Šnajberková, JaroslavaBidarra, JoséTavares, Mirian2026-06-022026-06-022026-05-29Šnajberková, J., Bidarra, J., & Tavares, M.N. (2026). The Mountain Knows Who You Are: Visual Storytelling Through Autoethnography. International Symposium on Biographical Narratives in Arts, Media and Society (Tell.Me 2026), 28-29 de maio, Macau, Brasil e Portugal.http://hdl.handle.net/10400.2/22103This paper discusses the concept of autoethnography used in doctoral research on digital media arts, based on long-term photographic fieldwork in the Sierra Nevada de Santa Marta, Colombia. The paper argues that photographic practice and scientific inquiry are forms of knowledge production embedded in landscape and interconnected lived experiences. The mountain landscape is considered a living being by local communities. Places called ‘ezuamas’ function as interwoven realities that preserve memory and are sources of ancestral teaching. Human activity exists in a network connecting people with the environment and spiritual forces. Similarly, various roles, from photographer and artist to researcher, converge in the figure of the author, and ultimately motherhood fundamentally influences the course and outcome of the research. The paper also suggests possible resonances between analogue photographic processes and digital logic. Interviews with local participants revealed parallel perspectives in which technologies may be understood as manifestations of pre-existing cosmological principles. The project was divided into two phases, fieldwork and post-production. The narrative component combines analogue black-and-white photography and digital colour audiovisual material with autobiographical notes written during stays in the region between 2019 and 2022, with subsequent analytical reflections during data processing between 2022 and 2026.engAutoethnographyDigital Media and ArtAnalogue PhotographyPhotographic FieldworkPractice-Based ResearchThe mountain knows who you are: visual storytelling through autoethnographyconference paper not in proceedings