Enterprise AI Analysis
Fostering Knowledge Infrastructures in Science Communication and Aerospace Engineering
This paper outlines a doctoral work aimed at fostering knowledge infrastructures in fragmented domains like science communication and aerospace engineering. It proposes tool-supported workflows using human-in-the-loop AI, wiki/knowledge-graph-based digital libraries, and stakeholder-driven interfaces. The work addresses challenges from complex data formats to lack of structured support, emphasizing collaborative curation and balancing automation with human validation.
Key Impact Metrics
Insights from the research highlight critical areas where AI-driven knowledge infrastructure can deliver significant enterprise value.
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SLR Requirements Formalized
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Documents Screened (Aerospace)
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Science Podcasts Curated
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Fragmented Knowledge: Knowledge in science communication and aerospace engineering is often siloed across formats and repositories, hindering FAIR principles. This leads to resource-intensive processes from simple searches to complex multidisciplinary design optimization.
Limited FAIR Adoption: Despite the existence of FAIR data management tools, their adoption is limited due to challenges like complex data formats, lack of structured support, incentives against collaboration, and legal barriers.
Human-in-the-Loop AI: Utilizes AI-supported workflows for information extraction and processing, balancing automation with human validation.
Wiki/Knowledge-Graph Digital Libraries: Employs structured, machine-actionable data models like knowledge graphs (e.g., Wikibase, ORKG) for robust knowledge representation.
Stakeholder-Driven Interfaces: Develops interfaces tailored to domain-specific needs, fostering collaborative curation practices in sustainable digital libraries.
Science Communication: Accessible audiovisual data needs structured representation with straightforward legal considerations and consolidation of contributors. The SciCom Wiki provides an openly accessible digital library.
Aerospace Engineering: Relies on formalized KBE processes, but faces fragmentation. Solutions must respect regulations while facilitating interoperability, as exemplified by CPACS/CMDOWS.
FAIR Data
Enhancing principles across fragmented domains is crucial.
Knowledge Infrastructure Development Flow
Data Acquisition (Videos, Publications)
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Human-in-the-Loop Information Extraction
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Data Transformation & Semantic Modelling
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FAIR Knowledge Representation (SciCom Wiki, ORKG, Wikidata)
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Collaborative Curation & Adoption
| Feature | Science Communication | Aerospace Engineering |
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| Data Accessibility |
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| Interoperability |
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| Collaboration |
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| Key Solutions |
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Case Study: SciCom Wiki Adoption
The SciCom Wiki, a Wikibase-based digital library for scientific videos and podcasts, significantly aids findability and curation. Early evaluations highlight its potential for improving discovery and metadata capture. While promising, broader adoption requires addressing legal, onboarding, and scalability challenges.
Estimated Efficiency Gains
Calculate potential time and cost savings by adopting AI-powered knowledge infrastructure solutions.
Annual Savings
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Hours Reclaimed Annually
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Your Implementation Roadmap
A phased approach to integrate advanced AI-driven knowledge infrastructure into your enterprise.
Phase 1: Needs Assessment & Pilot
Conduct detailed domain-specific requirements elicitation and initiate a pilot project with human-in-the-loop AI workflows.
Phase 2: Infrastructure Development
Implement wiki/knowledge-graph-based digital libraries (e.g., Wikibase instances) and integrate initial data sources.
Phase 3: Collaborative Curation & Tool Integration
Foster community adoption, develop stakeholder-driven interfaces, and integrate tools for systematic literature reviews and fact-checking.
Phase 4: Scaling & Governance
Scale solutions across the organization, establish governance models, and address legal/IP barriers for sustained knowledge sharing.
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