The iLog app
iLog is an application developed by the KnowDive group at the Department of Information Engineering and Computer Science of the University of Trento. We developed it to collect data for research purposes. With the user consent, it is able to collect data from the smartphone internal sensors and send context sensitive questions. The final goal is to study the users' habits, allowing to react accordingly with personalized services, and generating research datasets for further studies.
User Consent and Privacy Protection
The correct management of the information collected and the participants’ privacy is of utmost importance during the use of the iLog app. For this reason, we have established the mandatory steps before any data collection with the iLog app can take place:
- Ethical Board clearance: an ethical board or similar entity, local to the institution where the survey is going to take place, has to approve the survey’s protocol. Recommendations and limitations are implemented according to their feedback.
- Institutional legal agreements signed: institutional authorities from the institutions involved in the survey agree and sign on the documents regulating how the data from the survey will be collected, stored, anonymized and used. This also includes compliance with local privacy laws, like GDPR.
iLog is currently available through the Android store Google Play. Versions for other platforms are currently under development.
Main Surveys / Experiments
- SmartUnitnOne(2017, 72 people, 2 weeks, 110GB): To gather a more comprehensive understanding of students' everyday life and how it affects their academic performance. First data collection for initial testing of the data collection platform.
- SmartUnitnTwo(2018, 300 people, 1 month, 3.0TB): To gather a more comprehensive understanding of students' everyday life and how it affects their academic performance. Main data collection to generate the needed datasets for its intended purpose.
- Qrowds(2019, 200 people, 2 weeks, 1.0TB): Understand the mobility habits of citizens from the Municipality of Trento in order to understand modal split, which will enable data-driven policies to improve transportation in Trento.
- EuroStat Hackathon(2019, 150 people, 2 weeks, ~900GB): Track the participation and organization of participants in the 2019 EuroStat Hackathon.
- WeNet Diversity Pilots(2020, 500 people, 3 weeks, ~5TB): Collect information about the student’s lifestyle in several sites of the world (Italy, Denmark, UK, Mongolia, India, Mexico, Paraguay) to map their diversity and offer insights and services to improve the quality of student life around the world.
- Mattia Zeni, Ivano Bison, Britta Gauckler, Fernando Reis, and Fausto Giunchiglia. "Improving time use measurement with personal big data collection - the experience of the European Big Data Hackathon 2019." Journal of Official Statistics, 2020.
- Zeni M, Zhang W, Bignotti E, et al. Fixing mislabeling by human annotators leveraging conflict resolution and prior knowledge[J]. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2019, 3(1): 1-23.
- Maddalena E, Ibáñez LD, Simperl E, Gomer R, Zeni M, Song D, Giunchiglia F. Hybrid Human Machine workflows for mobility management. Companion Proceedings of The 2019 World Wide Web Conference, 2019.
- Giunchiglia, F; Zeni, Mattia; Gobbi, Elisa; Bignotti, Enrico; Bison, Ivano. Mobile social media usage and academic performance. Computers in Human Behavior, vol. 82, p. 177-185, 2018.
- Giunchiglia F, Zeni M, Big E. Personal context recognition via reliable human-machine collaboration[C]//2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE, 2018: 379-384.
- Giunchiglia F, Bignotti E, Zeni M. Personal context modelling and annotation 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE, 2017: 117-122.
- Zeni M, Zaihrayeu I, Giunchiglia F. Multi-device activity logging Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication. 2014: 299-302.
- Kim P H, Giunchiglia F. The open platform for personal lifelogging: the elifelog architecture[M]//CHI'13 Extended Abstracts on Human Factors in Computing Systems. 2013: 1677-1682.
Information on the processing of personal data pursuant to art. 13 EU Regulation 2016/679
The EU Regulation 2016/679 "General Regulation on the protection of personal data" (hereinafter "GDPR") establishes the right of every person to the protection of personal data concerning him.
According to the indicated legislation, this treatment will be based on compliance with the principles of lawfulness, correctness, transparency, relevance, not excess and in order to ensure adequate security of personal data.
As an interested party, pursuant to art. 13 of the GDPR, we provide you with the following information.
The personal data are essential to conduct the implementation of the purpose of the projects in which iLog will be used.
The processing of personal data is conducted by the Data Controller pursuant to the General Data Protection Regulation (GDPR). In the case of scientific research activities, the Data Controller will process the personal data in the execution of his tasks of public interest pursuant to art. 6, paragraph 1, letter e) of the GDPR.
An additional privacy statement which explains the purpose and the legal basis of the project will be always provided.
- personal characteristics, such as gender/age/department/course of study.
- experience sampling data.
- sensor data, such as acceleration/ gyroscope/ gravity/ rotation vector/ magnetic field/ orientation/ temperature/ atmospheric pressure/ humidity/ proximity/ position/ Wi-Fi network connections/ running applications/ screen status, flight mode, battery status, doze modality/ headset, audio mode, music playback (no track info)/ notifications received, touch event/ cellular network info.
Depending on the projects iLog is involved in, all or some of the data mentioned above may be used. The details of the collected data will be provided in the privacy statement of each project.
The collected personal data are stored on the servers of the Data Controller of each project in which iLog is involved, or external contractors.
The personal data will be processed exclusively by the Data Controller and / or authorized parties in the framework of the implementation of the project. Additional or different information from the above will be provided in the privacy statement of each project in which iLog is involved.
Pursuant to art. 28 of the GDPR, the data may be recipients of subjects or categories of subjects, such as, by way of example but not limited to, researchers and research groups belonging to universities, bodies or national and international research institutes, both public and private; students, PhD students and university professors solely for teaching, research and technology transfer purposes within university courses and thesis work; research groups, including private ones, for the development of services and for the improvement of the quality of life; public or private entities for scientific research purposes and / or interested in developing services useful for improving the quality of life.
Additional or different information from the above will be provided in the privacy statement of each project in which iLog is involved.
The Data Controller reserves the right to update this information, publishing any additions at the project URL.