Stardust: Digital Tooling for Earthly Science & Education
summary
Argues for a Launchpad of tools that assess full digital research objects (data, software, methods) rather than just PDFs, claiming that interoperable quantitative–qualitative tooling yields more precise, nuanced, reliable evaluation. Describes a Rwanda case where Kinyarwanda lacks LLM support, internet penetration sits near 30%, and a local project collects offline and voice/text datasets to build a language platform aligned with IDPC/CoARA standards. Proposes mapping and integrating ORCID/DOI/OSF ecosystems, exploring standardized badging for integrity and reproducibility.
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chapters (9)
- 0:00Introduction to Stardust
- 1:10Project and coalition background
- 3:15Digital challenges in research assessment
- 9:22Defining Stardust in data
- 11:08Rwanda case study on AI and language
- 15:30Plato’s Cave metaphor for data
- 16:55Current tooling and community needs
- 22:34Policy impact and digital tools
- 25:11Policy and technology gap
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