STICK Framework
In order to help SciSIP researchers understand the Innovation Eco-system, we designed the STICK system - an innovation knowledge-base with analytic and visualization tools. Figure 2 illustrates the overall framework of the system.
STICK contains two main modules:
- the innovation knowledge-base
- the analytic and visualization toolset
The innovation knowledge-base is built upon various data sources such as the academic and trade publications and government support and patent data from the STAR database. The knowledge-base will store longitudinal and comprehensive data on innovation-related entities (e.g., innovations, people, and organizations, and sentiments about the innovations), relationships among the entities, and additional description of entities and relationships. In order to make the knowledge-base scalable and sustainable, we use a hybrid approach that combines automatic entity and relationship detection and Social Information Processing (SIP)3 mechanisms that enables members of each innovation community to contribute to the content of the knowledge-base through a collective effort.
Above the knowledge-base is the analytic and visualization toolset that facilitates operations on and representations of the innovation networks, the evolution patterns of innovations, and interactions among innovations, innovation communities, or between innovations and communities. We will integrate the analytic and visualization tools: Analytic tools will be used to identify elements of interest to visualize; and visualization tools will be used to derive understanding of the results from computational or statistical analysis. SciSIP researchers and the diverse members of the innovation communities will be the users of STICK, including its visual analytic tools and the knowledge-base.
Together, the knowledge-base and the toolset will help SciSIP researchers understand relationships, identify patterns, and test models and hypotheses. The research findings on the popularity of innovations will then be presented to the members of various S&T innovation communities.
