Universität Wien
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290094 PS Location Privacy (2025S)

4.00 ECTS (2.00 SWS), SPL 29 - Geographie
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Termine "Ort in u:find-Details": Konferenzraum, NIG, 5. Stock, C0520
Termin am 3.6.: Büro von Ourania Kounadi

  • Tuesday 11.03. 08:30 - 10:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
  • Tuesday 18.03. 08:30 - 10:00 Ort in u:find Details
  • Tuesday 25.03. 08:30 - 10:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
    Ort in u:find Details
  • Tuesday 08.04. 08:30 - 10:00 Ort in u:find Details
  • Tuesday 29.04. 08:30 - 10:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
  • Tuesday 06.05. 08:30 - 10:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
  • Tuesday 20.05. 08:30 - 10:00 Ort in u:find Details
  • Tuesday 27.05. 08:30 - 10:00 Multimedia Mapping-Labor, NIG 1.Stock C0110
  • Tuesday 03.06. 08:30 - 10:00 Ort in u:find Details
  • Tuesday 10.06. 08:30 - 10:00 Ort in u:find Details
  • Tuesday 17.06. 08:30 - 10:00 Ort in u:find Details
  • Tuesday 24.06. 08:30 - 10:00 Ort in u:find Details

Information

Aims, contents and method of the course

As information and communication technologies advance and everybody can be connected to everybody else and everything all the time, we must ensure what location privacy implies within information privacy. In this course, we focus on location privacy (geoprivacy), because information about an individual’s location is substantially different from other kinds of personally identifiable information. Privacy can be defined as the positive right of individuals to determine for themselves when, how, and to what extent location information about them is communicated to others. During the course, we examine the process of transforming volunteered and observed information into inferred information, possibilities to control it, and we review examples of privacy-safeguarding strategies. It is important to understand protection as a facilitator to data openness and discuss the spectrum between information closure and disclosure.

Content
Introduction to location privacy, opinion and perception, regulatory frameworks, guidelines, information disclosure, re-identification & inference attacks, data anonymization, location protection methods, geomasking, geo-tracking apps, and geoethics.

Methods
The course follows a student-centred design educational principle. It entails a mixture of lectures and tutorials given by the lecturer as well as group-based active learning approaches; which contribute to the learning as well as the assessment of it. Additionally, students take a leading role by preparing and disseminating knowledge within the class.

Entry requirements
Elementary knowledge of GIS or spatial data structures is a prerequisite for this course.

Assessment and permitted materials

There are four testing elements.
The first (T1) is an assignment on one examination topic and it is assessed via an oral presentation. The second and third tests (T2 and T3) are group and game-based activities are that initiated with self-study, activated in class, and finalized through a written report. The last test (T4) is a review that involves active participation (discussion, feedback, questions) during oral presentations.

• Any ancillary material can be used in the preparation or presentation of the tests.

The weights of each test element are:

- Assignment 65% (T1)
- Group activity & report A 10% (T2)
- Group activity & report B 10% (T3)
- Review 15 % (T4)

Minimum requirements and assessment criteria

--> Attendance is compulsory on all test dates and for all.
--> All tests are obligatory to pass the course.

- T1 is assessed via the presentation file and the live presentation in class.
- T2 & T3 are assessed in class and via a written report.
- T4 is assessed in class.
- For T2, T3, and T4 a conditional mark is given for the completion of the test.

Examination topics

A. Location protection for discrete geodata
B. Location protection for spatiotemporal data
C. Geoinformation disclosure: risk or re-identification
D. Geoinformation disclosure: inference attacks
E. Research guidelines and regulatory frameworks on (Geo)privacy
F. Opinion and perception on Geoprivacy
G. Geotracking apps
H. Geoethics’ spectrum

Reading list

Armstrong, M. P., Rushton, G., & Zimmerman, D. L. (1999). Geographically masking health data to preserve confidentiality. Statistics in Medicine, 18 (5), 497-525.

Blumberg, A. J., & Eckersley, P. (2009). On locational privacy, and how to avoid losing it forever. Electronic Frontier Foundation: White Paper. retrieved at https://www.eff.org/wp/locational-privacy

Curtis, A. J., Mills, J. W., & Leitner, M. (2006). Spatial confidentiality and GIS: re-engineering mortality locations from published maps about Hurricane Katrina. International Journal of Health Geographics.5 (1). 44.

Democracy - Im Rausch der Daten https://www.youtube.com/watch?v=VUjo7mQXz0M&ab_channel=cheammon

Georgiadou, Y., Kounadi, O., & Rolf, A. (2020). Digital Earth Ethics. In Manual of Digital Earth (pp. 785-810). Springer, Singapore.

Hampton, K. H., Fitch, M. K., Allshouse, W. B., Doherty, I. A., Gesink, D. C., Leone, P. A., ... & Miller, W. C. (2010). Mapping health data: improved privacy protection with donut method geomasking. American journal of epidemiology, 172(9), 1062-1069.

Hoofnagle, C.J.; van der Sloot, B.; Zuiderveen Borgesius, F. The European Union General Data Protection Regulation: What It Is And What It Means. SSRN Electron. J. 2018, doi:10.2139/ssrn.3254511

Keßler, Carsten, and Grant McKenzie. "A geoprivacy manifesto." Transactions in GIS 22.1 (2018): 3-19.

Kounadi, O., & Leitner, M. (2016). Adaptive areal elimination (AAE): A transparent way of disclosing protected spatial datasets. Computers, Environment and Urban Systems, 57, 59-67.

Kounadi, O., & Resch, B. (2018). A Geoprivacy by Design Guideline for Research Campaigns That Use Participatory Sensing Data. Journal of Empirical Research on Human Research Ethics, 13(3), 203-222.

Krumm, J. (2007). Inference attacks on location tracks. Pervasive Computing.127-143.
The Guardian (2015)

Democracy: the film that gets behind the scenes of the European privacy debate. https://www.theguardian.com/technology/2015/nov/14/democracy-film-european-data-protection-privacy-debate

Association in the course directory

(MR1-b-PI) (MR3) (MR6) (MA UF GW 02) (MK2-PI)

Last modified: Tu 04.03.2025 14:07