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.

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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
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article

Data Sets for Regenerative Futures: Cultivating Relational Ontologies

Chris Speed, M. J. Dunbar
2 citations
Smart Cities and Technologies
0.64
article

Data Sets for Regenerative Futures: Cultivating Relational Ontologies

Chris Speed, M. J. Dunbar
article en
2 citations

Abstract

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.

RMIT University (AU)
Zero hunger
Openalex Percentile: Top 26%
Smart Cities and Technologies
0.64
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Data Sets for Regenerative Futures: Cultivating Relational Ontologies — Chris Speed, M. J. Dunbar · (2024) | TGRS Research Map | TGRS