Open participatory mapping data

Project description

Use of Public Participation Geographic Information System (PPGIS) for data collection has been significantly growing over the past few years in different areas of research and practice. With the growing amount of data, there is little doubt that a potentially wider community can benefit from open access to them. Additionally, open data add to the transparency of research and can be considered as an essential feature of science. However, data anonymization is a complex task and the unique characteristics of PPGIS add to this complexity. PPGIS data often include personal spatial and non-spatial information, which essentially require different approaches for anonymization. In this project, we first identify different privacy concerns and then develop a PPGIS data anonymization strategy to overcome them for an open PPGIS data. Specifically, this project introduces a context-sensitive spatial anonymization method to protect individual home locations while maintaining their spatial resolution for mapping purposes. Furthermore, in this project we empirically evaluate the effects of data anonymization on PPGIS data quality. In this project, European data protection regulations are used as the legal guidelines. However, adaptation of methods employed in this study may be also relevant to other countries where comparable regulations exist. Although specifically targeted at PPGIS data, what is discussed in this paper can be applicable to other similar spatial datasets as well.

Photo by David Martin on Unsplash.

Research themes

Project details

  • Start date:
    June 1, 2019
  • End date:
    December 31, 2019
  • Location:
    Aalto University
  • Funded by:
    Aalto University Seed Funding
  • Objectives:

Project contact

Kamyar Hasanzadeh

Aalto University

Participating partners

Related publications

Hasanzadeh, K., Kajosaari, A., Häggman, D. & Kyttä, M. (2020). A context sensitive approach to anonymizing public participation GIS data: From development to the assessment of anonymization effects on data quality. Computers, Environment and Urban Systems 83, 101513.

Participatory Mapping Institute
Copyright 2020