Browse > Article
http://dx.doi.org/10.3743/KOSIM.2021.38.4.065

The Implications of Current Practices Relating to the Sharing, Reuse, and Citation of Research Software for the Future of Research  

Park, Hyoungjoo (Department of Library and Information Science, Chungnam National University)
Wolfram, Dietmar (School of Information Studies, University of Wisconsin - Milwaukee)
Publication Information
Journal of the Korean Society for information Management / v.38, no.4, 2021 , pp. 65-82 More about this Journal
Abstract
The purpose of this research is to explore the phenomenon of the sharing, reuse, and citation of research software. These practices are playing an increasingly important role in scholarly communication. The researchers found that the citation and reuse of research software are currently uncommon or at least not reflected in the Data Citation Index (DCI). Such citation was observed, however, for the newer software in a number of prominent repositories. The repositories Comprehensive R Archive Network (CRAN) and Zenodo received the most formal software citations. The researchers observed both formal and informal forms of citation when researchers reused software. The latter form involves mentioning research software in passing in the main text of articles, while formal citations appear in the references section. In addition, our comparative analysis helps to explain the phenomenon of self-citation of research software.
Keywords
research software; software citation; software sharing; software reuse;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Robinson-Garcia, N., Jimenez-Contreras, E., & Torres-Salinas, D. (2015). Analyzing data citation practices using the data citation index. Journal of the Association for Information Science and Technology, 67(12), 2964-2975. http://doi.org/10.1002/asi.23529   DOI
2 Socias, S. M., Morin, A., Tomony, M. A., & Sliz, P. (2015). AppCiter: a web application for increasing rates and accuracy of scientific software citation. Structure, 23(5), 807-808. http://doi.org/10.1016/j.str.2015.04.005   DOI
3 Park, H. & Wolfram, D. (2017). An examination of research data sharing and re-use: implications for data citation practice. Scientometrics, 111(1), 443-461. http://doi.org/10.1007/s11192-017-2240-2   DOI
4 Jones, M. B., Boettiger, C., Mayes, A. C., Smith, A., Slaughter, P., Niemeyer, K., Gil, Y., Fenner, M., Nowak, K., Hahnel, M., Coy, L., Allen, A., Crosas, M., Sands, A., Chue Hong, N., Cruse, P., Katz, D. S., & Goble, C. (2017). CodeMeta. KNB Data Repository. http://doi.org/10.5063/schema/codemeta-2.0   DOI
5 Morisio, M., Ezran, M., & Tully, C. (2002). Success and failure factors in software reuse. IEEE Transaction on Software Engineering, 28(4), 340-357. http://doi.org/10.1109/TSE.2002.995420   DOI
6 Druskat, S., Spaaks, J. H., Chue Hong, N., Haines, R., & Baker, J. (2019). Citation file format (CFF) - specifications. Zenodo. http://doi.org/10.5281/zenodo.3515946   DOI
7 Kats, D. S., Bouquin, D., Chue Hong, N. P., Hausman, J., Jones, C., Chivvis, D., Clark, T., Crosas, M., Druskat, S., Fenner, M., Gillespie, T., Gonzalez-Beltran, A., Gruenpeter, M., Habermann, T., Haines, R., Harrison, M., Henneken, E., Hwang, L., Jones, M. B., Alastair, J., Kelly A. A., Kennedy, D. N., Leinweber, K., Rois, F., Robinson, C. B., Todorov, I., Wu, M., & Zhang, Q. (2019). Software citation implementation challenges. Available: https://arxiv.org/ftp/arxiv/papers/1905/1905.08674.pdf
8 Piwowar, H. A., Day, R. S., & Fridsma, D. B. (2007). Sharing detailed research data is associated with increased citation rate. PLoS ONE, 2(3), e308. http://doi.org/10.1371/journal.pone.0000308   DOI
9 SciCodes Consortium (2021). SCICODES: consortium of scientific registries and repositories. Available: https://scicodes.net/2021/04/09/welcome-to-scicodes
10 Smith, A. M., Katz, D. S., Niemeyer, K. E., & FORCE11 Software Citation Working Group. (2016). Software citation principles. PeerJ Computer Science, 2(e86). http://doi.org/10.7717/peerj-cs.86   DOI
11 Springer Nature. [n.d.]. Reporting standards and availability of data, materials, code and protocols. Available: https://www.nature.com/nature-portfolio/editorial-policies/reporting-standards
12 Yang, B., Huang, S., Wang, X., & Rousseau, R. (2018). How important is scientific software in bioinformatics research? A comparative study between international and Chinese research communities. Journal of the Association for Information Science and Technology. http://doi.org/10.1002/asi.24031   DOI
13 Park, H. & Wolfram, D. (2019). Research software citation in the Data Citation Index: current practices and implications for research software sharing and reuse. Journal of Informetrics, 13, 574-582. http://doi.org/10.1016/j.joi.2019.03.005   DOI
14 Ajiferuke, I., Lu, K., & Wolfram, D. (2010). A comparison of citer and citation-based measure outcomes for multiple disciplines. Journal of the American Society for Information Science and Technology, 61(10), 2086-2096. http://doi.org/10.1002/asi.21383   DOI
15 Allen, A. (2021). Citation method, please? A case study in astrophysics. arXiv. Available: https://arxiv.org/pdf/2111.12574.pdf
16 American Association for the Advancement of Science (2016). Science journals: editorial policies. Available: https://www.science.org/content/page/sciencejournalseditorialpolicies#research-standards
17 Astrophysics Source Code Library. [n.d.]. Welcome to the ASCL. Available: https://ascl.net
18 Bassett, P. G. (1997). Framing Software Reuse: Lessons from the Real World. Upper Saddle River: Yourdon Press.
19 Bietz, M. J., Baumer, E. P. S., & Lee, C. P. (2020). Synergizing in cyberinfrastructure development. Computer Supported Cooperative Work, 19, 245-281. http://doi.org/10.1007/s10606-010-9114-y   DOI
20 Clarivate Analytics (2020). Data Citation Index help. Available: http://images.webofknowledge.com/WOKRS517B4/help/DRCI/index.html
21 Clarivate Analytics (2021). Data Citation Index. Available: https://clarivate.com/webofsciencegroup/solutions/webofscience-data-citation-index
22 Du, C., Cohoon, J., Lopez, P., & Howison, J. (2021). Softcite dataset: a dataset of software mentions in biomedical and economic research publications. Journal of the Association for Information Science and Technology. http://doi.org/10.1002/asi.24454   DOI
23 Garcia, F., Bertoa, M. F., Calero, C., Vallecillo, A., Ruiz, F., Piattini, M., & Genero, M. (2006). Towards a consistent terminology for software measurement. Information and Software Technology, 48(8), 631-644. http://doi.org/10.1016/j.infsof.2005.07.001   DOI
24 Hannay, J. E., MacLeod, C., Singer, J., Langtangen, H. P., Pfahl, D., & Wilson, G. (2009). How do scientists develop and use scientific software? 2009 ICSE Workshop on Software Engineering for Computational Science and Engineering. Vancouver: IEEE. http://doi.org/10.1109/SECSE.2009.5069155   DOI
25 He, N. & Nahar, V. (2016). Reuse of scientific data in academic publications: an investigation of Dryad digital repository. Aslib Journal of Information Management, 68(4), 478-494. http://doi.org/10.1108/AJIM-01-2016-0008   DOI
26 Henry, V., Bandrowski, A. E., Pepin, A.-S., Gonzalez, B. J., & Desfeux, A. (2014). OMICtools: an informative directory for multi-omic data analysis. Database, 2014, 1-5. http://doi.org/10.1093/database/bau069   DOI
27 FAIR for Research Software Working Group (2021). FAIR for research software (FAIR4RS) WG. Available: https://www.rd-alliance.org/groups/fair-4-research-software-fair4rs-wg
28 Howison, J. & Herbsleb, J. D. (2011). Scientific software production: incentives and collaboration. Proceedings of the ACM 2011 Conference on Computer Supported Cooperative Work, 513-522. http://doi.org/10.1145/1958824.1958904   DOI
29 Hwang, L., Pauloo, R., & Carlen, J. (2020). Assessing the impact of outreach through software citation for community software in geodynamics. Computing in Science & Engineering, 22(1), 16-25. http://doi.org/10.1109/MCSE.2019.2940221   DOI
30 Keswani, R., Joshi, S., & Jatain, A. (2014). Software reuse in practice. Proceedings of the Fourth International Conference on Advanced Computing & Communication Technologies, 159-162. http://doi.org/10.1109/Acct.2014.57   DOI
31 American Astronomical Society (2016). Policy statement on software. Available: https://journals.aas.org/news/policy-statement-on-software
32 Lu, K., Ajiferuke, I., & Wolfram, D. (2014). Extending citer analysis to journal impact evaluation. Scientometrics, 100(1), 245-260. http://doi.org/10.1007/s11192-014-1274-y   DOI
33 Makitalo, N., Taivalsaari, A., Kiviluoto, A., & Capilla, R. (2020). On opportunistic software reuse. Computing, 102, 2385-2408. http://doi.org/10.1007/s00607-020-00833-6.   DOI
34 Nangia, U. & Katz, D. S. (2017). Track 1 paper: surveying the U.S. national postdoctoral association regarding software use and training in research. Workshop on Sustainable Software for Science: Practice and Experiences. http://doi.org/10.5281/zenodo.814220   DOI
35 Pan, X., Yan, E., Cui, M., & Hua, W. (2018). Examining the usage, citation, and diffusion patterns of bibliometric mapping software: a comparative study of three tools. Journal of Informetrics, 12(2), 481-493. http://doi.org/10.1016/j.joi.2018.03.005   DOI
36 Pan, X., Yan, E., Wang, Q., & Hua, W. (2015). Assessing the impact of software on science: a bootstrapped learning of software entities in full-text papers. Journal of Informetrics, 9(4), 860-871. http://doi.org/10.1016/j.joi.2015.07.012   DOI
37 Goble, C. (2014). Better software, better research. IEEE Internet Computing, 18(5), 4-8. http://doi.org/10.1109/MIC.2014.88   DOI
38 Henry, E. & Faller, B. (1995). Large-scale industrial reuse to reduce cost and cycle time. IEEE Software, 12(5), 47-53. http://doi.org/10.1109/52.406756   DOI
39 Howison, J. & Bullard, J. (2016). Software in the scientific literature: problems with seeing, finding, and using software mentioned in the biology literature. Journal of the Association for Information Science and Technology, 67(9), 2137-2155. http://doi.org/10.1002/asi.23538   DOI
40 Li, K., Lin, X., & Greenberg, J. (2016). Software citation, reuse and metadata considerations: an exploratory study examining LAMMPS. Proceedings of the 82nd Annual Meeting of the Association for Information Science and Technology, 1-10. http://doi.org/10.1002/pra2.2016.14505301072   DOI
41 Malone, J., Brown, A., Lister, A. L., Ison, J. Hull, D., Parkinson, H., & Stevens, R. (2014). The software ontology (SWO): a resource for reproducibility in biomedical data analysis, curation and digital preservation. Journal of Biomedical Semantics, 5(25). http://doi.org/10.1186/2041-1480-5-25   DOI
42 Pan, X., Yan, E., & Hua, W. (2016). Disciplinary differences of software use and impact in scientific literature. Scientometrics, 109, 1593-1610. http://doi.org/s11192-016-2138-4   DOI
43 Hong, N. C. (2014). Minimal information for reusable scientific software. Proceedings of the 2nd Workshop on Working towards Sustainable Scientific Software. Available: http://www.research.ed.ac.uk/portal/files/16773670/MinimalInfoScientificSoftware.pdf