Longitudinal Mobile, Wearable, and Ubiquitous Data Collection from Human Subject Studies
The Workshop on Longitudinal Data Collection welcomes contributions and discussions focused on the methods, tools, and frameworks for collection, analysis, and interpretation of human subjects’ mobile, wearable, and ubiquitous data obtained over long periods.
Individuals increasingly use mobile, wearable, and ubiquitous devices capable of unobtrusive collection of vast amounts of scientifically-rich human subject personal data over long periods (months to years), and in the context of their daily life. However, numerous human and technological factors challenge longitudinal data collection, often limiting research studies to very short data collection periods (days to weeks), spawning recruitment biases and affecting participant retention over time. This workshop is designed to bring together researchers involved in longitudinal data collection studies to foster an insightful exchange of ideas, experiences, and discoveries to improve the studies’ reliability, validity, and perceived meaning of longitudinal mobile, wearable, and ubiquitous data collection for the participants.
Workshop at a Glance
- One-day workshop on Longitudinal Data Collection (LDC 2019)
- Co-located with the ACM UbiComp conference (UbiComp 2019)
- September 9 or 10, 2019, London, United Kingdom
- Papers of 4-6 pages, SIGCHI extended abstract, PDF format
- Submission deadline June 14 AoE
The workshop will offer a professional space for researchers to share ideas, approaches, methods, tools, frameworks, and other insights that enable the collection of reliable and valid longitudinal mobile, wearable, and ubiquitous data. We aim:
- To present and discuss state of the art methods for longitudinal mobile, wearable, and ubiquitous data collection in human subject studies.
- To discuss ideas to minimize participants’ burden while maximizing their retention in studies contributing relevant data to support study results that will create value for researchers and participants alike.
- At mapping the challenges into the implications for the design of human subject studies that will drive this line of research in the coming years.
- To foster collaboration among researchers working in this area.
The workshop welcomes contributions and discussions focused on the methods, tools, and frameworks for collection, analysis, and interpretation of human subjects’ mobile, wearable, and ubiquitous data obtained over long periods:
- Elaboration on human, technological, and other factors influencing the design and execution of human longitudinal data collection.
- Approaches that increase the quality of mobile, wearable, and ubiquitous data collected as part of scientific studies or identify participant groups likely to exhibit compliance.
- Methodologies to assess and improve retention for a representative sample of participants and specific metrics, e.g., engagement, interruptions, consistency, or time to abandonment.
- Techniques or methods for the analyses of the representatives and quality of collected longitudinal mobile, wearable, and ubiquitous data.
- Novel findings and lessons learned from past or existing longitudinal data collection studies conducted in the user’s context, implying qualitative, quantitative, or mixed analyses.
The workshop organizers will accept a maximum of 10 papers by peer review. The authors of the accepted papers will present their work for 10 minutes, answer questions from the audience, and participate in the joint discussions. We welcome all interested conference attendees to the workshop.
- Society: SIGCHI
- Conference/Journal: UbiComp 2019
- Track: UbiComp 2019 Workshop – LDC
- Submission: June 14 AoE
- Notification: June 28 AoE
- Camera-ready: July 12 AoE
Peer-review assessing the submission’s relevance, significance, originality, clarity, and overall quality.
Accepted workshop papers will be added to the ACM Digital Library and the UbiComp adjunct proceedings.
The workshop is planned to cover a full day. The workshop will start with a round of introduction by all attendees. Three sections will partition the accepted papers in groups of 3-4 papers by their contribution area (e.g., human factors, technological issues, use cases), with breaks aimed at incentivizing attendees to discuss between themselves. The organizers will introduce the sections, after which the respective authors will present their work for 10 minutes. Following the presentations, all attendees will contribute to a group discussion on the work to identify the implications for the broader research agenda. One organizer will summarize and present the lessons learned from the ongoing discussions. We expect these findings to fuel dialogue over a joint dinner.
PhD Student, University of Copenhagen
Research interests: mobile and wearable computing, mobile health, machine learning
PhD Student, University of Geneva
Research interests: human-computer interaction, mobile and wearable computing, mobile health, human stress
PhD Student, University of Geneva
Research interests: mobile and wearable computing, quality of experience, context awareness, machine learning
Naja Holten Møller
Assistant Professor, University of Copenhagen
Research interests: computer-supported cooperative work, human-computer interaction, science and technology studies, ethnography, workplace studies
Associate Professor, University of Geneva
Associate Professor, University of Copenhagen
Research interests: pervasive and mobile computing, behavior modeling, digital health, quality of experience, quality of life
Research Associate Professor, New York University
Chief Scientific Officer, Datacubed Research
Research interests: decision making, human conditions, big data, urban studies
Professor, Technical University of Denmark
Research interests: complex networks, social networks, social data
Professor, Stanford University
Research interests: genomics, precision medicine, personalized medicine, inherited cardiovascular disease, cardiomyopathy
Please don’t hesitate to contact us at firstname.lastname@example.org.
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UbiComp Workshop on Longitudinal Data Collection | LDC 2019
September 9 or 10, 2019 | London, United Kingdom | Acknowledgements