Data-Sprinting: a Public Approach to Digital Research

Résumé En

This chapter is about the politics of interdisciplinarity. Not in the sense of the research politics fostering collaboration across disciplines, but in the stronger sense of transcending disciplinary boundaries to make significant political contributions. In short: it is about making research public. To address this question, this chapter introduces (through a concrete example in climate debate research) an original research format, that we call data-sprinting. « It is controversies of this kind, the hardest controversies to disentangle, that the public is called in to judge. Where the facts are most obscure, where precedents are lacking, where novelty and confusion pervade everything, the public in all its unfitness is compelled to make its most important decisions » (Lippmann, 1925, p. 121). What's in a data-sprint Data-sprints are intensive research and coding workshops where participants coming from different academic and non-academic background convene physically to work together on a set of data and research questions. Data-sprints have their roots in a series of organizational innovation introduced in the field of open-source development at the turn of the century (as a reaction to the previsous 'waterfall approach' inherited from the engineering management – Raymond, 2001). Faced with such radical uncertainty about how their project will develop and who will join them, open-source developers invented a form of coding event called " barcamps " or " hackathons " (or hacking marathons). Such format consists of short events in which a group of developers and designers meet to work intensively and expeditiously on some digital object. The features of hackathons and barcamps fit extremely well the practice of interdisciplinary research. We appreciated in particular: 1. The heterogeneity of the actors involved. Hackathons and barcamps are generally organized as to be open to many different types of actors. In part, this comes from the need to achieve deliverable results at the end of the event, which demands to collect all the necessary competences to go through all the phases of the project. In developing marathons, this translates in having experts from the entire programming stack: from setting up the server infrastructure, to designing the wireframes, from scraping the data to implementing the front-end. The push for heterogeneity also derives from the necessity to exchange with the potential end users of the projects, who should be at hand during the developing dash.