Understanding Hackathons for Science: Collaboration, Affordances, and Outcomes

  • Ei Pa Pa Pe-ThanEmail author
  • James D. Herbsleb
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11420)


Nowadays, hackathons have become a popular way of bringing people together to engage in brief, intensive collaborative work. Despite being a brief activity, being collocated with team members and focused on a task—radical collocation—could improve collaboration of scientific software teams. Using a mixed-methods study of participants who attended two hackathons at Space Telescope Science Institute, we examined how hackathons can facilitate collaboration in scientific software teams which typically involve members from two different disciplines: science and software engineering. We found that hackathons created a focused interruption-free working environment in which team members were able to assess each other’s skills, focus together on a single project and leverage opportunities to exchange knowledge with other collocated participants, thereby allowing technical work to advance more efficiently. This study suggests “hacking” as a new and productive form of collaborative work in scientific software production.


Hackathons Time-bounded events Collaboration Coordination Collocation Scientific software development 


  1. 1.
    Bos, N., et al.: From shared databases to communities of practice: a taxonomy of collaboratories. J. Comput.-Mediat. Commun. 12, 652–672 (2007)CrossRefGoogle Scholar
  2. 2.
    Corbin, J., Strauss, A.: Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, 4th edn. SAGE Publications Inc., Thousand Oaks (2014)Google Scholar
  3. 3.
    Crowston, K., Howison, J., Masango, C., Eseryel, Y.: Face-to-face interactions in self-organizing distributed teams. In: Presentation at the OCIS Division, Academy of Management Conference (2005).
  4. 4.
    Greeno, J.G.: Gibson’s affordances. Psychol. Rev. 101(2), 336–342 (1994)CrossRefGoogle Scholar
  5. 5.
    Hatton, L., Roberts, A.: How accurate is scientific software? IEEE Trans. Software Eng. 20, 785–797 (1994)CrossRefGoogle Scholar
  6. 6.
    Heaton, D., Carver, J.C.: Claims about the use of software engineering practices in science: a systematic literature review. Inf. Softw. Technol. 67, 207–219 (2015). CarverCrossRefGoogle Scholar
  7. 7.
    Henderson, S.: Getting the most out of hackathons for social good. In: Rosenthal, R.J. (ed.) Volunteer Engagement 2.0: Ideas and Insights Changing the World, pp. 182–194 (2015)Google Scholar
  8. 8.
    Hinds, P.J., Cramton, C.D.: Situated coworker familiarity: how site visits transform relationships among distributed workers. Organ. Sci. 25, 794–814 (2013)CrossRefGoogle Scholar
  9. 9.
    Howison, J., Herbsleb, J.D.: Scientific software production: incentives and collaboration. In: The ACM 2011 Conference on Computer Supported Cooperative Work, pp. 513–522. ACM, New York (2011)Google Scholar
  10. 10.
    Kelly, D.: Scientific software development viewed as knowledge acquisition: towards understanding the development of risk-averse scientific software. J. Syst. Softw. 109, 50–61 (2015)CrossRefGoogle Scholar
  11. 11.
    Komssi, M., Pichlis, D., Raatikainen, M., Kindström, K., Järvinen, J.: What are hackathons for? IEEE Softw. 32, 60–67 (2015)CrossRefGoogle Scholar
  12. 12.
    Kraut, R.E., Streeter, L.A.: Coordination in large scale software development. Commun. ACM 38, 69–81 (1995)CrossRefGoogle Scholar
  13. 13.
    Möller, S., et al.: Community-driven development for computational biology at sprints, hackathons and codefests. BMC Bioinf. 15, S7 (2014)CrossRefGoogle Scholar
  14. 14.
    Olson, G.M., Olson, J.S.: Distance matters. Hum.-Comput. Interact. 15, 139–178 (2000)CrossRefGoogle Scholar
  15. 15.
    Paine, D., Lee, C.P.: Who has plots? Contextualizing scientific software, practice, and visualizations. ACM Hum. Comput. Interact. 1, 21 (2017). Article 85Google Scholar
  16. 16.
    Segal, J.: Scientists and software engineers: a tale of two cultures. In: The 20th Annual Meeting of the Psychology of Programming Interest Group, PPIG 2008, University of Lancaster, UK (2008)Google Scholar
  17. 17.
    Stoltzfus, A., et al.: Community and code: nine lessons from nine NESCent Hackathons. F1000Research 6 (2017)Google Scholar
  18. 18.
    Teasley, S., Covi, L., Krishnan, M.S., Olson, J.S.: How does radical collocation help a team succeed? In: The 2000 ACM Conference on Computer Supported Cooperative Work, pp. 339–346, ACM, New York (2000)Google Scholar
  19. 19.
    Trainer, E.H., Kalyanasundaram, A., Chaihirunkarn, C., Herbsleb, J.D.: How to hackathon: socio-technical tradeoffs in brief, intensive collocation. In: The 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, pp. 1118–1130. ACM, New York (2016)Google Scholar
  20. 20.
    Wyngaard, J., Lynch, H., Nabrzyski, J., Pope, A., Jha, S.: Hacking at the divide between polar science and HPC: using hackathons as training tools. In: 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 352–359. IEEE (2017)Google Scholar
  21. 21.
    Zhang, Z.-X., Hempel, P.S., Han, Y.-L., Tjosvold, D.: Transactive memory system links work team characteristics and performance. J. Appl. Psychol. 92, 1722 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Carnegie Mellon UniversityPittsburghUSA

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