[1]  魏屹东,et al.  Scientometrics , 2018, Encyclopedia of Big Data.

[2]  Sandra Slaughter,et al.  Why Developers Participate in Open Source Software Projects: An Empirical Investigation , 2004, ICIS.

[3]  Robert Stevens,et al.  bioNerDS: exploring bioinformatics’ database and software use through literature mining , 2013, BMC Bioinformatics.

[4]  Feng Liu,et al.  A survey of the practice of computational science , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[5]  Michael Anthony Bauer,et al.  Towards the integration, annotation and association of historical microarray experiments with RNA-seq , 2013, BMC Bioinformatics.

[6]  James D. Herbsleb,et al.  From Personal Tool to Community Resource: What's the Extra Work and Who Will Do It? , 2015, CSCW.

[7]  James D. Herbsleb,et al.  Incentives and integration in scientific software production , 2013, CSCW.

[8]  Nancy Wilkins-Diehr,et al.  Summary of the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1) , 2014, ArXiv.

[9]  James D. Herbsleb,et al.  Socio-technical logics of correctness in the scientific software development ecosystem , 2010 .

[10]  Heather A. Piwowar,et al.  Altmetrics: Value all research products , 2013, Nature.

[11]  James D. Herbsleb,et al.  Understanding the scientific software ecosystem and its impact: Current and future measures , 2015 .

[12]  Tun Lu,et al.  Meanings and boundaries of scientific software sharing , 2013, CSCW.

[13]  Heather A. Piwowar,et al.  Beginning to track 1000 datasets from public repositories into the published literature , 2011, ASIST.

[14]  Sandra Slaughter,et al.  Understanding the Motivations, Participation, and Performance of Open Source Software Developers: A Longitudinal Study of the Apache Projects , 2006, Manag. Sci..

[15]  Janice Singer,et al.  How do scientists develop and use scientific software? , 2009, 2009 ICSE Workshop on Software Engineering for Computational Science and Engineering.

[16]  Qianqian Wang,et al.  Assessing the impact of software on science: A bootstrapped learning of software entities in full-text papers , 2015, J. Informetrics.

[17]  Marlon Pierce,et al.  Cyberinfrastructure Software Sustainability and Reusability: Report from an NSF-funded workshop held 27 & 28 March 2009 , 2010 .

[18]  Nancy Wilkins-Diehr,et al.  Report on the Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2) , 2015, ArXiv.

[19]  Paolo Manghi,et al.  Data journals: A survey , 2014, J. Assoc. Inf. Sci. Technol..

[20]  Judith Segal,et al.  Developing Scientific Software , 2008, IEEE Software.

[21]  Brian Fitzgerald,et al.  Why Hackers Do What They Do: Understanding Motivation and Effort in Free/Open Source Software Projects , 2007 .

[22]  Caroline Jay,et al.  The Blind Men and the Elephant: Towards an Empirical Evaluation Framework for Software Sustainability , 2014 .

[23]  Wendy W. Chapman,et al.  Public sharing of research datasets: A pilot study of associations , 2010, J. Informetrics.

[24]  J. Howison.  Scientific software production and collaboration , 2010 .

[25]  Daniel S. Katz,et al.  Report on the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3) , 2016, ArXiv.

[26]  James D. Herbsleb,et al.  Scientific software production: incentives and collaboration , 2011, CSCW.

[27]  C. Tenopir,et al.  Data Sharing by Scientists: Practices and Perceptions , 2011, PloS one.

[28]  Nial Peters.  AvoPlot: An extensible scientific plotting tool based on matplotlib , 2014 .

[29]  Tiffany C. Chao.  Disciplinary reach: Investigating the impact of dataset reuse in the earth sciences , 2011, ASIST.

[30]  Timothée Poisot.  Best publishing practices to improve user confidence in scientific software , 2015 .

[31]  James D. Herbsleb,et al.  Sharing, re-use and circulation of resources in cooperative scientific work , 2014, CSCW Companion.

[32]  Trainer Erik,et al.  The Big Effects of Short-term Efforts: A Catalyst for Community Engagement in Scientific Software , 2013 .

[33]  Claudio Gutierrez,et al.  Survey of graph database models , 2008, CSUR.

[34]  Arthur E. Kirkpatrick,et al.  Assessing open source software as a scholarly contribution , 2009, Commun. ACM.

[35]  James Howison,et al.  Software in the scientific literature: Problems with seeing, finding, and using software mentioned in the biology literature , 2016, J. Assoc. Inf. Sci. Technol..

[36]  Charlotte P. Lee,et al.  Beyond trust and reliability: reusing data in collaborative cancer epidemiology research , 2013, CSCW.

[37]  Evaristo Jiménez-Contreras,et al.  Analyzing data citation practices using the data citation index , 2015, J. Assoc. Inf. Sci. Technol..

[38]  Kevin Crowston,et al.  Free/Libre open-source software development: What we know and what we do not know , 2012, CSUR.