Our Data Scavenger Hunt seeks to playfully engage Annual Meeting attendees around ideas about data, across the discipline's various fields and contexts, but also in relation to broader arguments currently being voiced about data as necessary for validation of knowledge claims and part of the public footprint of science (including the social sciences).
We envision this event as a fun way to enliven serious conversations within and across the discipline of anthropology about our relationships to data, diverse sorts of data, and how these data are encountered and circulate.
This special event builds on a recent NSF-funded workshop that explored calls for transparency through data sharing, and the ways such calls might not be easy, possible, or even legible, for certain kinds of qualitative or interpretive social scientific practice. The hunt will conclude with an organized reception in San Jose Convention Center, Blossom Hill I, from 4:00 to 6:00 p.m., during which the winner will be announced and different stories, and challenges, of data collection discussed and explored.
In interdisciplinary terms, this workshop asked the following questions about data
1. At what point in your own work does one thing (e.g. “knowledge” or “information” or “field notes” or “raw data”) become recognizable and legitimate as something else (“research data”)?
2. And what has to happen to enable such a transformation?
From the vantage point of their own disciplinary training and research experiences, we ask AAA attendees to consider the same issues, now as part of a scavenger hunt.
Extending the workshop’s conversation, we suggest that any call for data transparency already assumes much about data, and encourages us to tell specific data stories and not others. The Data Scavenger Hunt extends the workshop’s discussion as a way to promote precise and nuanced deliberation within and across anthropology about what data are and how anthropologists variously relate to data.
We envision the hunt as an entertaining vehicle for encouraging more public discussion about our own relationships to data, in this case, through how we find, encounter, or collect them. As participants in the hunt undertake to find the kinds of data listed, they will also record the necessary steps involved, whether successful or unsuccessful. These will amount to short stories about how these data were “found” (or not), including any challenges – methodological, ethical, and otherwise – encountered along the way. Depending on the data, these can even be fictional, so long as they are realistic. These stories, and associated challenges, will be explored at the reception event during the Annual Meeting.
We hope the Data Scavenger Hunt promotes attention to: where data are specifically located, how this works, how specific kinds of data are found (or collected), and what steps one might need to undertake for the collection of diverse sorts of data. By training attention on the processes, and key moments, involved in data-making, we hope to highlight their contingent qualities, and to better situate anthropology's historically plural orientation to diverse data traditions with respect to the social sciences.
Directions/Suggestions For Completing the Data Scavenger Hunt:
- For the purposes of the Hunt, we invite you to identify the specific kind or type of “data” in which you are most interested, from the following list of options (from now on we will use the short hand: material, non-material, archival, event, bricolage, and wild card):
- The material (or empirical): you must provide a material artifact that is significant to the culture in which you’re working/to which you belong.
- The non-material: you must provide something non-material that is significant to the culture in which you’re working/to which you belong (e.g. a story, myth, or symbol).
- Archival: you must provide a type of archival data (textual, digital, or audio-visual), which documents something otherwise contested in the culture in which you are working/to which you belong.
- Event analysis/performance/social drama/epitomizing moment: you must provide an example of a meaningful event, explain why it is indeed an event, and what makes it significant. This needs to be drawn from the AAA meeting itself.
- Bricolage: you need to provide an example of data generated in order to address a topic or answer a question about the culture in which you are working/to which you belong. This can mix data sources but also needs to be drawn from the AAA meeting itself.
- Wild card: this is intended to provide an opportunity for collecting data about the culture in which you are working/to which you belong, that might not otherwise be covered by the first five categories. You must explain why this is the case.
- These data (or the failure to collect them) can be: selected from your own current or past research, collected directly as part of the scavenger hunt (beginning now, although some categories of data can only be collected during the AAA meeting itself in San José; see list above), or you can provide a “fictional” narrative of a plausible collection process (and associated challenges).
- Once you’ve selected a specific sort of data, we ask that you then describe the stepwise process of its/their “collection” (in ways publicly sharable). What steps, in short, did you need to take to successfully obtain this data (or if unsuccessful, what were your proposed steps, and why were your efforts unsuccessful)? Please offer a brief (here and throughout, 3-5 sentence) description of each step or phase in the data collection process. How you decide what counts as a “step,” and how many steps you include, will of course go a long way to determining what sort of data story you end up telling.
- Describe your specific relationship to these data: how you decide to describe this is largely up to you. Common ways to talk about data relationships include: proprietary; primary; secondary; anonymous; shared by project collaborator or research subject; interpretable; subjective; objective; empirical; measurable; some, none or all of the above; something else entirely.
- Describe any key conditions or circumstances responsible for determining/circumscribing the context or particular parameters for this relationship (e.g. professional ethics codes, human subject requirements, the terms of institutional or personal access, technological requirements, gender, where these data can/cannot circulate, among many other possible factors).
- We are particularly interested in the ways “information” (we prefer “stuff”, but pick your value-neutral term of choice) is transformed into “research data” for anthropologists. Given this, we invite you to think about what, if anything, need be added to the datum (whether material, non-material, archival, event, bricolage, or wild card) in order to turn it into research data. Briefly describe what this additive process (or non-additive, as the case may be) consists of for this case.
- Describe how you think these data are specifically anthropological (we leave the many embedded questions in this broad question for you to answer).
- Finally, were you successful in meeting your initial data goals? Did these goals have to change in significant ways over the course of the data collection process? Were you unsuccessful? Whether successful or unsuccessful, briefly describe the major challenges encountered as part of your data quest.
Once you’ve completed the Hunt, please upload your data story via email to amanthdatahunt@gmail.com. Please also join us for the reception to announce the winner of the Hunt and discuss some of the challenges encountered by participants on Saturday, November 17, 4:00 to 6:00 p.m. Modest food and drinks will be served.
