The grand challenge of Information Network Academic Research Center is to develop science that enables the modeling, design, analysis, and prediction of behaviors of networks, and to develop fundamental underpinnings to enable humans and networks of disparate information sources to discover and optimize information and knowledge from the full range of structured and unstructured sources.

INARC@UCSB is performing foundational research on network science, leading to a fundamental understanding of the interaction among the social/cognitive, information, and communication networks. Network science is a new and emerging scientific discipline that examines the interconnections among diverse physical or engineered networks, information networks, biological networks, cognitive and semantic networks, and social networks. This field of science seeks to discover common principles, algorithms and tools that govern network behavior. The National Research Council defines Network Science as "the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena." This effort is funded by the US Army and is a part of its Network Science Collaborative Technology Alliance (NS-CTA) that has funded three other centers on social networks, communication networks, and interdisciplinary research.

Figure 1

Specific goals of our Center are to systematically develop the foundation needed for information networks including: (1) entity identification, information extraction, and data integration and uncertainty characterization of multimodal data; (2) construction and access of information network systems; (3) structural and statistical analysis of networks; (4) knowledge discovery in information networks, and (5) robustness, reliability, and trustworthiness of information.

As shown in Figure 1, the INARC is working on the following projects:

  • Project 1: Integrated Modeling and Analysis of Networks (Cross-cutting Research),
  • Project 2: Distributed and Real-time Data-Source Integration and Information Extraction,
  • Project 3: Scalable, Human-Centric Information Network System,
  • Project 4: Knowledge Discovery in Information Networks, and
  • Project 5: Designing Trusted Information Networks (Cross-cutting Research).

In our Projects page, we introduce research milestones that have been achieved on the above five projects in the past 1.5 years including, but not limited to, composite network modeing and analysis, graph data mining, distributed graph processing, graph OLAP, visualization, and trust in infomation networks. A hallmark of our research has been collaborations within and across disciplines and the training of graduate students and post-doctoral researchers in the emerging scientific discipline of network science.