What are data sprints for?

Abstract

The data sprint approach enables various objectives for the digital methods community, from fostering interdisciplinary collaboration to providing teaching-learning spaces regarding creative methods. However, data sprints' purpose, advantages and concrete results are still little known across disciplines. Thus, this paper presents four facets pertaining to and deriving from data sprints to explain their prospects for different (non-) academic communities. First, we define the data sprint approach, providing a detailed description of what data sprints are and what they involve in practice and, in turn, propose guidance to facilitate the replicability of this work method. Second, we elucidate how data sprints are (1) a means of teaching and learning digital methods research, arguing that the data sprint environment is not only (2) a space for methods and tools creation but also (3) a reflective tool to understand the triad of data-, software-and platform-oriented research (from the standpoint of practice). Therefore, data sprints offer researchers situational ways to access and critique scientific knowledge production. Finally, we address a standard post-sprint procedure, (4) the reutilisation of data sprint reports for producing scientific knowledge, through academic and nonacademic publications, as an established research practice. The four facets unpack the data sprint approach for a broader audience whilst indicating the possible takeaways during and after such events. We conclude with reflections from and on data sprints.