Designing the Personal Data Stream: Enabling Participatory Privacy in Mobile Personal Sensing

17 Pages Posted: 6 Feb 2012  

Katie Shilton

University of Maryland, College Park - College of Information Studies

Jeff Burke

University of California, Los Angeles (UCLA)

Deborah Estrin

University of California, Los Angeles (UCLA)

Ramesh Govindan

University of Southern California

Mark Hansen

University of California, Los Angeles - Department of Statistics

Jerry Kang

University of California, Los Angeles (UCLA) - School of Law

Min Mun

University of California, Los Angeles (UCLA)

Date Written: August 15, 2009

Abstract

For decades, the Codes of Fair Information Practice have served as a model for data privacy, protecting personal information collected by governments and corporations. But professional data management standards such as the Codes of Fair Information Practice do not take into account a world of distributed data collection, nor the realities of data mining and easy, almost uncontrolled, dissemination. Emerging models of information gathering create an environment where recording devices, deployed by individuals rather than organizations, disrupt expected flows of information in both public and private spaces.

We suggest expanding the Codes of Fair Information Practice to protect privacy in this new data reality. An adapted understanding of the Codes of Fair Information Practice can promote individuals’ engagement with their own data, and apply not only to governments and corporations, but software developers creating the data collection programs of the 21st century. To support user participation in regulating sharing and disclosure, we discuss three foundational design principles: primacy of participants, data legibility, and engagement of participants throughout the data life cycle. We also discuss social changes that will need to accompany these design principles, including engagement of groups and appeal to the public sphere, increasing transparency of services through voluntary or regulated labeling, and securing a legal privilege for raw location data.

Suggested Citation

Shilton, Katie and Burke, Jeff and Estrin, Deborah and Govindan, Ramesh and Hansen, Mark and Kang, Jerry and Mun, Min, Designing the Personal Data Stream: Enabling Participatory Privacy in Mobile Personal Sensing (August 15, 2009). TPRC 2009. Available at SSRN: https://ssrn.com/abstract=1999839

Katie Shilton (Contact Author)

University of Maryland, College Park - College of Information Studies ( email )

College Park, MD
United States

Jeff Burke

University of California, Los Angeles (UCLA) ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095
United States

Deborah Estrin

University of California, Los Angeles (UCLA) ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095
United States

Ramesh Govindan

University of Southern California ( email )

Los Angeles, CA 90089
United States

Mark Hansen

University of California, Los Angeles - Department of Statistics ( email )

8125 Math Sciences
UCLA
Los Angeles, CA 90095
United States

Jerry Kang

University of California, Los Angeles (UCLA) - School of Law ( email )

385 Charles E. Young Dr. East
Room 1242
Los Angeles, CA 90095-1476
United States
310-206-7298 (Phone)
310-206-7010 (Fax)

Min Mun

University of California, Los Angeles (UCLA) ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095
United States

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