Transmedia storytelling: ArtScience collaboration for studies and representation of social-ecological-technological systems

Abstract:

Addressing the need for convergence of different sources of knowledge to deal with complex issues such as global change this paper presents the results of collaboration between artists and scientists for studies of social-ecological-technological systems (SETS). We focus on informal roads as an example of SETS. In the absence of public roads local, mostly indigenous communities and others use these forestry roads, seismic line clearings and oil and gas service roads for mobility in Siberian taiga affected by extractive industry.

The project started as a traditional scholarly research based on field studies focused on documentation and studies of the impacts of informal roads on local mobilities and environment in 2019. The project included a travelling exhibition created in collaboration with artists using ArtScience as a collaborative, experimentally-driven practice. The aim of exhibition was to launch discussions of pathways, directions for future participatory research that can involve any interested parties, be it physical or social scientists, artists, representatives of local and indigenous communities or any wanderers who decide to stop and involve in understanding of a place that we share and care about - village, forest or the Earth. In 2020, with cancellation of all travel plans due to COVID-19, we reconsidered forms of collaboration with the emphasis on virtual representations of the project. Working mostly from homes, scholars and artists experience the same push for transdisciplinary creativity and critical analysis of knowledge production while being connected through global technological and digital networks. We develop a website using a transmedia storytelling approach which converges different media platforms. It integrates digital content gathered and produced from various resources including artistic works and scholarly research to allow viewers and readers to engage with and comprehend the complexity of SETS’ state and transformations.