Deliberate Individual Change Framework for Understanding Programming Practices in four Oceanography Groups

Abstract

Computing affects how scientific knowledge is constructed, verified, and validated. Rapid changes in hardware capability, and software flexibility, are coupled with a volatile tool and skill set, particularly in the interdisciplinary scientific contexts of oceanography. Existing research considers the role of scientists as both users and producers of code. We focus on how an intentional, individually-initiated but socially-situated, process of uptake influences code written by scientists. We present an 18-month interview and observation study of four oceanography teams, with a focus on ethnographic shadowing of individuals undertaking code work. Through qualitative analysis, we developed a framework of deliberate individual change, which builds upon prior work on programming practices in science through the lens of sociotechnical infrastructures. We use qualitative vignettes to illustrate how our theoretical framework helps to understand changing programming practices. Our findings suggest that scientists use and produce software in a way that deliberately mitigates the potential pitfalls of their programming practice. In particular, the object and method of visualization is subject to restraint intended to prevent accidental misuse.

This is a preview of subscription content, log in to check access.

Figure 1
Figure 2.

Notes

  1. 1.

    “Part of the integrated global observation strategy,” a project that now offers 15 years of global float

    data. See http://www.argo.ucsd.edu/

References

  1. Barter, Christine; and Emma Renold (2000). 'I wanna tell you a story': Exploring the Application of Vignettes in Qualitative Research with Children and Young People. International Journal of Social Research Methodology , vol. 3, no. 4, pp. 307–323.

  2. Button, Graham; and Wes Sharrock (1994). Occasioned Practices in the Work of Software Engineers. In M. Jirotka and J. A. Goguen (eds.): Requirements Engineering. pp. 217–240. San Diego, California: Academic Press Professional, Inc.

  3. Carver, Jeffrey C.; Richard P. Kendall; Susan E. Squires; and Douglass E. Post (2007). Software Development Environments for Scientific and Engineering Software: A Series of Case Studies. In ICSE 2007:  29 th International Conference on Software Engineering, 2007. Minneapolis, MN, 19–May 27 May 2007. IEEE, pp. 550–559.

  4. Chen, Nan-Chen; Sarah Poon; Lavanya Ramakrishnan; and Cecilia R. Aragon (2016). Considering Time in Designing Large-Scale Systems for Scientific Computing. In CSCW 2016:  Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, San Francisco, CA, USA, 27 February – 2 March 2016. ACM Press, pp. 1535–1547.

  5. De Souza, Cleidson; Jon Froehlich; and Paul Dourish (2005). Seeking the Source: Software Source Code as a Social and Technical Artifact. In GROUP 2005:  Proceedings of the 2005 International ACM SIGGROUP Conference on Supporting Group Work, Sanibel Island, FL, USA, 6–9 November 2005. ACM Press, pp. 197–206.

  6. Easterbrook, Steve M.; and Timothy C. Johns (2009). Engineering the Software for Understanding Climate Change. Computing in Science & Engineering, vol. 11, no. 6, pp. 64–74.

  7. Edwards, Paul N. (2010). A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming . Cambridge: The MIT Press.

  8. Gilbert, John K. (2005). Visualization: A Metacognitive Skill in Science and Science Education. In J. K. Gilbert (ed): Visualization in Science Education, pp. 9–27. Dordrecht: Springer Netherlands.

  9. Hannay, Jo Erskine; Carolyn MacLeod; Janice Singer; Hans Petter Langtangen; Dietmar Pfahl; and Greg Wilson (2009). How do Scientists Develop and Use Scientific Software?. In SECSE'09:  Proceedings of the 2009 ICSE Workshop on Software Engineering for Computational Science and Engineering, 23 May 2009. IEEE, pp. 1–8.

  10. Heaton, Dustin; and Jeffrey C. Carver. (2015). Claims About the Use of Software Engineering Practices in Science: A Systematic Literature Review. Information and Software Technology, vol. 67, no. C, pp. 207–219.

  11. Howe, Bill; Peter Lawson; Renee Bellinger; Erik Anderson; Emanuele Santos; Juliana Freire; Carlos Scheidegger; António Baptista; and Cláudio Silva (2008). End-to-end eScience: Integrating Workflow, Query, Visualization, and Provenance at an Ocean Observatory. In IEEE Fourth International Conference on eScience, Indianapolis, Indiana, USA, 10–12 December 2008. IEEE, pp. 127–134.

  12. Jackson, Steven J. (2014). Rethinking Repair. In T. Gillespie, P. J. Boczkowski and K. A. Foot (eds.): Media Technologies: Essays on Communication, Materiality, and Society, pp. 221–39. Cambridge: The MIT Press.

  13. Jackson, Steven J.; and Sarah Barbrow. (2013). Infrastructure and Vocation: Field, Calling and Computation in Ecology. In CHI 2013:  Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, France, 27 April – 2 May 2013. ACM Press, pp. 2873–2882.

  14. Kelly, Diane (2015). Scientific Software Development Viewed as Knowledge Acquisition: Towards Understanding the Development of Risk-Averse Scientific Software. Journal of Systems and Software, vol. 109, no. C, pp. 50-61.

  15. Kunzig, Robert (2000). Mapping the Deep: The Extraordinary Story of Ocean Science. New York: WW Norton & Company.

  16. Latour, Bruno; and Steven Woolgar (1979). Laboratory Life: The Construction of Scientific Facts. Princeton: Princeton University Press.

  17. Leach, James; Dawn Nafus; and Bernhard Krieger (2009). Freedom Imagined: Morality and Aesthetics in Open Source Software Design. Ethnos. vol. 74, no. 1, pp. 51-71.

  18. Lee, Charlotte P.; Paul Dourish; and Gloria Mark (2006). The Human Infrastructure of Cyberinfrastructure. In CSCW 2006:  Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work, Banff, Canada, 6–8 November 2006. ACM Press, pp. 483–492.

  19. Lieberman, Henry; Fabio Paternò; Markus Klann; and Volker Wulf (2006). End-User Development: An Emerging Paradigm. In H. Lieberman, F. Paternò, V. Wulf (eds.):  End-User Development, pp. 1–8. Dordrecht: Springer Netherlands.

  20. Miles, Matthew B.; A. Michael Huberman; and Johnny Saldaña (2013). Qualitative Data Analysis: A Methods Sourcebook. Washington DC: SAGE Publications.

  21. Mislan, K. A. S.; Jeffrey M. Heer; and Ethan P. White (2016). Elevating the Status of Code in Ecology. Trends in Ecology & Evolution, vol. 31, no. 1, pp. 4–7.

  22. Orlikowski, Wanda J (2006). Material Knowing: The Scaffolding of Human Knowledgeability. European Journal of Information Systems, vol. 15, no. 5, pp. 460–466.

  23. Paine, Drew; and Charlotte P. Lee (2014). Producing Data, Producing Software: Developing a Radio Astronomy Research Infrastructure. In IEEE 10th International Conference on e-Science, 20–24 October 2014, vol. 1, pp. 231–238.

  24. Pipek, Volkmar; and Volker Wulf (2009). Infrastructuring: Toward an Integrated Perspective on the Design and Use of Information Technology. Journal of the Association for Information Systems, vol. 10. no. 5, pp. 447–473.

  25. Ribes, David; and Thomas A. Finholt (2009). The Long Now of Technology Infrastructure: Articulating Tensions in Development. Journal of the Association for Information Systems, vol. 10, no. 5, pp. 375–398.

  26. Rönkkö, Kari; Yvonne Dittrich; and Dave Randall (2005). When Plans Do Not Work Out: How Plans are Used in Software Development Projects. Computer Supported Cooperative Work (CSCW), vol. 14, no. 5, pp. 433–468.

  27. Segal, Judith (2007). Some Problems of Professional End User Developers. In P. Cox and J. Hosking (eds.): Visual Languages and Human-Centric Computing, Coeur d'Alene, ID, USA, 23–27 September 2007. IEEE, pp. 111–118.

  28. Sletholt, Magnus Thorstein; Jo Hannay; Dietmar Pfahl; Hans Christian Benestad; and Hans Petter Langtangen (2011). A Literature Review of Agile Practices and Their Effects in Scientific Software Development. In Proceedings of the 2011 ICSE Workshop on Software Engineering for Computational Science and Engineering, Waikiki, Honolulu, HI, USA, 21–28 May 2011. ACM Press, pp. 1–9.

  29. Star, Susan Leigh; and Karen Ruhleder (1996). Steps Toward an Ecology of Infrastructure: Design and Access for Large Information Spaces. Information Systems Research, vol. 7, no. 1, pp. 111–134.

  30. Steinhardt, Stephanie B. (2016). Breaking Down While Building Up: Design and Decline in Emerging Infrastructures. In CHI 2016:  Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, San Jose, CA, USA, 7–12 May 2016. ACM Press, pp. 2198–2208.

  31. Steinhardt, Stephanie B.; and Steven J. Jackson (2015). Anticipation Work: Cultivating Vision in Collective Practice. In CSCW 2015: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, Vancouver, BC, Canada, 14–18 March 2015. ACM Press, pp. 443–453.

  32. Suchman, Lucy (2002). Located Accountabilities in Technology Production. Scandinavian Journal of Information Systems, vol. 14, no. 2, p. 7.

  33. Trainer, Erik H.; Chalalai Chaihirunkarn; Arun Kalyanasundaram; and James D. Herbsleb (2015). From Personal Tool to Community Resource: What's the Extra Work and Who Will Do It?. In CSCW 2015: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, Vancouver, BC, Canada, 14–18 March 2015. ACM Press, pp. 417–430.

  34. Traweek, Sharon (2009). Beamtimes and Lifetimes. Cambridge: Harvard University Press.

  35. Truex, Duane; Richard Baskerville; and Julie Travis (2000). Amethodical Systems Development: The Deferred Meaning of Systems Development Methods. Accounting, Management and Information Technologies, vol. 10, no. 1, pp. 53–79.

  36. Wilson, Greg; Dhavide A. Aruliah; C. Titus Brown; Neil P. Chue Hong; Matt Davis; Richard T. Guy; Steven H. D. Haddock; Kathryn D. Huff; Ian M. Mitchell; Mark D. Plumbley; Ben Waugh; Ethan P. White; and Paul Wilson (2014). Best Practices for Scientific Computing. PLoS Biology, vol. 12, no. 1, e1001745.

  37. Yeh, Ron B.; and Scott Klemmer (2004). Field Notes on Field Notes: Informing Technology Support for Biologists. Stanford University, California: Stanford InfoLab.

  38. Young, Alyson L.; and Wayne G. Lutters (2015). (Re) defining Land Change Science through Synthetic Research Practices. In CSCW 2015: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, Vancouver, BC, Canada, 14–18 March 2015. ACM Press, pp. 431–442.

Download references

Acknowledgments

This work was supported by grants from the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation awarded to Professor Cecilia Aragon; and by NSF Graduate Research Fellowship and AT&T Graduate Research Fellowship awarded to Kateryna Kuksenok. NSF awards IIS-0954088 and NSF ACI-1302272 awarded to Prof. Charlotte P. Lee supported supplementary data used for the beginning of the study. We would like to thank Emmerline Wu and Madeline Wood, who assisted with gathering observational data from meetings. We would also like to thank the study participants for their time, energy, and goodwill.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Kateryna Kuksenok.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kuksenok, K., Aragon, C., Fogarty, J. et al. Deliberate Individual Change Framework for Understanding Programming Practices in four Oceanography Groups. Comput Supported Coop Work 26, 663–691 (2017). https://doi.org/10.1007/s10606-017-9285-x

Download citation

Keywords

  • Scientific software
  • Programming practice
  • Data science
  • Oceanography
  • Qualitative analysis
  • Sociotechnical infrastructure
  • Software engineering