DLCLMMMay 12, 2025

SciCom Wiki: Fact-Checking and FAIR Knowledge Distribution for Scientific Videos and Podcasts

arXiv:2505.07912v1h-index: 16Has Code
Originality Incremental advance
AI Analysis

This addresses the need for reliable information in democratic societies by supporting the underdeveloped Science Communication Knowledge Infrastructure, though it is incremental as it builds on existing tools like Wikibase.

The paper tackles the problem of misinformation in scientific videos and podcasts by developing SciCom Wiki, a collaborative platform for FAIR media representation and fact-checking, using a neurosymbolic approach to convert media into knowledge graphs, with evaluations involving 53 stakeholders, 11 interviews, and 43 survey participants showing its suitability and usability.

Democratic societies need accessible, reliable information. 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) curating non-textual media is still fragmented and not adequately 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 and the fact-checking of their content, particularly for videos and podcasts. Building an open-source service system centered around Wikibase, we survey requirements from 53 stakeholders, refine these in 11 interviews, and evaluate our prototype based on these requirements with another 14 participants. To address the most requested feature, fact-checking, we developed a neurosymbolic computational fact-checking approach, converting heterogenous media into knowledge graphs. This increases machine-readability and allows comparing statements against equally represented ground-truth. Our computational fact-checking tool was iteratively evaluated through 10 expert interviews, a public user survey with 43 participants verified the necessity and usability of our tool. Overall, our findings identified several needs to systematically support the SciCom KI. The SciCom Wiki, as a FAIR digital library complementing our neurosymbolic computational fact-checking framework, 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, yet a collaborative effort is required to scale against the imminent (mis-)information flood.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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