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Trajectory Data Analyses for Pedestrian Space-time Activity Study

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Published on: February 25, 2013

Providing Spatial Data for Secondary Analysis: Issues and Current Practices relating to Confidentiality.

Myron Gutmann¹, Kristine Witkowski, Corey Colyer

¹Inter-university Consortium for Political and Social Research, Institute for Social Research, University of Michigan.

Population Research and Policy Review

|January 6, 2009

Summary

Spatially explicit social science data offer benefits but risk respondent privacy. Best practices are crucial for data producers, archives, and users to manage these risks during preservation and analysis.

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Area of Science:

Social Sciences
Data Science
Information Science

Background:

Spatially explicit data present unique opportunities and challenges for data producers, archives, and users.
Long-term preservation and secondary analysis of such data require careful consideration of all stakeholders.
The core challenge revolves around the potential for disclosure of respondent identities.

Purpose of the Study:

To identify and discuss the opportunities and challenges associated with spatially explicit social science data.
To summarize current best practices for preparing, archiving, disseminating, and utilizing this data.
To highlight the critical issue of respondent privacy and disclosure risk.

Main Methods:

Review of current thinking and best practices in data management.
Analysis of stakeholder roles (producer, archive, user) in the data lifecycle.
Identification of privacy risks inherent in spatially explicit data.

Main Results:

Opportunities exist in enhanced analysis and accessibility of social science data.
Challenges include ensuring data security, respondent anonymity, and ethical data use.
The risk of re-identification is significant if location data is linked with other information.

Conclusions:

Awareness of disclosure risks is paramount for all parties involved with spatially explicit data.
Implementing robust best practices is essential to mitigate privacy harms to respondents.
Effective data management strategies are needed for the responsible use of sensitive social science data.