The writing of web publications mixing data visualization and textual prose opens novel opportunities for connecting evidence, arguments and narrative in social sciences communities. Such a practice poses a variety of challenges in terms of website design and development ; but also and maybe more importantly, it asks for experimenting specific workflows for coordinating a variety of expertises ranging from social sciences disciplines (history, sociology, etc.) to data science, information design and web-related skills. It also reconfigures, for the research processes themselves, the relationships between activities of (data-related) enquiry and (communication-oriented) writing, creating a renewed space for discovery, invention and verification for the data sustaining a given argument or narrative.
Relying on recent experiments in making collective digital publications grounded in sociology of technology (https://medialab.github.io/carnet-algopresse/#/publication/en) and history of economy (https://medialab.github.io/portic-storymaps-2021/), this talk accounts for the diverse challenges arising from such activities of “data visualization-driven writing”, and some strategies we used to cope with them. It describes and compares the technical and methodological workflows we developed in order to simultaneously develop text, datasets and visualizations, taking into account a variety of aims, data materials, and distribution of skills. Doing so, it advocates for an extended understanding of the notion of “academic writing”, encompassing the practices of writing software, data and diagrams. Such an extended understanding, we argue, is necessary to design and develop writing workflows allowing to foster a multimodal and scientifically productive dialogue between these heterogeneous practices, taking full advantage of the web publication format as a research situation.
Speakers: Robin De Mourat