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The Hierarchical Data Format (HDF): A Foundation for Sustainable Data and Software

Authors :
Habermann, Ted
Collette, Andrew
Vincena, Steve
Billings, Jay Jay
Gerring, Matt
Hinsen, Konrad
Benger, Werner
Maia, Filipe RNC
Byna, Suren
Buyl, Pierre De
Publication Year :
2014
Publisher :
figshare, 2014.

Abstract

When combined with community specific conventions and application-specific semantics, the Hierarchical Data Format (HDF) provides a robust and reliable foundation that many scientific communities rely on for interoperability and high-performance storage of metadata and data. This foundation addresses many technical obstacles related to sustainable data and software, critical steps towards sustainable science. Building on successes across the communities that are using, or could use, HDF5 successfully, requires significant community engagement and development efforts that are outside of the scope of traditional software development projects in research and non-profit organizations like The HDF Group. Identifying individuals and organizations that are already doing the right things and bringing them together to share best practices for funding and executing these activities is an important step towards our shared goal of sustainable science.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....25617a8bda30976a95c97eca51e2b00d
Full Text :
https://doi.org/10.6084/m9.figshare.1112485