Protection of privacy of persons and communities

Learning Objectives

  • Identify potential risks to persons and communities within the context of open science in natural sciences.
  • Understand strategies to minimize risks to persons and communities while practicing open science in natural sciences.

Introduction

It might seem that there are no risks to privacy or personal data safety in natural sciences; nevertheless, some fields of natural sciences might deal with personal data even if the research does not directly involve human research subjects. For example, location-based data analysis, a common practice in some natural sciences, may jeopardize privacy when individuals' identities or households are tied to detailed location information. Aggregating seemingly anonymized data can still allow for inferences about specific individuals or groups, threatening their privacy. Even anonymized data can be at risk of re-identification, especially when merged with other datasets. In community-based studies, there might be a risk of infringing on community privacy and interests.

Open science practices in natural sciences may involve sharing detailed datasets, including data on persons, households and communities, and inadequate anonymization can compromise privacy. Moreover, even with anonymization, the risk of re-identification persists, especially when integrating datasets or employing advanced analytics, potentially revealing identities unintentionally. To mitigate these risks, scientists must prioritize ethical considerations, inform persons and communities concerned, submit research projects to ethical review, employ stringent anonymization methods, and comply with data protection and privacy standards. Transparency and clear communication about data handling practices, as well as the establishment of controlled data sharing protocols, are essential. Engaging communities in the research process helps build trust and ensures that research respects community values and privacy concerns. Striking a balance between open science principles and the protection of persons' and communities' rights and privacy is essential for ethical research practice.

Zipper et al. have suggested a decision tree which can be used by researchers to evaluate practices for sharing their data (Zipper et al., 2019). The yellow boxes indicate actions which researchers should take to protect privacy of individuals and communities.

Zipper and colleagues have suggested a decision tree which can be used by researchers to evaluate practices for sharing their data. The yellow boxes indicate actions which researchers should take to protect privacy of individuals and communities.

Potential decision tree researchers can use to evaluate practices for sharing their data. Source: Zipper S.C. et al. https://doi.org/10.1029/2019WR025080, CC BY 4.0

References

  1. Zipper, S. C. et al. (2019). Balancing open science and data privacy in the water sciences. Water Resources Research, 55(7), 5202-5211. https://doi.org/10.1029/2019WR025080
  1. Blatt, A. J. (2015). The benefits and risks of volunteered geographic information. Journal of Map & Geography Libraries, 11(1), 99-104. https://doi.org/10.1080/15420353.2015.1009609
  2. Richardson, D. B., Kwan, M. P., Alter, G., & McKendry, J. E. (2015). Replication of scientific research: addressing geoprivacy, confidentiality, and data sharing challenges in geospatial research. Annals of GIS, 21(2), 101-110. https://doi.org/10.1080/19475683.2015.1027792
  3. Solymosi, R., Buil‐Gil, D., Ceccato, V., Kim, E., & Jansson, U. (2023). Privacy challenges in geodata and open data. Area. https://doi.org/10.1111/area.12888