This session seeks to begin an ongoing conversation between software engineers, data producers, data stewards, and data users to share pain points and exchange ideas about
1) designing and developing data tools and services that can work with most (or a lot of) disparate NASA data products;
2) designing and implementing data products that can easily interoperate with data tools and services, and with other data products;
3) preparing (e.g., creating metadata, assembling documentation, conducting testing, etc.) and publishing data products that can interoperate with data tools and services, and with other data products; and
4) using, accessing, transforming, and analyzing disparate data products.
We will bring tool developers, data users, and data stewards together to explore how we can work together to make more data more usable through improved standards compliance, more robust metadata, etc.
Metadata curation, data product design, standards development, and software engineering are typically done by completely separate teams; but software that makes Earth science data accessible requires standardized formats and data models, as well as robust, standards-compliant metadata and documentation. As ESDIS moves away from bespoke data tools toward an integrated environment of shared, enterprise-class tools and services, this session aims to bring together diverse groups to understand how to work more cooperatively to improve data FAIRness.
The session aims to be interactive and conversational. Please come prepared to share your use cases and the barriers you experience in executing them efficiently. We want to hear from you. Topics include:
- What standards exist or are needed that could address current barriers to interoperability?
- If standards already exist, what is keeping them from addressing current barriers to interoperability?
- Should standards be enforced rigorously? If so, what infrastructure changes might be needed to make enforcement and compliance more feasible?
- Are more and better tools needed? For data producers? For data stewards? For data users?
AudienceMetadata curators, software engineers, and data producers (scientists) who want to improve data FAIRness and data interoperability.
