The Ethnographer’s Complete Guide to Big Data: Small Data People in a Big Data World (part 1 of 3)


Statistics House, Kampala, Uganda

Part I: Questions

Research is hard to do. Much of it is left to the specialists who carry on in school 4-10 more years after completing a first degree to acquire the proper training. It’s not only hard to do, it’s also hard to read and understand and extrapolate from. Mass media coverage of science and social research is rife with misinterpretations – overgeneralizations, glossing over research limitations, failing to adequately consider the characteristics of subject populations. Does more data or “big data” in any way, shape, or form alter this state of affairs? Is it the case, as Wired magazine (provocatively…arrogantly…and ignorantly) suggests that “the data deluge makes the scientific method obsolete” and “with enough data, the numbers speak for themselves?”

Being an ethnographer makes me more of a “small data” person. It seems counter-intuitive at first, but I find there are good, sound reasons to sometimes forgo the opportunity to collect more data. This gets to ever present questions about how much is sufficient when doing qualitative or, more specifically, ethnographic research (i.e. how many people to interview? how many months to spend in the field? etc). I find memory limits are an important bounding factor. Can I remember key points from each interview, distinctive elements of that individual’s story? Can I recall the setting and some of the things I observed there? Reading a transcript or my field notes, can I put myself back in that time and place? To have good recall and mastery of your data helps you to move through it with agility and to draw the kinds of surprising thematic connections across data that make ethnographic work, at times, profound. As much as qualitative data analysis software (like NVivo or Atlas TI) aids in rediscovering whats in your data through coding and keyword search, I find the flexibility of my brain is indispensable in drawing connections that no search algorithm would make. If I have all the data for a project more or less sketchily outlined in my memory then if I don’t recall something exactly, at least I know where to look. Otherwise it is too easy to draw haphazardly and selectively from data.  It is easy to overlook counter-examples, contradictions, and challenges to my emerging claims if the mountain of data becomes too tall.

Leading into a data science conference my department (DataEdge) is hosting this week, I want to list some questions that I (and maybe other ‘small data’ people) have about the big data / data analytics trend. These questions arise from my ethnographic orientation and an interest and history in applied research. For me, they are the following:

  • What do researchers consider the most compelling examples, the ‘showcase’ applications of big data that involve study of the social world and social behavior?
  • To what end is such a research approach being put? What actions are being taken on the basis of findings from ‘big data’ analysis?
  • The data analytics discussion appears to be US-centric debate … how well are researchers grappling with the analysis of ‘big data’ when dealing with data collected from across heterogeneous, international populations?
  • How do ‘big data’ analysts connect data on behavior to the meaning/intent underlying that behavior? How do they avoid (or how do they think they can avoid) getting this wrong?
  • How might the analysis of ‘big data’ complement projects that are primarily ethnographic?

For good measure, a couple of interesting, probing takes on big data:

Following the DataEdge conference, I will try to address some of these questions and offer some answers through a conference recap.

___________________________________________________________________

Read the rest of the posts in the “The Ethnographer’s Complete Guide to Big Data” series:
The Ethnographer’s Complete Guide to Big Data: Answers  (part 2 of 3)
The Ethnographer’s Complete Guide to Big Data: Conclusions  (part 3 of 3)

Tags: , , , ,

16 Responses to “The Ethnographer’s Complete Guide to Big Data: Small Data People in a Big Data World (part 1 of 3)”

  1. May 30, 2012 at 6:42 pm #

    Sometimes I wonder whether the material generated by some ethnographic research is even possible to categorize as small data or big data. It seems like trying to — pardon the cliche — fit a square peg in a round hole. It reminds me of literature on art about the difference between an analogue photograph and its digital counterpart.

    Certainly, we can make data quantifiable. Then big data folks can argue about how much data is need to cross the threshold from a lot of data points to “big data” (based on number of terabytes, number of physical machines required to store data, process data, etc).

    Perhaps the counterpart in ethnographic work is the question of how much time in the field is “enough” (a tiring argument!). How much data is represented by a collection of fieldnotes? Or are fieldnotes the data and then easily quantified again by the size of the file (“small data”). Doesn’t the material elicited from fieldnotes continually change in some ways? Is a year in the field really “small data”?

    Anyhow, pardon the rambling. I am looking forward to your notes following the conference. I have many of the same questions you ask here and am curious to see what answers you find.

Trackbacks/Pingbacks

  1. Putting people first » Ethnographic research in a world of big data - June 1, 2012

    […] Jenna Burrell, sociologist and assistant professor in the School of Information at UC-Berkeley, lists some questions that she (and maybe other ‘small data’ people) have about the big data / data analytics […]

  2. The Ethnographers Complete Guide to Big Data, Part II: Answers | Ethnography Matters - June 11, 2012

    […] The idea that big data might usher in a new era of automatic research and along with it researcher de-skilling or that it would render the scientific method obsolete did not prove to be a popular sentiment (*phew* sigh of relief). The point that data isn’t self-explanatory, that it needs to be interpreted was reasserted many times during the conference coming from people who occupy very different roles in this data science world. No need to panic, let’s move along to some answers to those questions I raised in part I. […]

  3. Putting people first » Ethnographic research in a world of big data – Part 2 - June 11, 2012

    […] up on her earlier piece on ethnographic research in a world of big data, Jenna Burrell, sociologist and assistant professor […]

  4. 3×5: Culture, Neuroscience, and Psychiatry Weekly Roundup (June 19) | thefpr.org blog - June 18, 2012

    […] The Ethnographer’s guide to big data, part 1 and part 2. Jenna Burrell’s dispatch from the DataEdge conference hosted by UC […]

  5. 3×5: Culture, Neuroscience, and Psychiatry Weekly Roundup (June 19) | thefpr.org blog - June 18, 2012

    […] The Ethnographer’s guide to big data, part 1 and part 2. Jenna Burrell’s dispatch from the DataEdge conference hosted by UC […]

  6. The Ethnographer’s Complete Guide to Big Data: Conclusions (part 3 of 3) | Ethnography Matters - July 2, 2012

    […] rest of the posts in the “The Ethnographer’s Complete Guide to Big Data” series: The Ethnographer’s Complete Guide to Big Data: Small Data People in a Big Data World (part 1 o… The Ethnographer’s Complete Guide to Big Data: Answers  (part 2 of 3) Share […]

  7. Web Round Up October 2012 | Somatosphere - October 16, 2012

    […] says Wikipedia. Big data in anthropology has already been discussed, for example by Jenna Burrell at Ethnography Matters. In her three-installment post she links the use of big data to a hope of being able to better […]

  8. All This ChittahChattah | Big Content/Big Data Quickies - November 8, 2012

    […] The Ethnographer’s Complete Guide to Big Data: Small Data People in a Big Data World [Ethnography … – Jenna Burrell has a three-part series of posts looks at qualitative cultural work and both traditional and emerging approaches to larger and larger data sets. […]

  9. In between is the place where you have to understand people: Social science, stigma, and data big or small | Ethnography Matters - November 14, 2012

    […] Right, it’s different. In qualitative research, the human is the analyst. Jenna says this, right? She says something about that she only has so much ability to remember things when she’s […]

  10. Ethnography Matters - November 14, 2012

    […] Right, it’s different. In qualitative research, the human is the analyst. Jenna says this, right? She says something about that she only has so much ability to remember things when she’s […]

  11. April 2013: Ethnomining and the combination of qualitative & quantitative data | Ethnography Matters - April 2, 2013

    […] Many of the issues were brought up in contributing editor Jenna Burrell’s series, “The Ethnographer’s Complete Guide to Big Data.” We hope this month’s edition continues to extend the conversations around ethnography […]

  12. Big Data Needs Thick Data | Ethnography Matters - May 13, 2013

    […] of inferring correlations, Samuel Arbesman calls for us to move on to long data. Our very own Jenna Burrell has produced a guide for ethnographers to understand big […]

  13. Investigación: entre la etnografía y la minería de datos (Big Data) | juandon. Innovación y conocimiento - May 21, 2013

    […] http://ethnographymatters.net/2012/05/28/small-data-people-in-a-big-data-world/ Etnography Matters […]

  14. July 2013: Ethnography in Education | Ethnography Matters - July 11, 2013

    […] to evaluate these reforms has its allure (and can be useful in ethnographic research, as Jenna and Ayman have shown us in previous posts), ethnography is unique in being able to dig below the […]

  15. Studying Up: The Ethnography of Technologists | Ethnography Matters - March 10, 2014

    […] with an interest in big data have worked hard to define what they do in relation to these other methods. Ethnography, they argue, provides thick, specific, contextualized understanding, which […]

Leave a Reply