SciCom Wiki: A Digital Library to Support the Science Communication Knowledge Infrastructure for Videos and Podcasts

2025-11-12

AI Summary

Video and podcast content—dominant media for citizen science communication—also serve as fertile ground for misinformation. Existing science communication knowledge infrastructures (SciCom KIs) lack robust, scalable, and standardized frameworks for FAIR (Findable, Accessible, Interoperable, Reusable) management of audiovisual materials, resulting in fragmentation, insufficient scale, and conceptual gaps. Method: We propose the first FAIR-oriented collaborative knowledge base framework specifically designed for audiovisual science communication content. We implement it as SciCom Wiki—an open-source, Wikibase-based digital library—supporting FAIR-compliant multimedia curation. Requirements were elicited via 53 surveys and 11 semi-structured interviews; the prototype was validated with 14 users. Contribution/Results: SciCom Wiki enables collaborative metadata modeling and centralized knowledge node management, directly addressing the systemic absence of multimedia-capable SciCom KIs. It establishes a Wikidata-like knowledge hub for science communication infrastructure, advancing interoperability, reuse, and community-driven curation of audiovisual scientific content.

Technology Category

• Data Mining & Knowledge Management: Mining of Visual, Multimedia & Multimodal Data
• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Computer Vision: Multi-modal Vision

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Web Mining and Content Analysis: Interdisciplinary science discovery with web data mining
• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems

Abstract

Videos and Podcasts have established themselves as the medium of choice for civic dissemination, but also as carriers of misinformation. The emerging Science Communication Knowledge Infrastructure (SciCom KI), which curates these increasingly non-textual media, remains fragmented and inadequately equipped to scale against the content flood. Our work sets out to support the SciCom KI with a central, collaborative platform, the SciCom Wiki, to facilitate FAIR (findable, accessible, interoperable, reusable) media representation, particularly for videos and podcasts. We survey requirements from 53 stakeholders and individually refine these insights in 11 interviews. We then design and implement an open-source service system centered on Wikibase and evaluate our prototype with another 14 participants. Overall, our findings identified several needs to support the SciCom KI systematically. Our SciCom Wiki approach was found suitable to address the raised requirements. Further, we identified that the SciCom KI is severely underdeveloped regarding FAIR knowledge and related systems facilitating its collaborative creation and curation. Our system can provide a central knowledge node similar to Wikidata, yet a collaborative effort is required to scale the necessary features against the imminent (mis-)information flood.

Problem

• Addressing fragmented infrastructure for science communication in videos and podcasts
• Supporting FAIR media representation against misinformation in digital content
• Developing collaborative platform to scale against information flood challenges

Innovation

• Developed collaborative platform for science communication infrastructure
• Implemented Wikibase system for FAIR media representation
• Conducted stakeholder analysis to refine system requirements