Microsoft Word - Brooks-Discourses, a Community of Scientists, and Long-tail Data-Discourses, a Community of Scientists, and_ed Selected Papers of Internet Research 16: The 16th Annual Meeting of the Association of Internet Researchers Phoenix, AZ, USA / 21-24 October 2015 Suggested Citation (APA): Brooks, C. F., Heidorn, P. B., Stahlman, G., and Chong, S. (2015, October 21- 24). Discourses, a community of scientists, and long-tail data in the cloud. Paper presented at Internet Research 16: The 16th Annual Meeting of the Association of Internet Researchers. Phoenix, AZ, USA: AoIR. Retrieved from http://spir.aoir.org. DISCOURSES, A COMMUNITY OF SCIENTISTS, AND LONG-TAIL DATA IN THE CLOUD Catherine F. Brooks University of Arizona P. Bryan Heidorn University of Arizona Gretchen Stahlman University of Arizona Steven Chong University of Arizona Data in the Sciences Data collection, use, and management are significant activities in the scientific enterprise, and are evolving given the onset of a big data world. Many scientists (e.g., scholars or instructors) do not have access to the computing infrastructure needed to work with large data sets. This is particularly true at many biological research stations – while some stations are part of or loosely affiliated with major universities, others are stand-alone entities. The station researchers are relatively transient, spending seasons at the stations then returning to their home institutions – their data scatter in their differing formats (Estrin et al., 2003). This is particularly true for little data that often do not conform to established standards (Borgman et al., 2007). Previous research on the long tail of data (Heidorn, 2008; Palmer, Cragin, Heidorn, & Smith, 2007) suggests that a significant portion of data collected in previous eras was actually lost or went unused, data collected may have been used for specific projects then left to die on floppy disks or personal computers. Data sharing on cloud-based platforms provides a way to share costs for needed infrastructure and offers hope that previously-lost ‘dark’ data will be brought to light. Discussions of day-to-day computing needs and data-sharing possibilities are an important initial step in enabling problem- solving for contemporary scientists – facilitating this type of discussion was the focus of the workshop interrogated in this study. Data sharing and related infrastructure dilemmas are of interest across a wide variety of scientists, salient for those engaging with ‘little’ or big data. Scientists tend to work with technologist and engineers as part of their working teams (smaller projects often rely on graduate students working in laboratories). So, it is easy to imagine the ways in which shifts in scholarly practice, data collection, and the management of information – especially in an age of big data – are of paramount importance across sectors and to those coming from the entire research spectrum. To interrogate contemporary concerns in science about data management, particularly that in the cloud, the following research question was posed: RQ: How do issues with sharing data in the cloud get discursively situated by an interdisciplinary group of scientists? Method This qualitative work (Miles & Huberman, 1994) drew themes from within the data themselves, and followed protocols that are well established in qualitative research traditions (Lindlof, 1995). Data collection and organization was IRB approved and involved the audio recording of whole-workshop talk between a leader and workshop attendees. These recordings were then transcribed and analyzed. This qualitative work (Miles & Huberman, 1994) drew themes from within the data themselves, and followed protocols that are well established in qualitative research traditions (Lindlof, 1995). Data collection and organization was IRB approved and involved the audio recording of whole-workshop talk between a leader and workshop attendees. These recordings were then transcribed and analyzed. The central premise of the workshop was that new science could be enabled through the development of shared cloud-based cyberinfrastructure. The work was funded under the National Science Foundation’s Software Infrastructure for Sustained Innovation program1. Alongside one primary workshop leader, there were three other workshop facilitators, 29 participants, and five assisting doctoral students. Findings: Framing Shared Problems As described previously, these scientists came together to resolve a shared problem, considering tools that can support sharing data in the cloud. If dark data from smaller projects were drawn together, scientists would have a broad set of data available to them. Shawn, the workshop planner began the first meeting by explaining dark data: Gyou could pull it together and get to a critical mass to make it easier to share and useful for science. He continued to explain that if scholars share and work together though the Internet or other web-based platforms, more data will be made available, viewable, and usable – 1 This workshop was sponsored in part by the National Science Foundation through the following collaborative SI2-S2I2 grants: 1216726, 1216754, 1216872, 1216879, 1216884. http://www.nsf.gov/si2/ data will become increasingly ‘democratized’ and access across communities of scholars and practitioners will be enhanced. As Shawn continued, Gthere is a huge growth in the amount of data that we can acquire. Sequenced data, in particular, is outstripping the Moore’s Law, so, in fact, the amount of data we have is growing faster than our computing capacity to process that data. To give context for the current interrogation, then, Shawn’s talk shows that shifts in computing infrastructures and cloud-based solutions need consideration. Findings: Capital, Commercialized Threats, and the Economy of Innovative Science In some ways, sharing data on the cloud implies trust of commercial interests. In such an environment, data become the commodity providing a rich place for commercialized competition. Moderator: G programs, like [those with] Amazon Gthat are put in place for science dataG they’ll take data, literally for free, and host it for free within certain constraints that they’re still often a little fuzzy aboutG Participant: Right. Moderator: I think this is actually a wingding for everybodyG Indeed, commercial concerns were continually voiced relative to companies like Amazon and Google, as Shawn discussed: Some of you may remember that Google would send you a suitcase with a hard drive that said, “Just send your data. We’ll take care of the rest.” It took them less than six months to close that program downG [Laughter] For these scientists, individualized academic culture, institutionalized legal concerns, and a broad capitalist culture were all considered disruptions or barriers to the common scientific enterprise and to ‘figuring out’ how to share and manage data with and through contemporary Internet, web, or cloud-based tools. Conclusion Contemporary science has witnessed recent shifts that are powerful, cultural, and sit within and well beyond the confines of academia. The very nature of our knowledge- related capabilities has changed. Computing infrastructure is needed, most practicing scientists cannot manage those needs alone. This study provides an early glimpse of how these issues are situated by scientists and in relation to the broader milieu in contemporary science. References Borgman, C. L., Wallis, J. C., & Enyedy, N. (2007). Little science confronts the data deluge: Habitat ecology, embedded sensor networks, and digital libraries. International Journal on Digital Libraries, 7(1-2), 17-30. Estrin D, Michener W, Bonito G, and the workshop participants (2003) Environmental Cyberinfrastructure Needs for Distributed Sensor Networks: A Report from a National Science Foundation Sponsored Workshop. Scripps Institution of Oceanography, La Jolla, CA. August 12-14, 2003. Heidorn, P. B. (2008). Shedding light on the dark data in the long tail of science. Library Trends, 57(2), 280-299. Lindlof, T. R. (1995). Qualitative communication research methods. Thousand Oaks, CA: Sage. Mayernik, M. S., Batcheller, A. 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