February 17, 2014 | 2 Comments

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

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.

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

May 13, 2013 | 43 Comments

Big Data Needs Thick Data

Tricia Wang

Editor’s Note: Tricia provides an excellent segue between last month’s “Ethnomining” Special Edition and this month’s on “Talking to Companies about Ethnography.” She offers further thoughts building on our collective discussion (perhaps bordering on obsession?) with the big data trend. With nuance she tackles and reinvents some of the terminology circulating in the various industries that wish to make use of social research. In the wake of big data, ethnographers, she suggests, can offer thick data. In the face of derisive mention of “anecdotes” we ought to stand up to defend the value of stories.

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image from Mark Smiciklas at Intersection Consulting

Big Data can have enormous appeal. Who wants to be thought of as a small thinker when there is an opportunity to go BIG?

The positivistic bias in favor of Big Data (a term often used to describe the quantitative data that is produced through analysis of enormous datasets) as an objective way to understand our world presents challenges for ethnographers. What are ethnographers to do when our research is seen as insignificant or invaluable? Can we simply ignore Big Data as too muddled in hype to be useful?

No. Ethnographers must engage with Big Data. Otherwise our work can be all too easily shoved into another department, minimized as a small line item on a budget, and relegated to the small data corner. But how can our kind of research be seen as an equally important to algorithmically processed data? What is the ethnographer’s 10 second elevator pitch to a room of data scientists?

…and GO!

Big Data produces so much information that it needs something more to bridge and/or reveal knowledge gaps. That’s why ethnographic work holds such enormous value in the era of Big Data.

Lacking the conceptual words to quickly position the value of ethnographic work in the context of Big Data, I have begun, over the last year, to employ the term Thick Data (with a nod to Clifford Geertz!) to advocate for integrative approaches to research. Thick Data uncovers the meaning behind Big Data visualization and analysis.

Thick Data: ethnographic approaches that uncover the meaning behind Big Data visualization and analysis.

Thick Data analysis primarily relies on human brain power to process a small “N” while big data analysis requires computational power (of course with humans writing the algorithms) to process a large “N”. Big Data reveals insights with a particular range of data points, while Thick Data reveals the social context of and connections between data points. Big Data delivers numbers; thick data delivers stories. Big data relies on machine learning; thick data relies on human learning.

In between is the place where you have to understand people: Social science, stigma, and data big or small

Judd and Tamar

Editor’s Note: Judd Antin @juddantin is a social psychologist and user experience researcher who studies motivations for online participation. In 2011, he was named an MIT Technology Review Innovator Under 35. Prior to joining Facebook, he worked with Yahoo Research. His educational background includes Applied Anthropology, Information Science, and training at the French Culinary Institute. One of my favorite papers of his is Readers are Not Free Riders: Reading as a form of participation on Wikpedia (pdf) [1].

Tamar Antin is a research scientist who uses mixed and especially qualitative methods to critically examine public health policies and narratives. She has several years of experience in public health research. One of her recent publications is Food Choice As a Multidimensional Experience [2]. Her dissertation [3] combining three papers on food choices and body image is excellent reading for any student of qualitative methods.

I’ve known Tamar and Judd for several years now, and Tamar has been a mentor to me. Every time Tamar and I talk about research and ethnography, it never seems to last long enough; I just want to ask her more questions. And every time I see Judd, I want to ask him a million questions too. So a post for Ethnography Matters was a great excuse to get together with them for a chat on anthropology, Big Data and Small Data, and other interesting things. – Rachelle

P.S. This isn’t a straight transcript of our conversation but a sort of Frankenstein transcript made out of chopped up pieces sewn back together.

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1. Two Ethnographers
2. What they’re working on
3. Stigma and hacking
4. Qualitative research as art, science and handmaiden
5. Big Data and Small Data

1. Two Ethnographers

What’s your background in anthropology?.

Judd: I have an undergraduate degree in anthro from Johns Hopkins, where I was one of seven anthropology majors I think, like in the whole university. It was a small department. I got interested in anthro primarily because of my adviser, who became our friend, Felicity Northcott. Coincidentally she also married Tamar and I. She was internet ordained and she officiated our wedding. She’s awesome. She was just a very down to earth, foul-mouthed, passionate anthropologist.

Tamar: And for me, I have an undergraduate degree in anthropology also, from the University of Texas. I was having this conversation with the undergraduate adviser there at the end of my senior year, like okay now I have this degree, but I didn’t really know what to do with it. I went to the career center, and they had a list of all the jobs that you could do with certain majors, and I think the only job that was listed for anthropology majors was travel agent.

Judd: What?

Tamar: Oh yeah. I was thinking, well I don’t want to do that.

Judd: Travel agent?!