The Office of the Vice President (Research) and the Kule Institute for Advanced Study are collaborating to develop a picture of the richness and variety of social sciences, humanities and fine arts (SSHA) research at the University of Alberta. To that end, we developed a digital Research Map (in beta) based on the websites of all SSHA departments and their full-time faculty members. The tool maps faculty members and their research keywords as well as the connections between them and includes a web-based search interface with network data visualization. We hope this will help us identify new interdisciplinary connections in support of building research capacity and help research administrators appreciate the heterogeneous network of research undertaken in the U of A community.
I was hired as a research assistant by the Kule Institute Director Geoffrey Rockwell to design and developed this network map. The tool/visualization was built using web standards and works in any modern browser.
Learn more here: http://cloud.tapor.ca/viz/phil/
Features
Dataset
Our dataset includes researchers from 11 SSHA faculties, their research interests and departments based on a web scrape of University of Alberta websites from 2015. These are separated into corresponding categories in the ‘Tags’ menu of the side panel that can be searched either by using the search icon or manually reviewing the list. The visualization is populated as you select and deselect tags. The nodes represent tags (Researchers, Departments, and Interests), and the lines the connection between them. For a detailed description of functionalities please use the ‘Help’ menu located at the bottom section of the side panel in the visualization interface.
Layout
The layout menu in the side panel provides additional customization options and can be accessed by clicking on the network icon at the bottom section of the side panel. These additional options include:
Network and cluster view;
Adjusting how nodes react to each other through gravity, charge, distance, and collision detection;
Changing the weight, size, and color of nodes (color coding can be applied by type of tags or by community; the latter is calculated by an algorithm that finds similar clusters based on the number of shared connections);
Changing title and network link size and color.
Export
Export the data or graphic from the on-screen visualization.
CSV and JSON: Both options contain the nodes (researchers, interests, and departments) and their relationship to other nodes.
PNG and SVG: The PNG option generates a raster file with transparent background. All the nodes and links currently present in the visualization. The SVG option generates a vector-based file that can be opened in the browser or in any vector-based image editor.