The Politics of Data Portals in Inter- And Transdisciplinary Research

Maximiliano Vila Seoane, Anna-Katharina Hornidge


In this paper, we argue that the ongoing processes of datafication and dataism are constraining initiatives to construct open data portals contributing to inter- and transdisciplinary research. The former overvalues quantitative data, whereas the latter reinforces the belief that ‘raw data’ is neutral and apolitical, ignoring how data is processed. Based on the case study of an open data portal being developed at an inter- and transdisciplinary research institute, we argue that datafication and dataism are highly problematic trends, because they marginalize qualitative data employed in critical, constructivist, and other interpretive methods, thereby limiting the possibility of complementing and extending each other. Nonetheless, we also maintain that these trends are not technologically determined but are modifiable, based on the design of data portals. Accordingly, we conclude by offering suggestions for constructing data portals, such as opening up the design process and democratizing standards.


Datafication; dataism; transdisciplinary research; data portal; standards

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Baack, S. (2015). Datafication and empowerment: How the open data movement re-articulates notions of democracy, participation, and journalism. Big Data & Society, 2(2), 1–11.

Baker, M. (2016). Is there a reproducibility crisis? Nature, 533(7604), 452–454.

Bijker, W. E. (2010). How is technology made?-that is the question! Cambridge Journal of Economics, 34(1), 63–76.

Bijker, W. E., Hughes, T. P., & Pinch, T., eds. (2012). The social construction of technological systems (anniversary edition). Cambridge, Massachusetts, USA: The MIT Press.

Bowker, G. C., & Star, S. L. (1996). How things (actor-net)work: classification, magic and ubiquity of standards. Philosophia, 25(3-4), 195–220.

Boyd, D., & Crawford, K. (2012). Critical questions for big data. Information, Communication & Society, 15(5), 662–679.

Carrigan, M. (2015). Emma Uprichard: Most big data is social data – the analytics need serious interrogation. Retrieved January 10, 2016, from The Impact Blog. The London School of Economics and Political Science website:

Doolin, B., & McLeod, L. (2012). Sociomateriality and boundary objects in information systems development. European Journal of Information Systems, 21(5), 570–586.

Gilpin, R. (2001). Global Political Economy. Understanding the international economic order. New Jersey, USA: Princeton University Press.

Gitelman, L., & Jackson, V. (2013). Introduction. In “ Raw Data ” Is an Oxymoron (pp. 1–14). Cambridge, Massachusetts, USA: The MIT Press.

Guba, E. G., & Lincoln, Y. S. (1994). Competing paradigms in qualitative research. In N. K. Denzin & Y. S. Lincoln, Handbook of qualitative research (pp. 105–117). Thousand Oaks, CA: SAGE.

Heuser, R., & Le-Khac, L. (2011). Learning to read data: bringing out the humanistic in the digital humanities. Victorian Studies, 54(1), 79–86.

International Open Data Charter. (2015). International Open Data Charter (p. 7).

Jahn, T., Bergmann, M., & Keil, F. (2012). Transdisciplinarity: between mainstreaming and marginalization. Ecological Economics, 79(C), 1–10.

Kim, Y., & Adler, M. (2015). Social scientists’ data sharing behaviors: Investigating the roles of individual motivations, institutional pressures, and data repositories. International Journal of Information Management, 35(4), 408–418.

Klein, J. T. (2017). Typologies of interdisciplinarity: the boundary work of definition. In R. Frodeman, J. T. Klein, C. Mitcham, & J. B. Holbrook (Eds.), The Oxford Handbook of Interdisciplinarity (pp. 21–34). Oxford University Press.

Lowe, P., Phillipson, J., & Lee, R. P. (2008). Socio-technical innovation for sustainable food chains: roles for social science. Trends in Food Science & Technology, 19(5), 226–233.

Lycett, M. (2013). “Datafication”: making sense of (big) data in a complex world. European Journal of Information Systems, 22(4), 381–386.

Mayer-Schönberger, V., & Cukier, K. (2013). Big data. A revolution that will transform how we live, work and think. New York, USA: Houghton Mifflin Hartcourt Publishing Company.

Mollinga, P. P. (2010). Boundary work and the complexity of natural resources management. Crop Science, 50(1), 1–9.

Nahuis, R., & van Lente, H. (2008). Where are the politics? Perspectives on democracy and technology. Science, Technology & Human Values, 33(5), 559–581.

O’Rourke, M., & Crowley, S. J. (2013). Synthese, 190(11), 1937–1954.

Parry, O., & Mauthner, N. S. (2004). Whose data are they anyway? practical, legal and ethical issues in archiving qualitative research data. Sociology, 38(1), 139–152.

Petts, J., Owens, S., & Bulkeley, H. (2008). Crossing boundaries: interdisciplinarity in the context of urban environments. Geoforum, 39(2), 598–601.

Phoenix, C., Osborne, N., Redshaw, C., Moran, R., Stahl-Timmins, W., Depledge, M., … Wheeler, B. W. (2013). Paradigmatic Approaches to Studying Environment and Human Health. Environmental Science and Policy, 25(11), 218–228.

Pohl, C. (2011). What is progress in transdisciplinary research? Futures, 43(6), 618–626.

Redclift, M. (1998). Interdisciplinary research on the global environment. Global Environmental Change, 8(3), 177–182.

Rosendahl, J., Zanella, M., Rist, S., & Weigelt, J. (2015). Scientists’ situated knowledge: strong objectivity in transdisciplinarity. Futures, 65, 17–27.

Sayer, A. (2010). Method in social science. A realist approach. (Second). Abingdon, Oxon, UK: Routledge.

Science International. (2015). Open data in a big data world. An international accord. (p. 15) [International accord]. Paris, France: International Council for Science (ICSU), International Social Science Council (ISSC), The World Academy of Sciences (TWAS), InterAcademy Partnership (IAP).

Snow, C. P. (2012). The two cultures. In Canto Classics. Cambridge, UK: Cambridge University Press.

Star, S. L. (2010). This is Not a Boundary Object: Reflections on the Origin of a Concept. Science, Technology & Human Values, 35(5), 601–617.

Star, S. L., & Griesemer, J. R. (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.

Strang, V. (2009). Integrating the social and natural sciences in environmental research: a discussion paper. Environment, Development and Sustainability, 11(1), 1–18.

Van Dijck, J. (2014). Datafication, dataism and dataveillance: big data between scientific paradigm and ideology. Surveillance & Society, 12(2), 197–208.

Van Dijck, J., & Poell, T. (2013). Understanding Social media logic. Media and Communication, 1(1), 2–14.

Wendt, A. (1999). Social Theory of International Politics. Cambridge, UK: Cambridge university press.

Williams, R., & Edge, D. (1996). The social shaping of technology. Research Policy, 25, 865–899.

Winner, L. (1980). Do Artifacts Have Politics? Daedalus, 109(1), 121–136.