Research Projects

PERVADE: Pervasive Data Ethics for Computational Research (2017-2023)

  • Role: PI
  • Sponsor: National Science Foundation Division of Information & Intelligent Systems, Award #1704598
  • Project Website: pervade.umd.edu

Networked information technologies, such as the internet of things, wearable devices, ubiquitous sensing, and social sharing platforms, have increased the flow of rich, but often personal, information available for computing research. The growth in the scale, scope, speed, and depth of human data research—what we call pervasive data practices—requires reconsideration of fundamental ethical assumptions.

This collaborative project asks questions like: How do we quantify the risks to individuals and groups in the use of pervasive data? How do people experience the reuse of their personal data? And how should existing ethical codes be adapted and adopted for computational research?

Find out more at the PERVADE Project Website.

Impact of Privacy Environments for Personal Health Data on Patients (2015-2018)

  • Role: Co-investigator
  • PI: Cinnamon Bloss
  • Sponsor: National Institute of Health (NIH) National Human Genome Research Institute (NHGRI), Award #1R01HG008753-01

A big data ecosystem is evolving in our society in which people may have, or feel they have, little control over the flow of their personal health information, and thus their privacy. Further, although there has been significant discussion related to big data and privacy at the highest levels of government, there is little consensus among scholars and stakeholders as to what privacy actually is, not to mention a lack of data from individuals as to personal conceptions of privacy. While much has been written about the potential harms of this and the rapidity with which the divide between health-related big data capabilities and privacy controls and protections is widening, we have little systematic knowledge of the nature and impacts of individual-level privacy concerns, and no reliable and valid tools for acquiring such knowledge from patients. The goal of this project is to conceptualize, measure, and understand individual privacy affinities and responses to privacy environments in the context of health-related big data technologies.

Health Data Exploration (2013-2017)

A variety of health-relevant parameters can now be easily captured via wearable devices, smartphones and other tools that may yield insights about personal and population health. Sensors on these devices are collecting ever-larger streams of data that have never been collected before on individuals – across the lifespan, throughout the course of health and illness and in geospatial context. Yet the fields of behavioral, social, clinical and public health research still largely rely on traditional sources of health data such as electronic medical records, clinical trials funded by pharmaceuticals or the NIH, and public health data from periodic surveys or reports from surveillance systems. There may be considerable scientific value in making new forms of health data available to researchers in medicine, public health and the social and behavioral sciences. The Health Data Exploration project is exploring how to bridge the “worlds” of health researchers, the set of mostly private and often small technology companies that hold these data, and individuals who may want to donate their own health or medical data. Issues to be addressed include whether there are unique scientific, methodological or ethical issues involved in such research; how to handle intellectual property of research findings; how and where these data intersect with other forms of medical and public health data; data quality; and privacy and confidentiality.

Virtual Standards Development Organizations: Enhancing Interoperability in Data-Intensive Science (2012-2016)

  • Role: PI
  • Sponsor: NSF Award #1221908

The success of large-scale data-enabled scientific collaboration depends upon the development of high-quality, useful and usable standards to enable data sharing and reuse. This project will undertake a three-year qualitative study of open-participation community standards organizations in the genomic sciences to investigate how they manage diverse stakeholder interests to develop and deploy community standards.

Socio-Computational Approaches to Planetary Exploration (2012-2014)

  • PI: Janet Vertesi
  • Sponsor: NSF Award #0968616

This project studies the ongoing NASA-ESA-ASI Cassini Mission to Saturn to better understand the issues that envelop complex socio-computation systems, such as the mutual interdependence of humans and machines, to present broader implications for the design of complex human-computer systems more generally. Using ethnography, oral history interviews, and archival work, researchers will probe the practices of sociotechnical organization, distributed operations, data sharing, and community maintenance in an existing, complex, high-stakes and international sociocomputational environment.

Personal Genomics and the Quantified Self (2013)

In this project, we are exploring the use of personal genomic testing (e.g. 23andme.com) as part of self-quantification activities. As part of the Algorithmic Living theme within the Intel Science and Technology Center for Social Computing, we are interested in the ways that new forms of data allow for and support new understandings of the self and well-being. We are focusing on members of the Quantified Self (QS) community. QS is a movement for individuals to understand themselves through personal data. QS practitioners track their own activities (e.g., diet and exercise), performance measures (mental and physical testing), mood states, and medical diagnostics as a way to monitor and make sense of their health and happiness. The QS movement promotes a view that collecting data about inputs (food consumption, environmental factors, stress levels, etc.), outputs (disease, moods, activity levels, bowel movements, etc.), and processing instructions (the genetic code) will empower individuals to comprehend and intervene in their personal predictable human system. We are probing how this algorithmic rhetoric is understood and experienced by those who are participating in QS activities, and how these participants understand the potential social and scientific benefits and risks of sharing personal health data. Additionally, information technology plays a key role in the QS movement, and we will begin to characterize how participants use computational tools for collecting, analyzing, organizing, and sharing their personal data.

Collaboration Success Wizard (2010-2012)

  • PI: Judith Olson and Gary Olson
  • Sponsor: NSF Award #1025769, Google, and the Donald Bren Foundation

The Collaboration Success Wizard is a web-based survey designed to both help geographically distributed groups reflect on their collaboration practices and to provide data for the validation of the Theory of Remote Scientific Collaboration (Olson, et al., 2008). Using a translational science paradigm, the project works to develop practical applications of over 20 years of theory-building about how to create successful collaborative projects.

Trust in Software Development Teams (2010-2012)

  • PI: David Redmiles
  • Sponsor: NSF Award #0943262

We are interested in exploring the antecedents of trust in virtual teams. Our research has three principle objectives. The first is to develop a deeper understanding of trust in virtual teams. Our second goal is to develop requirements (design rationale) for automated monitoring and management of trust in virtual teams. Our third objective is to develop software (user interface prototypes) to monitor and manage trust in virtual teams. Our understanding of trust will be formed by field studies of trust in two or more organizations. This understanding will inform the subsequent software tool we will develop to support positive trust in virtual teams.

Collaboration in the Development of Cyberinfrastructure (2008-2010)

  • PI: Charlotte Lee
  • Sponsor: NSF Award #0712994

Cyberinfrastructures are large-scale distributed scientific enterprises supported primarily through advanced technological infrastructures such as supercomputers and high speed networks. This project is systematically studying the actual practices of cyberinfrastructure development and use and is also examining the transformations that it is created to engender. Ethnographic methods are being used including participant-observation and semi-structured interviews. A nascent metagenomic cyberinfrastructure project is serving as the field site.

Leveraging Development Expertise Across Cyberinfrastructures (2008-2010)

  • PI: Charlotte Lee
  • Sponsor: NSF Award #0838601

This project is undertaking an unprecedented 18-month comparative ethnographic study of two large cyberinfrastructure building and research organizations: the National Center for Supercomputing Applications and the San Diego Supercomputer Center. Each of these organizations hosts and participates in multiple cyberinfrastructure projects of varying size and complexity. Qualitative research methods will include participant-observation and semi-structured interviews to understand how work practices change and develop over time.

Interactivity and Electronic Communication: An Experimental Study of Mediated Feedback (Dissertation Research)

The use of computer-mediated communication (CMC) and other electronic communication technologies can affect not only what information is communicated, but also how we make sense of that information. In my dissertation, I studied how mediating interpersonal communication technologies shape how individuals give, interpret, and use critical feedback.

This research focuses on the ability of some CMC technologies to create inequalities in individual participation in conversation. For example, some virtual meeting technologies give one participant the ability to communicate through video and audio, while restricting others to sending only text messages. In such a situation, the technology can disrupt backchannel communication, interfere with communication norms, and enforce power differentials among participants. In my dissertation, I explore these issues through a series of experiments in which pairs of participants give each other critical feedback using a variety of communication media.

Dissertation Committee:

  • Dr. Gary M. Olson, School of Information (Chair)
  • Dr. Judith S. Olson, School of Information
  • Dr. Michael D. Cohen, School of Information
  • Dr. Jason D. Owen-Smith, Sociology & Organizational Studies

The Science of Collaboratories (2004-2006)

  • PIs: Gary Olson, Judith Olson, Thomas Finholt, Stephanie Teasley, Daniel Atkins
  • Sponsor: NSF Award #0085951

This NSF-funded project at the University of Michigan School of Information looked across a large number of collaborative scientific projects in order to generate a set of technical and behavioral principles that may lead to better, more successful design of cyberinfrastructure in the future.

International AIDS Research Collaboratory (IARC) (2001-2004)

  • PI: Gary Olson

IARC was a study of HIV/AIDS research groups collaborating across laboratories in the United States, the United Kingdom, South Africa, and Botswana. These groups were doing both basic science about the nature of the HIV virus and clinical research into treatment effectiveness with different populations. This project involved conducting interviews and observations in laboratory settings in the U.S. and Africa, and deploying new infrastructure to support distributed laboratory meetings across sites.