Private, Public, Personal

Geospatial data sources include data collected by the public sector (i.e., government), private sector (i.e., industry), or through field work. Of these categories, the private sector, especially through tech firms, has provided new types of cutting-edge data sets that are particularly large and novel. These include data from social media platforms and location-based technologies such as Global Positioning Systems and mobile phones. Here, we explore the extent to which peer-reviewed geospatial research has adopted these data sources, perhaps in lieu of more traditional data types. We review peer-reviewed journal articles from six flagship journals in geographic information systems, geography, and urban analytics that publish research that uses spatial data analysis. We find that geospatial researchers continue to rely on government-collected data for their research, but that researchers’ use of data from the private sector have increased in recent years. This finding implies that as spatial analysis studies increasingly rely on private data sets, we should revisit (1) how industry data collection faces fewer regulations on data quality and has different motivations for their collection, (2) how this affects our ability to trust our data sets, and (3) the role of government and field work in data collection and dissemination in the future

Cartography · Data science · Environmental planning · Environmental resource management · Geographic information system · Geography · Geospatial analysis · GIS and public health · Public participation GIS · Regional science · Computer Science · Data-Driven Disease Surveillance · Environmental Science · Geographic Information Systems Studies · Research Data Management Practices

• From data silos to data agency

  Open Access•Yijia Jiang, Kin Wai Michael Siu et al.•Urban Studies•2026

  Incluir item

• Ten simple rules for responsible big data research

  Open Access•Matthew Zook, Solon Barocas et al.•PLoS Computational Biology•2017

  Incluir item

• Welcome to the Tidyverse

  Open Access•Hadley Wickham, Mara Averick et al.•Journal of Open Source Software•2019

  Incluir item

• The Fair Guiding Principles for scientific data management and stewardship

  Open Access•Mark D Wilkinson, Michel Dumontier et al.•Scientific Data•2016

  Incluir item

• Urban ambient air temperature estimation using hyperlocal data from smart vehicle-borne sensors

  Open Access•Yanzhe Yin, Navid Hashemi Tonekaboni et al.•Computers Environment and Urban…•2020

  Incluir item

• How can Big Data and machine learning benefit environment and water management

  Open Access•Alexander Y Sun, Bridget R Scanlon•Environmental Research Letters•2019

  Incluir item

• The quality of big (geo)data

  Open Access•Michael F Goodchild•Dialogues in Human Geography•2013

  Incluir item

• Potential Biases in Big Data

  Open Access•Eszter Hargittai•Social Science Computer Review•2018

  Incluir item

• Artificial Intelligence and Inclusion

  Open Access•William R Frey, Desmond Upton Patton et al.•Social Science Computer Review•2018

  Incluir item

• The Relative Importance of Socioeconomic and Environmental Variables in Explaining Land Change in Bolivia, 2001–2010

  Daniel J Redo, Daniel Redo et al.•Annals of the Association of…•2012

  Incluir item

• Social Vulnerability to Climatic Shocks Is Shaped by Urban Accessibility

  Open Access•Luke Parry, Brendan Sturgeon et al.•Annals of the American…•2018

  Incluir item

• Three Globalizations Shaping the Twenty-first Century

  Ben Derudder, Paul J Taylor et al.•Annals of the American…•2020

  Incluir item

• Qualitative Content Analysis

  Open Access•Satu Elo, Maria Kääriäinen et al.•SAGE Open•2014

  Incluir item