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Want to know how to make your data machine readable and how your data people can spend more time on analysis and less time on data wrangling?
Join us in San Diego, May 28-31 for FAIR Data Stewardship training.
The promise of machine learning and AI are exciting, but are predicated on access to data that are findable, accessible, interoperable, and reusable (FAIR). Several studies show that 80% of a data professional’s time is spent on finding and cleaning data, rather than analysis. There are established models for creating and transforming data so that it is FAIR, to ensure data scientists and analysts spend more time seeking insights than on data cleaning. The potential new value to be captured and costs to be saved are enormous, especially when one adds in the untapped value from ‘dark data’, or data that isn’t used.
This past week, the San Diego Supercomputer Center (SDSC) announced the opening of the first US GO FAIR Coordination Office in the US. With the new U.S. office, the nation joins the Netherlands, France, Germany, and Brazil in establishing country-level coordinating offices. GO (Global Open) FAIR is a ‘bottom up’ initiative aimed at implementing the FAIR principles to ensure that data is findable, accessible, interoperable, and reusable. GO FAIR’s main goal is to kick-start the development of a global data commons for research and innovation.
As part of our new office, we are bringing trainers from Europe (EU) to UCSD for a FAIR Data Stewardship training course, not yet offered in the US.