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Knowledge sharing and discovery across heterogeneous research infrastructures
Siamak Farshidi1, Xiaofeng Liao2, Na Li2
1Department of Information and Computer Science, Utrecht University, Utrecht, The Netherlands.
Open Research Europe
|August 30, 2023
Summary
A new knowledge management system was developed for environmental research infrastructures to address fragmented data. This system uses AI to integrate and deliver knowledge, aiding environmental scientists in understanding the Earth System.
Area of Science:
- Environmental Science
- Information Science
- Knowledge Management
Background:
- Research infrastructures are vital for scientific data but are often domain-specific and disconnected.
- Fragmented knowledge from heterogeneous sources poses challenges for researchers.
- The rapid growth of knowledge exceeds human capacity for efficient capture.
Purpose of the Study:
- To present the development of a knowledge management system for Environmental Research Infrastructures (ENVRI).
- To address challenges in managing and integrating knowledge from diverse environmental science sources.
- To facilitate knowledge discovery, acquisition, integration, and delivery for environmental scientists.
Main Methods:
- Development of a knowledge management system tailored for ENVRI.
- Application of artificial intelligence (AI) approaches for automated knowledge acquisition.
- Integration of knowledge from heterogeneous and autonomous data sources.
Main Results:
- Successful development of a functional knowledge management system for environmental research.
- Demonstrated ability to discover, acquire, and integrate knowledge from fragmented sources.
- Facilitated consistent knowledge delivery to researchers and end-users.
Conclusions:
- Knowledge management systems are essential for overcoming fragmentation in research infrastructures.
- AI-driven approaches can effectively automate knowledge acquisition and integration.
- The developed system provides a valuable tool for environmental scientists studying the Earth System.
Keywords:
Knowledge baseknowledge managementresearch infrastructuresearch enginesoftware development lifecycleMore Related Videos
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