The right tools for the job: The case for spatial science tool‐building

Geoff Boeing

doi:10.1111/tgis.12678

Abstract

AbstractThis article was presented as the 8th annual Transactions in GIS plenary address at the American Association of Geographers annual meeting in Washington, DC. The spatial sciences have recently seen growing calls for more accessible software and tools that better embody geographic science and theory. Urban spatial network science offers one clear opportunity: from multiple perspectives, tools to model and analyze non‐planar urban spatial networks have traditionally been inaccessible, atheoretical, or otherwise limiting. This article reflects on this state of the field. Then it discusses the motivation, experience, and outcomes of developing OSMnx, a tool intended to help address this. Next it reviews this tool's use in the recent multidisciplinary spatial network science literature to highlight upstream and downstream benefits of open‐source software development. Tool‐building is an essential but poorly incentivized component of academic geography and social science more broadly. To conduct better science, we need to build better tools. The article concludes with paths forward, emphasizing open‐source software and reusable computational data science beyond mere reproducibility and replicability.

Highlights

Do I need to know the precise polygonal geometries of Los Angeles and the University of Southern California (USC) to assert that the latter is within the former? No My mind contains no such precise geometric model of points and lines, yet I know that USC is in Los Angeles
When humans reason with the real world, they focus on its objects, relations, and processes—rather than starting with geometry—because these are the keys to Transactions in GIS. 2020;00:1–16
New data sources and knowledge discovery systems can help us wrestle with tricky questions, we impoverish our ability to reason with computers if we do not center theory when we create computational representations of the real world—even if we must rethink or advance our technologies and tools to do so

Summary

Introduction

Do I need to know the precise polygonal geometries of Los Angeles and the University of Southern California (USC) to assert that the latter is within the former? No My mind contains no such precise geometric model of points and lines, yet I know that USC is in Los Angeles. I reflect on my own tool-building experiences in urban planning and geography: facing the need for a better tool to model and analyze urban street networks in a scalable, theoretically sound way, I developed a new open-source Python-based software package called OSMnx. This article considers its history, motivation, and purpose, reviews its recent use in the empirical street network science literature. In turn, Gahegan argues that GIScientists must foster a more robust software development community to build and democratize better scientific research tools that are accessible and available to everyone.

Results

Conclusion