Work

Yirgacheffe: A Declarative Approach to Geospatial Data

Year: 2025

Type: conference-paper

Abstract: We present Yirgacheffe, a declarative geospatial library that allows spatial algorithms to be implemented concisely, supports parallel execution, and avoids common errors by automatically handling data (large geospatial rasters) and resources (cores, memory, GPUs). Our primary user domain comprises ecologists, where a typical problem involves cleaning messy occurrence data, overlaying it over tiled rasters, combining layers, and deriving actionable insights from the results. We describe the successes of this approach towards driving key pipelines related to global biodiversity and describe the capability gaps that remain, hoping to motivate more research into geospatial domain-specific languages.

DOI: 10.1145/3759536.3763806

Authors: Michael Winston Dales, Alison Eyres, Patrick Ferris, Francesca A. Ridley, Simon Tarr, Anil Madhavapeddy

Institutions: University of Cambridge, Newcastle University, International Union for Conservation of Nature (United Kingdom)

Language: English

Topic: Geographic Information Systems Studies

Subfield: Geography, Planning and Development

Field: Social Sciences

Domain: Social Sciences

SDG: Life on land

Open Access status: gold

OpenAlex ID: W4415002586

FWCI: 78.48

Cites: 17

Cited by: 8

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