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

TL;DR

This paper addresses the fragmentation of Science Communication Knowledge Infrastructure (SciCom KI) for non-textual media (videos and podcasts) by proposing SciCom Wiki, a central, open, Wikibase-based digital library designed to make audiovisual content Findable, Accessible, Interoperable, and Reusable (FAIR). The authors conducted a stakeholder survey (n=53) and 11 interviews to elicit requirements, then implemented a federated system with a Full Text Wiki for transcripts and a Linked Data Wiki for metadata, plus a Dashboard for ingestion and discovery, and evaluated it with 14 participants. Results show strong usability (UEQ mean ≈ 1.78), demonstrated efficiency and effectiveness in tasks, and confirmation that the platform can address several prioritized needs, while recognizing substantial work remains to scale and fully satisfy all features. The work highlights the necessity of a shared, collaborative infrastructure to combat misinformation, enabling a central knowledge node akin to Wikidata but tailored for audiovisual science communication, and calls for broader community and institutional engagement to realize a robust SciCom KI.

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.

Figures (8)

• Figure 1: Total and clustered reported interest in our sample (n=53). The clusters indicate many participants are solely consumers, a second larger group can be classified as scientists and developers, a third as content creators and curators. Notably, almost every participant is interested as a viewer, often strongly.
• Figure 2: Results of 53 participants assessing the importance of Sci KI media criteria (above) and features (below), ranked by their importance averaged over all responses.
• Figure 3: Data import facilitated by the Dashboard import page and the backend integration service. Content can be added and edited through the MediaWiki Frontend as well, but especially bulk ingestion is facilitated through the Dashboard. The MediaWiki API provides authorization and an edit history as well.
• Figure 4: Process overview of the search page and its Federated Wiki Service. Query results are fetched from each wiki, filtered, and entries that are only matched in one wiki are complemented with the information from the respective other wiki. These results and suggested filters are then displayed.
• Figure 5: Overview of our proposed system (green) to connect knowledge from existing systems. The Dashboard serves as a non-technical, user-friendly entry point to the data curated in the Linked Data and Full Text Wikis.