The document discusses a study that tested a tool called the Data Track, which allows users to exercise their right to data portability by exporting personal data from services like Google and importing it locally. The study had two main research objectives: 1) understand users' perceptions of transparency with the Data Track and 2) understand users' perceptions of data export and portability. Sixteen participants tested the Data Track and were interviewed. Results showed unclear understanding of data portability, concern over data sharing, and difficulty differentiating locally vs remotely stored data. Improvements could help users form correct mental models of data portability and increase awareness of transparency, control, and portability functions.

1. Visualizing Exports of Personal Data by Exercising the Right of Data
Portability in the Data Track
Are People Ready for This?
Farzaneh Karegar*,Tobias Pulls*, and Simone Fischer-Hübner*
* Department of Mathematic and Computer Science
Karlstad University (KaU)
Karegar F., Pulls T., Fischer-Hübner S. (2016) Visualizing Exports of Personal Data by Exercising the Right of Data Portability in the Data
Track - Are People Ready for This?. In: Lehmann A., Whitehouse D., Fischer-Hübner S., Fritsch L., Raab C. (eds) Privacy and Identity
Management. Facing up to Next Steps. Privacy and Identity 2016. IFIP Advances in Information and Communication Technology, vol 498.
Springer, Cham.

2. Background
 EU Data Protection Directive 95/46/EC and General Data Protection
Regulation (GDPR)
 Enhanced data subject and transparency rights
 Including the right of data portability:
• Increase user choices of online services
• Allow users to request data from the controllers
• Provide users with data in electronic form
 Challenges:
• Lack of clear understanding
• Lack of Transparency in regard to Cloud service’s operations
• Lack of tools provided for exercising data subjects’ rights

3. Background
• To exert the rights pursuant to GDPR : Using TETs
User Side TET Server Side TET Trusted Third Party TET
Google Dashboard
and
My Activity

4. Background
• Data Track (DT): an ex-post TET tool
• A part of the European PRIME and PrimeLife and the A4Cloud project.
Data export
Download on her computer

5. Research objectives
1. What are the users’ perceptions of transparency with the standalone
Data Track?
E.g.: Does the interface convey that Google has more information about the users
other than what they have sent explicitly or implicitly? What kind of transparency
options are the users interested in and would they like the Data Track to provide more
transparency information related to their data?
2. What are users’ perceptions of data export and portability with the
stand-alone Data Tack?
E.g.: Do users understand and value the idea and the concept of exporting data from a
service provider (Google in this case) and importing it to a tool running on their own
machines or to another service provider? Consequently, do users understand the
differences between locally stored (and thus user controlled) and remotely stored
data? (i.e., data stored on their computers in the Data Track under their control after
being exported from a service provider vs. data stored at the service’s side)?

6. How does Data Track work?

7. How does Data Track work? Three Different
Views
The map view
The timeline view
The trace view

8. Usability Tests and Methods
• Participants:
o Incremental and evolutionary pilot tests with 16 participants.
o unbiased sample of ten participants by recruiting arbitrary people in Karlstad
city center, via a Facebook group related to Karlstad and participants in an
innovation seminar.
Task: aimed to have the location data imported to the Data Track as the starting point of
discussing the interview questions.
• Study procedure: test plan
o Multiple data collection methods
pre-test questionnaires, semi-structured interview questions
o Participants’ goals : Export the location data from the Google and import it to
DT and navigate the map view.
o Not using personal data : the role of a persona to play
Location On
Google Location History On

9. Results
• Demographic :
?

10. Results (derived from our data collection methods for each
research question)
• Users’ Perceptions of Transparency Functions
• Derived vs. Disclosed Data
• Sensitivity and Importance of Derived Data
• Transparency Functions
• Users’ Perceptions of Data Export and Portability
• Locally vs. Remotely Stored Data and Access to the Uploaded
• Data to the Data Track
• Users’ Attitudes of Data Portability, Preferable Ways and
• Usefulness of Data Track
Data Track

11. Limitations
• Use of fake location data of a persona: it will be interesting to
conduct future user studies for our transparency tools with real data
of test participants to analyze how they are reacting if they are
confronted their own data traces.
• The novelty of concepts presented in Data Track (DT) : artificial
impacts on users’ perceptions.
o Limited time to use the DT and reflect on the different
questions asked.
o We need to repeat similar interviews over time

12. Conclusion and Future Work
Major HCI problems:
• Unclear understanding of what data portability means, not being aware of data
portability benefits
• Concerned about what a service provider can send to the other parties when
exercising Data Portability
• Difficulties to differentiate between locally and remotely stored and controlled data.
• Showed rather little interest in the visualization of derived activity data from location
data file: interests in other kind of derived data (e.g., by Facebook or online
marketing services), like movement and travel patterns, usage patterns for different
service providers, statistical data based on their behaviors.
Suggestion for improvements:
• Evoking correct mental models for data portability
• Improving awareness of transparency, control and data portability functions besides
awareness of consequences
• Extend the DT : real data from other service providers

13. Any Question?
Thank you for your attention.
Any Question?