Professor Toby Higbie (History) needed to “clean” a digital copy of the American Labor Who’s Who. While he used Optical Character Recognition to recognize the letters, the various types of data were jumbled together, and needed to be separated to enable visualizations of the relationships between the leaders of the movement. He asked HumTech staff to contribute expertise with scripting, to try to programmatically clean as much as possible; and where that failed, HumTech staff have helped manually clean portions of the data, and providing critical instructional technology support when Prof. Higbie asked his undergraduate students to clean portions of the data set as part of teaching them about historiography. Now, HumTech staff are experimenting with linking the individuals in the dataset to the VIAF, to allow other scholars to connect their own relevant data to it.
COVID-19 Instructional Support
HumTech is here to help with moving Humanities finals and instruction online as a result of COVID-19.