I’m a reference and systems librarian at the U.S. Holocaust Memorial Museum, and as such I work with historians at all stages of their career who are utilizing the primary and secondary sources in the Museum’s Library and Archives. I’ve also been helping Rebecca Erbelding, an archivist at the Museum and an ABD in history at George Mason University, in constructing her personal digital archive of more than 30,000 documents (not images; PDF documents, ranging from a single-page memo to a 100+ page report, almost all created from photographs of primary sources from various archives), all while retaining relevant metadata. About a year ago, I took what Rebecca and I had learned about how to build a useful personal archive and did a well-received workshop at the Museum for visiting Fellows. We realized today, during a talk about personal archives and big data sets, that some AHA participants might be interested in this workshop. Rebecca and I are proposing to lead a how-to session to provide a framework for the step-by-step process of constructing a personal digital archive of all the photos and scanned documents you have created as part of your research, incorporating them into software that allows you to analyze the documents and, if you want, export your work into fielded data sets (all with no or minimal programming or coding skills). You can adapt or reject any aspect of the framework to make it work for you, but if you truly have no idea how to get from zero to personal archive, we might be able to help. This could certainly build upon (or lead into) Jordan’s proposal for a discussion about “Notecards for the New Century.“

Patrick Murray-John, Research Assistant Professor at the Roy Rosenzweig Center for History and New Media at George Mason University, has agreed to offer an Omeka workshop at THATCamp AHA2014. Thanks, Patrick!

Omeka is a simple system used by scholarly archives, libraries, and museums all over the world to manage and describe digital images, audio files, videos, and texts; to put such digital objects online in a searchable database; and to create attractive web exhibits from them. In this introduction to Omeka, you’ll create your own digital archive of images, audio, video, and texts that meets scholarly metadata standards and creates a search engine-optimized website. We’ll go over the difference between the hosted version of Omeka and the open source server-side version of Omeka (we’ll work from the server version), and we’ll learn about the Dublin Core metadata standard for describing digital objects. We’ll also look at some examples of pedagogical use of Omeka in humanities courses and talk about assigning students to create digital archives in individual or group projects.

Lincoln Mullen, a Ph.D. candidate at Brandeis University, has agreed to repeat the hands-on workshop on using statistical programs to analyze data sets relevant to humanities scholars that he offered at THATCamp AAR in November 2013. Mullen has also agreed to hold a kind of THATCamp office hours after his workshop, where he’s agreed to work one on one with interested campers. Thanks, Lincoln!

Humanities scholars now have access to a range of data sets and techniques for analyzing them that were previously regarded as the province of scholars in other disciplines. In this workshop, we’ll try our hands at a couple forms of analysis, using data sets of interest to scholars of religion. We will make maps from the missions of the Paulist Fathers and do some quantitative analysis of religious demographic data. By bringing these common kinds of data analysis together, we will learn the basic practices and theories which underlie all of them. Of course we will have occasion to discuss what data analysis means from a humanistic perspective. During this workshop we will get hands-on with the statistical programming language R. While there are many tools to make maps, mine texts, and analyze numbers, R is especially powerful because it can perform all of these types of analysis. R is a favorite tool of academics, Google, and the New York Times, so it has strong support. You are encouraged to install R (the programming language itself) and the desktop version of R Studio (a tool to help you use R) in advance. Self-starters can watch some of Google’s video introductions to R to acquire the basics. While you will benefit from learning some of the theory behind the analysis even without using R, there is no substitute for performing the analysis yourself, and you’ll pick up the basics of a powerful digital humanities tool.