Pre-ESIP Workshop
About
Curating standards-based quality metadata and consistent quality descriptive information at the dataset level is fundamental for helping establish the credibility and trustworthiness of individual datasets and for providing sufficient guidance for users to address their specific needs, including machine learning. However, there are currently no community standards or guidelines on how to consistently curate and represent the dataset quality information that is machine- and human-readable.
ESIP Information Quality Cluster (IQC) and the Evaluation and Quality Control (EQC) Team of Barcelona Supercomputing Center (BSC) have co-organized a pre-ESIP workshop to bring together national and international subject matter experts on dataset quality to kick off the development of community guidelines for consistently curating and representing dataset quality information that is findable, accessible, interoperable, and reusable, aka, FAIR.