Spatial data old and new – Spatialists

Martin Fleischmann¹ teaches a course on Spatial Data Science through Charles University in Prague. The course is taught online and is open to anyone. Although I haven’t had the time to really dive into the material yet, one section titled “Spatial data old and new” caught my attention. In it, Martin Fleischmann introduces a dichotomy of spatial data:

Old – think: purposefully collected, carefully crafted, expensive, and slow – versus
New – think: incidental or repurposed, detailed, fast

He then goes on and suggests classifications of the “new spatial data” from two sources:

According to Lazer & Radford (2017)²:
- Digital life: social media platforms, Wikipedia, etc.
- Digital traces: records of digital actions such as metadata on media use
- Digitalised life: non-inherently digital aspects of life recorded in digital form, e.g. in government records or on the web
According to Arribas-Bel (2014)³:
- Bottom-up: Citizens as “sensors”
- Intermediate: Digital businesses
- Top-down: Open Government Data

While I’m not entirely convinced by these classifications and concepts, they offer a fresh (to me) perspective on some aspects of spatial data and seem to complement some traditional concepts⁴. Even after roughly 20 years of recent “neogeography”, it seems to me, there are still crucial debates and important developments in the geoinformation industry (also in Switzerland) that revolve around these ideas.

The Fighting Temeraire by William Turner, as famously seen in Skyfall — *The Fighting Temeraire* by William Turner, as famously seen in *Skyfall*

Footnotes

Among other things, Martin Fleischmann is the developer or one of the developers behind such geospatial tools as momepy, GeoPandas, and PySAL.↩︎
David Lazer and Jason Radford (2017): Data Ex Machina: Introduction to Big Data. Annual Review of Sociology, 43(1): 19–39.↩︎
Daniel Arribas-Bel (2014): Accidental, Open and Everywhere: Emerging Data Sources for the Understanding of Cities. Applied Geography, 49: 45–53.↩︎
for example, distinctions such as “official/authoritative” vs. “crowdsourcing”, concepts like (so-called) “volunteered geographic information”, and the “cathedral vs. bazaar” model of thinking about data↩︎