I am very interested in data curation skill sets required by the historian: What does data curation mean for the humanist? What do humanists need to know to work with data effectively? What skill sets are needed by the historian that analyzes and shares their data in digital form? What skill sets does the “average” historian need to have in dealing with data in digital formats (ex. .tiffs of rare texts from an archive, oral histories, pdfs of articles, video)? How do historians create effective research workflows? How does the historian effectively “archive” data in ways that can be shared in collaborations with other scholars? How do historians compartmentalize and standardize the collection of data for projects with their students?
There has been a great deal of discussion in the news lately about the cost of colleges texts and rightly so. But not all Open Educational Resources are created equal, and most have been aimed at introductory classes or at replacing textbooks. That can be quite helpful, but that doesn’t always meet the needs of upper-level undergraduate or graduate history classes.
I propose a session in which we talk about existing openly available resources for teaching history, identify the key components in good resources, discuss the possibilities of working with students to create openly available resources of our own, and collaborate on a Google doc to share those ideas.
I titled this “obligatory” because the issue of convincing departments, administrators, hiring committees, and tenure and promotion boards of the value of digitally enabled scholarship and teaching has been coming up since the very first THATCamp in 2008 (and most of the hundreds since then). The advantage of the question coming up that often is that lots of people have had chances to talk about it and even formulate some responses. [The AHA itself released its Guidelines for the Professional Evaluation of Digital Scholarship by Historians just this year.] And yet, each situation, each school, each project, each individual’s work is different, so it continues to be a topic worth discussing.
So, I propose a session where we discuss people’s concerns in this area, talk about strategies others have used in the past, and talk about the ways that the AHA’s new guidelines provide some structure for the profession going forward.
I’d love to compare notes among people who are using mapping for DH research projects. I’m particularly interested in moving away from GIS (e.g. ArcGIS or QGIS) and GIS-in-the-browser (e.g., CartoDB) to using the various libraries that let us create our own custom maps. For me that looks like the leaflet and lawn (an R wrapper around Turf.js) packages for R, tied together with the Shiny web framework. But I’d like to know what everyone else considers the state of the art in mapping for DH, and how they are using it.
As a part of that, this session could also include people showing the projects that they’ve worked or otherwise admire, and talking about next steps for coming up with meaningful conclusions from DH mapping data.
Or we could just talk about how awesome Shiny is.
An iron law of DH software is that it is easier to use than to install. Philip Guo has memorably identifed the problem in a post titled “Helping my students overcome command-line bullshittery.” I’d like to talk about ways teachers, whether at the undergrad or the grad level, use to overcome this problem. How do we get students into the real work (necessary complexity) while avoiding as much as possible the unnecessary complexity of installing and configuring software? Or, in some cases is there pedagogical value in understanding how computers really work, such as by dealing with the Unix command line?
I can explain what I’m planning to do with my graduate class using RStudio Server this semester, and I hope that others have their own techniques.