Data Sets for Regenerative Futures: Cultivating Relational Ontologies
This short paper examines the limitations of current urban data infrastructures in representing more-than-human perspectives and explores pathways toward more inclusive, regenerative data practices. It argues that prevalent data sets and knowledge repositories reflect anthropocentric ontologies, perpetuating the erasure of non-human subjects and diverse epistemologies. The paper identifies key challenges in developing more inclusive data infrastructures, including ontological incommensurability, the risk of cognitive injustice, and the need for expanded representational repertoires. Drawing on examples from Indigenous knowledge systems, multispecies ethnographies, and arts-based practices, the authors propose strategies for enriching urban datasets. These include centering marginalized perspectives, expanding participatory data governance models, and reimagining urban infrastructure as multi-species sensing apparatuses. The paper concludes by calling for the cultivation of relational data ontologies that can better capture the complex interdependencies between human and more-than-human worlds, essential for envisioning and realizing regenerative urban futures.
Authors
- Chris Speed (ORCID: https://orcid.org/0000-0003-0101-8117)
- M. J. Dunbar (ORCID: https://orcid.org/0009-0002-5182-9129)
Institutions
- RMIT University (AU)
Publication Details
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1145/3686169.3686200
- Citations
- 2
- Primary Topic
- Smart Cities and Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.64