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Description
Universities increasingly recognize the value of interdisciplinary collaboration as a powerful way to tackle complex challenges. However, establishing effective partnerships across institutions, industry, and government is often difficult due to siloed organizational structures and language barriers between sectors.
The Ohio Innovation Exchange (OIEx) provides a centralized web portal enabling users to discover expertise, research opportunities, intellectual property, and specialized equipment and services across Ohio's higher education landscape. Built upon Symplectic Elements, OIEx directly facilitates connections between academia and industry partners to foster collaboration and innovation.
Simply bringing potential collaborators together is often not enough: effective partnerships depend on clear communication and shared understanding. Industry practitioners often describe emerging technologies in terms unfamiliar to academics, who instead reference more traditional disciplinary frameworks. This linguistic disconnect creates challenges when industry users seek academic expertise.
To address these dual challenges of language barriers and researcher time constraints, OIEx is partnering with Digital Science to explore the potential of two complementary AI-powered approaches:
- Generative AI-driven search: Integrating generative AI models within researcher profile searches to translate and interpret user queries from industry partners, allowing for intuitive discovery of academic expertise despite differing vocabularies and linguistic approaches.
- Automated tagging of researcher profiles: An exploratory prototype is underway to automatically enhance academic researcher profiles with industry-specific keywords and standardized industry classifications, such as the North American Industry Classification System (NAICS).
Keywords:
AI, industry partnerships, taxonomies, ontologies, discoverability
Start Date
18-9-2025 3:10 PM
End Date
18-9-2025 3:40 PM
Target Audience
EFS/CRIS managers, research administrators, librarians, and technology specialists
Learning Objectives
Gain practical insights into how integrated AI-driven approaches can support, rather than disrupt, scholarly communication. Learn how AI solutions can strategically reduce communication barriers between researchers, industry partners, and external stakeholders. Understand how AI-driven research information systems enhance the discoverability, visibility, and accessibility of academic research. Explore early outcomes from institutions that have adopted AI responsibly within their research information workflows. Equip your institution to make informed, responsible decisions when adopting AI technologies in scholarly communications.
Recommended Citation
Anderson, Jackson and Cain, Timothy, "Lost in Translation? Using Generative AI to make academic expertise easier for partners to discover" (2025). International Forum on Expert Finder Systems. 18.
https://efsrimsrepository.expertfindersystems.org/efs_forum/2025/fullschedule/18
Lost in Translation? Using Generative AI to make academic expertise easier for partners to discover
Universities increasingly recognize the value of interdisciplinary collaboration as a powerful way to tackle complex challenges. However, establishing effective partnerships across institutions, industry, and government is often difficult due to siloed organizational structures and language barriers between sectors.
The Ohio Innovation Exchange (OIEx) provides a centralized web portal enabling users to discover expertise, research opportunities, intellectual property, and specialized equipment and services across Ohio's higher education landscape. Built upon Symplectic Elements, OIEx directly facilitates connections between academia and industry partners to foster collaboration and innovation.
Simply bringing potential collaborators together is often not enough: effective partnerships depend on clear communication and shared understanding. Industry practitioners often describe emerging technologies in terms unfamiliar to academics, who instead reference more traditional disciplinary frameworks. This linguistic disconnect creates challenges when industry users seek academic expertise.
To address these dual challenges of language barriers and researcher time constraints, OIEx is partnering with Digital Science to explore the potential of two complementary AI-powered approaches:
- Generative AI-driven search: Integrating generative AI models within researcher profile searches to translate and interpret user queries from industry partners, allowing for intuitive discovery of academic expertise despite differing vocabularies and linguistic approaches.
- Automated tagging of researcher profiles: An exploratory prototype is underway to automatically enhance academic researcher profiles with industry-specific keywords and standardized industry classifications, such as the North American Industry Classification System (NAICS).