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2017 STS Making and Doing Program

Meeting Home | Making & Doing Main | Making and Doing 2017 | Category: STS Infrastructures

Data Sense

Nafus, Dawn, Intel

Data Sense is a software prototype that emerged from the Biosensors in Everyday Life program—a collaboration between four universities and Intel that examined the proliferation of technologies that sense bodies and their environments. That program identifieda need for greater space for technology users to reframe and repurpose what data means to them. Many technologies, especially those that work with idioms of health or fitness, traffic in cultural normativities that are not especially helpful for deepening or questioning knowledge about bodies. Yet technology users often have good contextual knowledge that might reveal the significance of data beyond what a data scientist could do working behind the scenes. That program also explored the materiality of enumeration—the idea that counting and physicality are inseparable, and that numeracy is not necessarily a function of formal STEM education alone. When it comes to their own bodies, technology users learn about data quite quickly, provided they have a starting place and support. Based on this work, Intel formed a team co-led by an STS scholar and an engineer to prototype a tool that would ease some of the technical barriers of exploring data, and make it easier to explore temporal, spatial, or correlational patterns that could be contextually meaningful. Data Sense automates some formatting issues that tend to trip up non-data scientists trying to explore data. It then provides a limited set of visual tools where users can interact with data directly on the visualization—a user can “grab” a spike in a line graph and “throw” it over to a map to see where it happened. We also built in explanations of commonly used data processing functions that tie back to the everyday context of using sensor device users, such as a video that shows why a rolling average might be particularly useful for calorie data but not necessarily heart rate data. By facilitating greater access to data in manipulatable formats, and providing introductory tools to explore it, we hope to make a small intervention in narrowing the big data divide. While Data Sense sought to embody key sensibilities of STS, I have also begun using it as an methodological tool for conducting ethnography. In my ongoing research on self-tracking, I invite participants to explore their data with me using Data Sense. Data Sense provides them opportunities to reflect on their data in a new way, which in turn gives me the opportunity to understand their thought processes and webs of significance more deeply.

Browse 2017 Projects

Alac: STS Olfactorium

Battles: The Trial Balloon: buoyancy, embodied media, and patchy planetarity

Callahan: Rethinking Citizen Science through doing Citizen Science

Cardoso Llach: Tracing Design Ecologies

Clement: Snowden Surveillance Archive

Cohen: Toward Improving Public Policy for Struct Engrg Design of Bridge, Transport & Marine Infrastructure

Durnova: Politicizing the scientific self through media interventions

Erickson-Davis: What it is to see: a simulation of artificial vision

Gluzman: Feminist Theory Theater

Gomez-Marquez: Construction Sets for DIY Medical Technologies and their Black Box Counterparts

Hidalgo: Collaborative Research Toolkit: a copyleft resource for the co-design of research processes

Hoagland: Getting a Sense of the Place: Navigating FemTechNet’s Critical Race and Ethnic Studies Workbook

Houston: Collaborative urban sensing with the “Dustbox” air quality monitor

Howell: Emotional Interpretation & Materiality of Biosensing

Johnson: Engineering Comes Home: Co-designing local infrastructure with residents of a London housing estate

Kennedy: Doing STS at the science/policy intersection

Knopes: Integrating STS into Bioethics and Medical Humanities Programs

Lachney: Generative STEM: Circulating Unalienated Value in Education, Labor and Environment

Lawson: (T)racing Eyes and Hearts:  An Installation to Explore the Physiology of Empathy

Lehr: Undergraduate STSers Learn by Doing in the Trump Era

Lippman: Making Sensible in 360°

Michails: AirTRACS: Community-based Air Quality Monitoring

Mogul: A STS STEM Education Incubator: The Co-Making of Inquiry

Mohsin: QEERI’s Science Majlis

Murphy: Environmental Data and Governance Initiative: Engaged STS Responding to the U.S.Administration

Nafus: Data Sense

Navarro: Our Driverless Futures: Speculating Moral Dilemmas of Self-Driving Cars

Nieusma: STS Design and Innovation: Disciplinary Discomfiture

Onaga: Biomaterial Matters: Fitting Humans into Cocoons, A Speculative Prototype

Ostman: STS approaches to public engagement with science: Synthetic biology

Ostrowski: The Empirical Printing Program

Perez Comisso: Technological theory for all: Teaching experiments on STS in Chile

Rosado Murillo: Pedal Transcriba, an Ethnographic Device of (and for) Qualitative Research

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Steensen: Face-off! Platform versus Self: A photobooth experiment

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Terrell: The making of an undergraduate Sociotechnical Ethics Society

Wentworth: Handholds: making sense of bodies through slaughter

Wong: Design Workbook Variations: Exploring Biosensing Privacy Futures

Wylie: Making and Doing STS with Undergraduate Engineers: The UVA Approach