Spatial data old and new

Slides from the talk about the nature of old spatial data and new spatial data, adapted from Dani Arribas-Bel (2019), drawing from the work of Lazer et al. (2014) and Daniel Arribas-Bel (2014).

Related reading

Parts of the chapter Spatial Data dealing with tabular data from the Geographic Data Science with Python by Rey, Arribas-Bel, and Wolf (2023).

Acknowledgements

This section is derived from A Course on Geographic Data Science by Dani Arribas-Bel (2019), licensed under CC-BY-SA 4.0.

References

Arribas-Bel, Dani. 2019. “A Course on Geographic Data Science.” The Journal of Open Source Education 2 (14). https://doi.org/10.21105/jose.00042.

Arribas-Bel, Daniel. 2014. “Accidental, Open and Everywhere: Emerging Data Sources for the Understanding of Cities.” Applied Geography 49: 45–53. https://doi.org/10.1016/j.apgeog.2013.09.012.

Lazer, David, Ryan Kennedy, Gary King, and Alessandro Vespignani. 2014. “The Parable of Google Flu: Traps in Big Data Analysis.” Science 343 (6176): 1203–5. https://doi.org/10.1126/science.1248506.

Rey, Sergio, Dani Arribas-Bel, and Levi John Wolf. 2023. Geographic Data Science with Python. Chapman & Hall/CRC Texts in Statistical Science. London, England: Taylor & Francis.