The Semantic eHumanities Methodology: Same but different.

摘要

The Empirical Humanities, which includes the work of history, folklore, and cultural anthropology, are facing new challenges. For decades, they been an almost entirely individual-centric enterprise. Field notes, observations, collected artifacts, photos, videos, and other cultural data are very rarely shared, except when reduced or rendered into some form of publication or museum display. As these researchers investigate more complex open systems that span many disciplines and languages, they are increasingly finding the need to collaborate across and within their field of study. This, along with new funding requirements, presents the need to share and archive primary collected cultural data. These requirements present new challenges in citing, revealing, sharing and reusing the often invisible work of Empirical Humanities research (i.e. creating templates, questions, methods, protocols, etc.). Humanities scholars need a digital platform that will encourage and facilitate collaboration and allow for experimentation with diverse analytic models. The system must also provide a place to store, share and manage the primary data generated by these scholars. This collaborative digital platform could also provide an opportunity to experiment with new forms of peer review for humanities research, and could be used to develop and evaluate new, digitally-enabled genre forms. To develop such a system, computer scientists and empirical humanities researchers will need to find sustainable ways to plan, design and build together. Past projects in the digital humanities and social sciences have often developed without sufficient involvement of practicing humanities researchers, resulting in systems that aren't used. With this in mind, I turn to the Semantic eScience Methodology. The Semantic eScience Methodology has been developed to help researchers collaboratively build digital infrastructure for the natural sciences by focusing on use cases, formal evaluation, semantic modeling, and rapid prototyping. This methodology has been used successfully in a wide array of science projects to design, build and maintain digital infrastructure and tools. The main aim of this thesis is to test whether the Semantic eScience Methodology can be used to build digital infrastructure for the empirical humanities, particularly in experimental ethnography. As it currently exists, the Semantic eScience Methodology has only been used in quantitative natural science projects. This thesis explores and explains the philosophical and epistemological assumptions of the Semantic eScience Methodology and highlights the different needs and challenges that experimental ethnography places on digital infrastructure. To test this aim, I used the Semantic eScience Methodology to develop a digital platform for experimental ethnography called PECE (Platform for Experimental and Collaborative Ethnography). With this work, I have shown that not only can the Semantic eScience Methodology be used in the context of the empirical humanities, but that many of the tools and technologies used in past eScience projects can also be successfully reused as well. The key difference was how these technologies were used. One of the main outcomes of this thesis is a proposal for a new Semantic eHumanities Methodology that extends the Semantic eScience Methodology by taking into consideration the needs and challenges of experimental ethnography. I have also produced a completed and shareable PECE distribution that has been used and evaluated by empirical humanities scholars in the field.