CCC announced the availability of AI-disambiguated data and enriched metadata, for researchers and institutions, within RightFind Navigate through a pilot for its customers.
Since the introduction of FAIR principles in 2016, there has never been a question that their implementation would help drive innovation and accelerate the R&D lifecycle.
While generative AI such as ChatGPT gets all the buzz, AI in other, typically more targeted forms, has been used for years to solve business and research challenges.
Mary Ellen Bates shares the inside story of an information scientist working among a team of data professionals – with his tips for collaborative success.
Data quality is an expression of a data’s usefulness and value. We often describe the things we build as knowledge systems, or a system that takes data as its input and, through a series of data process steps, extracts as much of the ‘actionable information’ in the data as is possible.
As publishers continue to leverage new systems and tools in their efforts to continually improve publishing workflows, additional challenges with inconsistent and inaccurate metadata have emerged.
In Thomas Kuhn’s work, paradigms are characterized by “universally recognized scientific achievements that for a time provide model problems and solutions to a community of practitioners.”