University-community partnerships can be highly beneficial to both parties through the sharing of critical empirical knowledge and cutting-edge scientific research. However, these partnerships can be difficult to facilitate. One notable difficulty with these relationships is identifying potential partners with similar interests. Although many community organizations and university researchers have websites and online profiles that describe their interests, these can take enormous amounts of time, energy, and resources to locate, read, and process.
Currently, partnership connections rely heavily on manual searches and the latent knowledge of key individuals. This limits the extent to which relationships are brokered, and may exacerbate bias or power relations. Potential opportunities for novel configurations of collaboration go unrecognized, and the decision about outreach to community stakeholders often happens after the research has already been developed or designed. There is a need for tools that can streamline this process and reduce the burdens of time, energy, and effort that are currently required to identify potential partnerships.
Researchers at Arizona State University have developed the novel Knowledge Alliances Tool, which provides a search interface that enables users to search for potential partners based on similarities in shared work topic interests. This invention uses both text and semantic network analysis methods to process the information from online university researcher profiles and community organization websites to identify the topics and shared interests that the groups have in common. The search platform within the tool enables users to type their name, organization name, or a research topic and identify researchers and organizations with similar interests.
The tool incorporates a project proposal matching feature, which identifies potential matches based on an uploaded project proposal or research description document. There is also a collaboration rosters feature, which gives users the ability to save searches of potential collaboration partners and create rosters for meetings or proposal development purposes.
- Identification of potential university-community partnerships (likely expansion to data on private sector entities)
Benefits & Advantages
- Detection of potential partnerships between university personnel and non-university organizations
- Generation of matches based on an uploaded project proposal or research description document
- Ability to save searches of potential collaboration partners and create rosters for meetings or proposal development
Inventor Bio: Mason Mathews | Knowledge Exchange for Resilience