We are developing a Visual Analytics Digital Library (VADL) to support instructors building new visual analytics courses and students and others who simply seek to learn more about the area. The VADL includes articles, course notes, lecture slides, video lectures, homework exercises and other useful items. By accumulating all these materials at one site, we provide a convenient and easy-to-access collection.
Together with researchers at the other RVACs and at NVAC, we developed a taxonomy that serves as the organizational framework for the materials. Generalized search capabilities are provided, and viewers also can search by material type such as PowerPoint slides or documents. Our goal is to provide a flexible set of exploration possibilities to help people with differing objectives to use the VADL.
The VADL home page, shown in the figure, includes a conspicuous SHARE link. We hope that you will contribute. Our goal is to make this site the place to go for accessing visual analytics focused documents and materials. This project is led by Jim Foley.