With support from the Institute of Museum and Library Services, Always Already Computational: Library Collections as Data will foster a strategic approach to developing, describing, providing access to, and encouraging reuse of library collections that support computationally-driven research and teaching in areas including but not limited to Digital Humanities, Public History, Digital History, data driven Journalism, Digital Social Science, and Digital Art History. In the first stage, a national forum will bring together an expert group of librarians, archivists, museum professionals, researchers and practitioners, and technologists for 2.5 days at the University of California Santa Barbara from March 1 – March 3, 2017.
the sourcecaster helps you use the command line to work through common challenges that come up when working with digital primary sources.
A data curation record supports reuse of data and reproducibility of claims by documenting data source(s), data types and formats, data quality, as well as methods and tools used to subset, transform, augment, and derive insight from data.
Data praxis highlights a range of perspectives on the practice of digitally inflected research, pedagogy, curation, and collection building and augmentation. Topics span methods and tools in the context of research questions and/or exploratory trajectories, and extend to consider reflections on data definition, access, curation, sharing, and reuse.
This guide is a companion to the Data Preparation for Digital Humanities Research workshop. It is designed to help you begin using OpenRefine to: ☞ facet data ☞ filter data ☞ cluster data ☞ transform data.
This guide will help you: ☞ Visualize network data ☞ Measure network data ☞ Describe features of network data