Data sprints are interdisciplinary collaborative environments in which a set of questions is addressed and attempted to be responded to with online data and quali-quanti methods. It is an activity well-known within the digital methods community, but its purpose, advantages and concrete results are still little known across fields of study. In this paper we present four facets about and deriving from data sprints to explain their prospects for different (non-) academic communities:
- Data sprints as a means of teaching-learning digital methods research
- Data sprints as a space for methods and tools creation
- Data sprints as a reflective tool to understand the triad of data-, software- and platform-oriented research (from the standpoint of practice).
- Data sprints for producing scientific knowledge
We start with a definition of 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. This is the type of publication thought to contribute to the literature about digital methods research. The reader will learn not only what data sprints are (definition, characteristics and format) but she will also understand what happens before, during and after a data sprint. It is a piece written in four hands by Lorena Cano-Orón, Beatrice Gobbo, Ana Marta Flores and myself. We took advantage of our experience as organizers, collaborators and participants in several data sprints. We hope this paper can serve the academic and non-academic community as a guideline to practically grasp the data sprint proposal and its four purposes listed above.
The paper is part of the Revista Dígitos special issue – The Data Sprint Approach to Research: Experiments, Protocols and Knowledge, and is available in English and Spanish. Links and abstracts are below.
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.
KEYWORDS
data sprint, digital methods, science production, data analysis, data visualisation, interdisciplinary
research
How to cite this article:
Omena, J. J.; Cano-Orón, L.; Gobbo, B. & Flores, A. M. (2022). What are data sprints for?. Dígitos. Revista de Comunicación Digital, 8: 9-30. DOI: 10.7203/drdcd.v1i8.253
¿Para qué sirven los data sprints?
RESUMEN
El método data sprint permite varios objetivos para la comunidad de métodos digitales, desde el fomento de la colaboración interdisciplinaria hasta la provisión de espacios de enseñanza-aprendizaje en relación con los diseños metodológicos creativos. Sin embargo, el propósito, las ventajas y los resultados concretos de los data sprints son todavía poco conocidos en todas las disciplinas. Este artículo presents cuatro facetas que pertenecen y se derivan de esta metodología de trabajo para explicar sus perspectivas para diferentes comunidades (no) académicas. En primer lugar, definimos el método de los data sprints, proporcionando una descripción detallada de lo que son y lo que implican en la práctica y, a su vez, proponemos una guía para facilitar la replicabilidad de este método de trabajo. En segundo lugar, exponemos cómo los data sprints son: (1) un medio de enseñanza y aprendizaje de la investigación de métodos digitales, argumentando que el entorno de los data sprints no es sólo (2) un espacio para la creación de métodos y herramientas, sino también (3) una herramienta de reflexión para entender la tríada de la investigación orientada a los datos, el software y la plataforma, desde el punto de vista de la práctica. Por lo tanto, los data sprints ofrecen a los investigadores formas delimitadas de acceder y criticar la producción de conocimiento científico. Finalmente, abordamos un procedimiento estándar posterior al sprint: (4) la reutilización de los informes del data sprint para producir conocimiento científico, a través de publicaciones académicas y no académicas, como una práctica de investigación establecida. Estas cuatro dimensiones desvelan el enfoque del data sprint para un público más amplio, a la vez que indican las posibles conclusiones durante y después de tales eventos. Concluimos con reflexiones procedentes de los data sprints y sobre ellos.
PALABRAS CLAVE
data sprint, métodos digitales, producción científica, análisis de datos, visualización de datos,
investigación interdisciplinar
Cómo citar este artículo:
Omena, J. J.; Cano-Orón, L.; Gobbo, B. y Flores, A. M. (2022). What are data sprints for?. Dígitos. Revista de Comunicación Digital, 8: 9-30. DOI: 10.7203/drdcd.v1i8.253
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