The qualitative social science community has been engaged in debate about how data can and should be shared for at least the past two decades. The recent NSF requirement for data management plans has reignited these discussions and caused scholars to rethink strategies for preserving and sharing primary data, rather than disseminating findings through publication of synthesized results alone. Additionally, the discipline of anthropology has reached a life cycle stage when many anthropologists may consider archiving their data from studies begun forty or more years ago. Data from these longitudinal studies form a valuable resource for the discipline both as historical documents and as primary data that can serve as a basis for understanding of change over time. Creating systems of archiving that preserve data and facilitate sharing among scholars, while simultaneously protecting confidentiality and study participants, has become an urgent need for establishing a truly 21st century anthropological discipline.
In this project, Dr. Lisa Cliggett (University of Kentucky) addresses this need by developing a digital archive that will serve as a prototype for building a system of data archiving, metadata documentation, and data sharing designed specifically for cultural anthropology. Cliggett will use her own longitudinal data from the Gwembe Tonga Research Project (GTRP) to create the prototype, which will immediately facilitate the useful archiving of more than sixty years of GTRP data collected by Elizabeth Colson, Thayer Scudder, and associated researchers, while also benefiting future GTRP research. Cliggett's archiving system will be designed to be adapted by others in the qualitative social sciences and humanities communities for their own projects. Outcomes of the project include: 1) A prototype digital repository for the GTRP data archive, which other scholars can adapt for their own needs; 2) A Work Flow guide for qualitative data archiving 3) A project web site to disseminate details about the archiving process and other related information; 4) An American Anthropological Association meeting session about qualitative data archiving.
The goals of this project are to make data and knowledge have value beyond purely academic and science settings. By making qualitative data accessible and searchable, the public gains profound opportunities to explore the foundations of knowledge (the data that underlies all scientific knowledge building), as well as gain knowledge about specific research settings and the communities living in those settings (in the case of this specific project, Zambia and the Tonga people of Southern Province, Zambia). Particularly because qualitative data (ie: text) is more "readable" than statistical data and other quantitative data, there is much greater likelihood that the public will seek out these new forms of knowledge via the kind of access this project attempts to create. Among the populations who are most likely seek out these new resources are the people and communities with whom researchers work, and collect data, as well as other interested researchers and members of the public. Currently, the most tangible results from this grant include 2 articles (one in a multidisciplinary journal, another in an edited volume about the digital era of qualitative research), 3 conference presentations, 2 web sites, and a set of files ready for archiving. Perhaps more importantly, this grant has resulted in identifying the key challenges in building a usable qualitative digital archive, particularly one that leverages longitudinal data and data of all types. The PI would welcome communication from anyone working on archiving, or on technological / software development that speaks to the issues below. The key barriers this project has identified (to date) are: 1) The inability of current qualitative data analysis software to incorporate existing codes from text (non-proprietary) files which are required for any long term and durable archiving. This failure means that others hoping to use coded data for new purposes are unable to take existing coded data and ADD their own codes – ie: build on existing analysis and knowledge. 2) Another software limitation, particularly software for anonymizing (that is, concealing proper names and place names, while allowing automated (on demand) replacement of original names), concerns interoperability across software packages. One open source software package has potential in this area (Qualanon, developed at ICPSR, University of Michigan). However, results from this grant indicate that anonymizing software (Qualanon, as of 2014), erases codes created through analysis software (Dedoose, Atlas.ti, etc). The outcome is that anonymizing coded data, at this point in time, requires using MSWord "find and replace" tools – which is a very labor intensive, especially when working with existing data files. However, one lesson from the work on this grant is that anonimyzing labor is minimized in the process of writing new fieldnotes, interview transcripts and other narrative data. This conclusion is a significant finding in terms of how qualitative disciplines move forward with guidelines for data management in the digital era. 3) One other barrier identified through the work on this grant centers on problems in archiving longitudinal narrative data. Coding and anonymizing previously created data sets (such as the Gwembe Tonga Research Project data, from 1956 to 2004) is unrealistic due to the sheer quantity of material in qualitative longitudinal projects. In order to link new but related data to established data sets, while maintaining anonymity / confidentiality is unrealistic, again, due to the vast human labor required. Given this challenge, it is most likely that new digital data cannot be coherently linked through electronic paths, with past data, in a fashion that would allow general access. (Please contact the PI for more detailed information). In addition to the broader impacts mentioned above, this grant offered research and training opportunities to four college students and one MA student. The PI also worked with Information Technology, and Library Science and Information staff, providing opportunities to learn about qualitative research methods and needs, with an outcome of increasing knowledge across scholarly and technology communities.
