Making Data AI-Ready
Of Interest to the Information Community
Curious about making data AI-ready? Check out our latest blog post for insights on what it means and why it matters. #DataScience #AI https://t.co/dXU5roW9UY
— Dryad (@datadryad) June 11, 2024
Key Quote
Of on-going interest to the NISO community is the means by which researchers discover and use data:
AI-ready data refers to data that is organized, evaluated by Dryad data curators, and prepared in a way that makes it easy for researchers to utilize it for AI modeling. Dryad provides a large corpus of this kind of well-structured, well-documented data. This data can be combined with datasets from specialist repositories and a researcher’s own data to create comprehensive datasets that fuel AI-driven research. Accessing the wide range of datasets from a “generalist” platform like Dryad, and potentially combining it from data sourced elsewhere facilitates the integration of knowledge “from various fields and knowledge systems” that can lead to “more accurate models and foster curiosity-driven research.” Dryad is also an invaluable resource for researchers who lack access to expensive equipment, distant or off-limits field sites, or face other barriers to collecting the data they need themselves.
How do we make our data AI-ready? Adhering to FAIR principles means ensuring that datasets are well-organized, properly documented, and easily accessible for machine harvesting and analysis. Dryad empowers FAIR through data curation and data connections.
Read more from Dryad in the full blog post.