This project will design, evaluate, and operate a unique distributed, shared resources environment for large-scale network analysis, modeling, and visualization, named NetWorkBench (NWB). The envisioned data-code-computing resources environment will provide a one-stop online portal for researchers, educators, and practitioners interested in the study of biomedical, social and behavioral science, physics, and other networks.
The NWB will support network science research across scientific boundaries. Users of the NWB will have online access to major network datasets or can upload their own networks. They will be able to perform network analysis with the most effective algorithms available. In addition, they will be able to generate, run, and validate network models to advance their understanding of the structure and dynamics of particular networks. NWB will provide advanced visualization tools to interactively explore and understand specific networks, as well as their interaction with other types of networks.
A major computer science challenge is the development of an algorithm integration framework that supports the easy integration and dissemination of existing and new algorithms and can deal with the multitude of network data formats in existence today. Another challenge is the design and implementation of an easy to use menu-based, online portal interface for interactive algorithm selection, data manipulation, user and session management. The NWB will be evaluated in diverse research projects and educational settings in biology, social and behavioral science, and physics research. It will be well documented and available as open source for easy duplication and usage at other sites. An annual summer school and a series of workshops and tutorials are planned to introduce the tool to diverse research communities.
The NWB will provide members of the scientific research community at large (biologists, physicists, computer scientists, social and behavioral scientists, engineers, etc.) with the means to carry out network analysis, modeling, and visualization projects in their own fields. This will result in a direct transfer of knowledge and results from the fields of specialist network research to a wider scientific community. Researchers will have access to validated algorithms that in the past have been obtained through time-consuming personal developments of ad hoc computer programs. The NWB is expected to enhance and encourage the empirical analysis and model validation of networks, generating an eventual acceleration in the development of network science research. Online instructional material will support the use of the NWB in educational settings.
The NWB will provide a unique tool for network science researchers in many disciplines. In effect, NWB can deploy the knowledge accumulated in network theory and practice across sciences with just one web click to any interested researcher, practitioner, or student. The NWB shared resources environment will speed up and ease network science applications and education in biology, social and behavioral science, and large infrastructure analysis, thereby accelerating the rate of scientific discovery.
