1Starting in the spring of 2017, humanities faculty and graduate students Florida State University have been working to create a Prosopographies Working Group, where participants explore methods for collecting and analyzing structured data around people. With help from faculty University Library faculty and staff (such as myself), faculty and graduate students have been given the space, time, and resources to begin creating datasets and learning essential data skills. The members of this group span from veteran users of digital methods to novices to data creation and analysis. While this group utilizes many different standards of data creation, the TEI namesdates module and the TEI’s concept of the “personography” have been essential for teaching many of the fundamental concepts of humanities data. This paper will use experiences gained from this working group to discuss methods for teaching broader concepts of data skills and “data literacy” to advanced humanities practitioners, who are highly skilled in using traditional methodologies, but who may be new to certain technological and data-centric skills.

2By utilizing the TEI personograpies for their data-focused research, participants have been able to explore important concepts of data management that they were not taught during their formal education. They have grappled with new ways of organizing and designing their research by exploring concepts like data types, constraint, and transformation. Additionally, using the TEI has forced participants to address the scope and scale of their research project in ways that traditional humanities prose writing has not. The use of the TEI standard has honed their data collection abilities. It has also encouraged them to look at their research resources in a new light: specifically making them think about their sources as data. This paper will discuss how the TEI, and specifically the “personography” can be used to translate humanities scholars’ inherited modes of thinking about knowledge production into a new data-driven way of approaching research. I will explore the ways in which using TEI for pedagogical purposes can lead to broader data literacy skills, even for researchers and practitioners whose focus may not lay primarily with textual studies and digital editions.

3Concepts such as data constraint and transformation are essential to creating rigorous digital scholarship, but often humanities faculty and graduate students in U.S. institutions are left to teach themselves these skills. Using discussions with the faculty and graduate students in this working group, this paper will explore the ways in which the Text Encoding Initiative can be used to teach these essential data skills to researchers whose primary point of contact with data may not come in traditional classroom settings. Additionally, I will explore how to embed these skills and concepts into the classes that these faculty and graduate students teach. Much of this paper will rely on the context of an American public institution to describe the challenges of integrating digital humanities into the undergraduate classroom, but the discussion will be applicable to other institutional contexts. Through discussing my work with these advanced scholars, I hope to gesture towards the ways that the TEI can be utilized to open up new possible models for pedagogy and iterative learning in the academy.