Commentary on the state of the art, challenges and future prospects for Points-of-Interest (POI) data

Points-of-Interest (POI) data have a prominent role in the ever-evolving spatial data ecosystem. We use them everyday when we plan our commute, decide where to spend our free time, or post our vacation photos on social media. POI data are also increasingly used in urban planning, sociology, public health, and mobility studies and applications, among others. However, a general commentary that encapsulates and reflects on the broad set of human experiences and challenges that derive from the modern POI data ecosystem and its platial implications is currently lacking.

Four POI‐based digital representations for the same real‐world location (Notre‐Dame Basilica in Montreal). Each point is labeled by the POI provider. Base map by CARTO/OpenStreetMap Contributors.

To fill this gap, Dr. Achilleas Psyllidis of the Urban Analytics group teamed up with prominent scholars in the fields of GIScience and Urban Analytics, namely Song Gao (University of Wisconsin-Madison), Yingjie Hu (University at Buffalo), Eun-Kyeong Kim (University of Zurich), Grant McKenzie (McGill University), Ross Purves (University of Zurich), May Yuan (University of Texas at Dallas), and Clio Andris (Georgia Institute of Technology), to develop a commentary, now published in Computational Urban Science, titled “Points of Interest (POI): a commentary on the state of the art, challenges, and prospects for the future”.

In this commentary, the authors describe the current state of the art of points of interest (POIs) as digital, spatial datasets, both in terms of their quality and affordings, and how they are used across research domains. They further list challenges in POI geolocation and spatial representation, data fidelity, and POI attributes, and address how these challenges may affect the results of geospatial analyses of the built environment for applications in public health, urban planning, sustainable development, mobility, community studies, and sociology. This commentary is intended to shed more light on the importance of POIs both as standalone spatial datasets and as input to geospatial analyses.

The article is accessible to everyone at this link. Feel free to share it broadly with your network.