Tag Archives: quantified self

February 17, 2014 | 2 Comments

Ethnography in Communities of Big Data: Contested expectations for data in the 23andme and FDA Controversy


IMG_2834 Brittany Fiore-Silfvast (@brittafiore) is a PhD candidate in Communication at the University of Washington and she holds an MA in sociocultural anthropology from Columbia University. Her research focuses on the relationship of technology and emerging cultural and organizational forms. Her work cited in this article was supported in part by an NSF Doctoral Dissertation Improvement Grant and an Intel grant.

Editor’s note: One of the disciplines big data is most strongly influencing is medicine, and here Brittany Fiore-Silfvast (@brittafiore) applies her expertise to examine the interplay between health and technology to understand the implications of today’s unprecedented levels of patient data collection and analysis (although, notably, seldom including access to the data by those very patients who produced it).

Brittany hits upon a key issue with her post: seeing “big data” as a means of eliminating uncertainty through statistical analysis. While the elimination of uncertainty through statistical analysis is nothing new, the difference today is the scale at which collection and analysis of such data is unfolding and the diversity of the fields in which it is occurring.

Read on to discover the nature of conflict between the main personal genetics testing company 23andme, the importance of and difference between big data, small data, thick data, and DaM data, and the role that “Blue Suede Shoes” play in all of this.

For more posts from this EPIC edition curated by  editor Tricia Wang (who gave the opening keynoted talk at EPIC this year), follow this link.
23andme box

Scott Beale / Laughing Squid laughingsquid.com

Across the field of health and wellness there is a lot of talk about data, from consumer self-tracking and Quantified Self data, to data-driven, personalized health care, to data-intensive, crowd sourced, scientific discovery. But what are these different stakeholders talking about when they talk about data and are they talking about the same thing?

At EPIC, in the “Big Data/Ethnography or Big Data Ethnography” session, I presented on this topic drawing from our ethnography of the impact of consumer big and small data on institutions of healthcare. In this post I use the recent controversy between the FDA and personal genetics testing company, 23andme, to exemplify many of the concepts my co-author, Dr. Gina Neff, and I develop in our EPIC paper “What we talk about when we talk data: Valences and the social performance of multiple metrics in digital health”, rather than simply re-present them.  I also demonstrate how ethnography can be leveraged in the context of so-called “big data” or data intensive transformations in science and practice.Read More… Ethnography in Communities of Big Data: Contested expectations for data in the 23andme and FDA Controversy

January 20, 2014 | 17 Comments

Lessons Learned From EPIC’s Mobile Apps & Quantified Self Workshop


MikeGotta_CasualMike Gotta (@Mikegotta) is a Research Vice President for collaboration and social software at Gartner. He has more than 30 years of experience in the IT industry, with 14 of those years spent as an industry analyst advising business and IT strategists on topics related to collaboration, teaming, community-building, and social networking. He has expanded his research to include quantified self trends as well as the business use and organizational value of ethnography. He is currently pursuing a master’s degree in Media Studies at The New School in New York City.

At EPIC 2103, Mike Gotta (@Mikegotta) gave a workshop, Mobile Apps & Sensors: Emerging Opportunities For Ethnographic Research, that examined mobile apps developed for ethnographic research uses. I asked Mike to contribute to the January EPIC theme at Ethnography Matters because his research is always spotlighting some of the most fascinating trends in the tech industry. In this article, Mike provides a wonderful overview of his workshop, but even more interesting is his discussion of all the different ways the dialogue veered away from the original topic of the workshop. Essentially, things didn’t go as Mike had planned. The new direction, however, offered Mike a lot of insights into the future of mobile apps, which led him to reflect on personalized sensors as part of Quantified Self trends and the increasing importance of APIs in future research tools.  If you’re a qualitative researcher who wants to know how to make use of the latest mobile apps, this is a must-read article. The second half of Mike’s article can be read on Gartner’s blog.

Mike is currently at Gartner, Inc. (NYSE: IT), which describes itself as the world’s leading information technology research and advisory company. Mike is a familiar face at Ethnography Matters; during his time at Cisco Systems, Mike contributed to Ethnography Matters a piece that has become one of the most often-cited pieces of research on the role of ethnography in  Enterprise Social Networks (ESN).

For more posts from this January EPIC edition curated by contributing editor Tricia Wang, follow this link.

Slide1You might wonder – what’s a technology industry analyst doing at EPIC and why deliver a workshop on mobile apps and sensors?

The world of the IT industry analyst is becoming much more inter-disciplinary as societal, cultural, economic, media, demographic, and technology trends become more intertwined. These trends, perhaps, were always entangled in some fashion and we are only now becoming more interested in how the patterns of everyday life are mediated by various technologies.

There was a time when industry analysts could cover technology trends and their business relevance as long as they had an IT background. That might still be true in some cases – maybe – but in my opinion, being well-versed in social sciences is becoming a baseline competency for those in my profession.

Which brings me back to EPIC 2013. I had been looking into synergies across design, ethnography, and mobile and was happy to deliver a workshop for EPIC attendees to look at advances in mobile apps that support ethnographic research. As a group, we identified the pro/con’s of mobile apps and discussed how field research could be better supported. The topic was relevant not only to the ethnographic community but also to audiences who interact frequently with industry analysts: digital marketers, innovation teams, design groups, product/service managers, and IT organizations.  It struck me that EPIC (as a conference and organization) is in a position to act as a yearly event touch point between those in the social sciences and business/technology strategists interested in the same issues.Read More… Lessons Learned From EPIC’s Mobile Apps & Quantified Self Workshop