Data Sprint Learning. Exercising Proximity to Data in Teaching Situations




This paper reports on a data sprint conducted as part of a PhD course on digital methods and data critique at the University of Klagenfurt. We reflect on how our data sprint contributed to this higher educational setting, and point to ways in which the data sprint method can be developed further based on our experience. The paper discusses how the sprint fabricated a moment of “critical proximity” for students that were mainly working with qualitative social science methods. The data sprint allowed them to put their critique on “big data” into practice by working with selected sets of data from Twitter and Scopus. We reflect on our collective experience and draw conclusions on the use of data sprints in teaching. Data sprints encourage us to engage with feelings of being underwhelmed and overwhelmed by data that provoke our social science way of critique. Our data sprint tangibly demonstrates that data work is in fact “messy”: transgressing ideals of good data management, biased, ambiguous and open-ended. But instead of turning away from this “wildness”, we urge to make use of it in teaching settings. This wildness allows to step out of conventional modes of critique, and into modes of action. We conclude with a protocol as a practical guide for everyone who wants to introduce data sprints in their teaching.


CAT Capture and Analysis Toolkit [Computer software]. (2021). OILab and Digital Methods Initiative at the University of Amsterdam. Retrieved from

Agre, P., Toward a Critical Technical Practice: Lessons Learned in Trying to Reform AI. In Bowker, Geoffrey, ed. (1997). Social Science, Technical Systems and Cooperative Work: Beyond The Great Divide. USA: L. Erlbaum Associates Inc. ISBN 978-0-8058-2403-2.

Ballestero, A., Winthereik B. (2021). Experimenting with Ethnography. A Companion to Analysis. Duke University Press.

Bastian M., Heymann S., Jacomy M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media.

Berry, D. M., Borra, E., Helmond, A., Plantin, J. C., & Rettberg, J. W. (2015). The data sprint approach: exploring the field of Digital Humanities through Amazon’s application programming interface. Digital Humanities Quarterly, 9(4).

Birkbak, A., Petersen, M. K., & Elgaard Jensen, T. (2015). Critical proximity as a methodological move in techno-anthropology. Techné: Research in Philosophy and Technology, 19(2), 266-290.

Borgman, C. L., Scharnhorst, A., & Golshan, M. S. (2019). Digital data archives as knowledge infrastructures: Mediating data sharing and reuse. Journal of the Association for Information Science and Technology, 70(8), 888-904.

Bowker, G. C. (2009). Memory Practices in the Sciences. MIT Press

Corti, L., Van den Eynden, V., Bishop, L., & Woollard, M. (2019). Managing and sharing research data: a guide to good practice. Sage.

Criado Perez, C. (2019) Invisible Women. Exposing Data Bias in World Designed for Men. Vintage Books.

Cunningham, W. (1992). The WyCash Portfolio Management System. OOPSLA ‘92. Accessed 1 November 2021.

Gitelman, L. and Jackson, V. Introduction. In Gitelman, L. (ed.) (2013). “Raw Data” is an Oxymoron. MIT Press.

Godfrey-Smith, P. (2003). Theory and Reality. An Introduction to the Philosophy of Science. Chicago: University of Chicago Press.

Haraway, D. (1988). Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective. Feminist Studies, 14(3), 575–599.

Haraway, D. (2016). Staying with the trouble: Making Kin in the Chthulucene. Duke University Press.

Herbrechter, S. (2017) Critical proximity, Journal for Cultural Research, 21:4, 323-336, DOI: 10.1080/14797585.2017.1370485

Hutchins, E. (1995). Cognition in the Wild. MIT Press.

Jacomy, M. (2021). Situating Visual Network Analysis. Aalborg Universitetsforlag. Aalborg Universitet. Det Humanistiske Fakultet. Ph.D.-Serien

Jensen, T. E. (2020). Exploring the Trading Zones of Digital STS. STS Encounters - DASTS working paper series, 11(1), 89-116.

Jensen, T. E., Birkbak, A., Madsen, A. K., & Munk, A. K. (2021). Participatory Data Design: Acting in a digital world. In Making and Doing STS. MIT Press.

Latour, B. (1987). Science in Action: How to Follow Scientists and Engineers Through Society. Harvard University Press. ISBN 0-674-79291-2

Latour, B. (2004). Why has critique run out of steam? From matters of fact to matters of concern. Critical Inquiry, 30(2), 225-248.

Latour, B. (2005). Reassembling the Social. An Introduction to Actor-Network Theory. Oxford University Press.

Law, J. (2011). Heterogeneous Engineering and Tinkering. Accessed 1 November 2021.

Levin, N., & Leonelli, S. (2017). How Does One "Open" Science? Questions of Value in Biological Research. Science, Technology & Human Values, 42(2), 280–305.

Loukissas, Y. A. (2019). All data are local: Thinking critically in a data-driven society. MIT Press.

Marres N. (2015). Why Map Issues? On Controversy Analysis as a Digital Method. Science, Technology, & Human Values, 40(5):655-686. doi:10.1177/0162243915574602

Meldgaard Kjær, K., Ojala, M., Henriksen, L. (2021). Absent Data: Engagements with Absence in a Twitter Collection Process. Catalyst, 7(2).

Mol, A., Moser, I. and Pols, J. (eds) (2010). Care in Practice: on Tinkering in Clinics, Homes and Farms. Transcript verlag, Bielefeld.

Munk, A. (2001). The digital minced meat. EASST Review. 40(1).

Munk, A. K., Tommaso, V., & Meunier, A. (2019a). Data Sprints: A Collaborative Format in Digital Controversy Mapping. In J. Vertesi, & D. Ribes (red.), Digital STS: A Field Guide for Science & Technology Studies (s. 472-496). Princeton University Press.

Munk, A. K., Madsen, A. K., & Jacomy, M. (2019b). Thinking Through The Databody: Sprints as Experimental Situations. In Å. Mäkitalo, T. Nicewonger, & M. Elam (Eds.), Designs for Experimentation and Inquiry: Approaching Learning and Knowing in Digital Transformation (1 ed., pp. 110-128). Routledge.

Omena, J. J., Rabello, E. T., & Mintz, A. G. (2020). Digital Methods for Hashtag Engagement Research. Social Media and Society, 6(3), 1-18.

Parack, S. (2021). Introducing the new Academic Research product track. Twitter Developer forum. Retrieved from

Pearce, W., Özkula, S. M., Greene, A. K., Teeling, L., Bansard, J. S., Omena, J. J., & Rabello, E. T. (2020). Visual cross-platform analysis: digital methods to research social media images. Information Communication and Society, 23(2), 161-180.

Prainsack, B., & Leonelli, S. (2018). " Responsibility". In Science and the politics of openness. Manchester, England: Manchester University Press. Retrieved Dec 22, 2021, from

Puig de la Bellacasa, M. (2017). Matters of care: Speculative ethics in more than human worlds. University of Minnesota Press.

Rogers, R. (2013). Digital Methods. MIT Press.

Rogers, R. (2019). Doing Digital Methods. Sage.

Rogers. Y. (2011). Interaction design gone wild: striving for wild theory. Interactions. 18(4)

Sanderhoff, M. (ed.). (2014). Sharing is Caring. Openness and Sharing in the Cultural Sector. Statens Museum for Kunst. Copenhagen, Denmark.

Star, S., Griesemer, J. (1989). Institutional Ecology, 'Translations' and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertebrate Zoology, 1907-39. Social Studies of Science. 19 (3): 387–420. DOI:

Sørensen, E. (2009). The Materiality of Learning: Technology and Knowledge in Educational Practice (Learning in Doing: Social, Cognitive and Computational Perspectives). Cambridge: Cambridge University Press. DOI:

Sørensen, E. and Kocksch, L. (2021). Data Durabilities: Towards Conceptualizations of Scientific Long-Term Data Storage. Engaging Science, Technology, and Society. 7(1): 12-32. DOI:

Venturini, T., Bounegru, L., Gray, J., & Rogers, R. (2018a). A reality check(list) for digital methods. New Media & Society. 20(11): 4195-4217. DOI:

Venturini, T., Munk, A., & Meunier, A. (2018b). Data-Sprinting: a Public Approach to Digital Research. In: Celia Lury; Rachel Fensham; Alexandra Heller-Nicholas. Routledge handbook of interdisciplinary research methods, Routledge, Routledge international handbooks, 978-1-138-88687-2. ff10.4324/9781315714523-24ff. Ffhal-01672288f

Venturini, T., & Munk, A. K. (2021). Controversy Mapping: A Field Guide. John Wiley & Sons.

Verran, H. (2001). Science and an African logic. University of Chicago Press.