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NOAA OneStop Metadata Requirements and Tools
Session Time January 9th; 1:30 pm to 3:00 pm
Location Glen Echo
Description The OneStop Project’s mission is to improve discoverability and access to NOAA data. We can do this through high quality collection level and granule metadata descriptions and online access. This session will comprise two parts that provide insight into the OneStop activities from the metadata team’s perspective. The first part will provide an overview of our requirements, our progress, lessons learned and next steps. The second part will provide a deeper dive into the metadata team’s workflows and solutions to support Data Stewardship Maturity assessments, granule metadata generation and collection level metadata updates. There will be some time at the end of session to solicit feedback about how to make these processes and requirements more accessible to all NOAA data providers.
Chair Anna Milan
Presentations and Notes Click Here!

Talk Length (min) Title Presenter
3B.1 15 Overview of OneStop Project from a Metadata Point of View Anna Milan
3B.2 15 Decomposition of Collection Metadata and Dynamic Regeneration John Relph
3B.3 15 Light under ISOLite - OneStop granule level discovery metadata Yuanjie Li
3B.4 45 Open Discussion

3B.1 Overview of OneStop Project from a Metadata Point of View

Anna Milan (NESDIS/NCEI)

Yuanji Li, John Relph, Phil Jones, Nancy Ritchey, OneStop Metadata Team

The OneStop Metadata team was formed during the spring of 2016. Since then, we improved and created metadata for 5 data groups comprised of 322 collection level records and hundreds of thousands of granule level records. In this short amount of time, following the iterative spirit of an agile approach, we developed requirements and best practices while producing metadata while the design and development of the discovery system is also unfolding. This presentation will discuss our requirements, progress so far, lessons learned and next steps.

3B.2 Decomposition of Collection Metadata and Dynamic Regeneration

John Relph (NESDIS/NCEI/OneStop)

The descriptive information (metadata) for many data sets contain similar information; they might use the same keywords, they might have some of the same contributors, they might refer to the same scientific papers. In order to increase consistency between the representations of this information across data sets, it might be useful to decompose the information into references to external components or to identified terms in standard vocabularies, for example. Automated processes can be built to regenerate the descriptive information from its decomposed components. This can reduce the amount of effort that data managers need to expend in order to update the information in all metadata records, because the components can be updated and the changes will be reflected in all affected records. This can also increase consistency between those records because those common components are rendered identically, and because every component of a similar type is rendered in the same way. The metadata management system being developed by OneStop is being designed to support this data model.

3B.3 Light under ISOLite - OneStop granule level discovery metadata

Yuanjie Li (NESDIS/NCEI)

Phil Jones (NESDIS/NCEI), Anna Milan (NESDIS/NCEI)

This presentation will introduce talks about the new ISOLite metadata template, including the real examples of using ISOLite for granule metadata/discovery work, and the built up tailored validation tools, such as the new Metadata Rubric tool. The ISOLite metadata is the template was created by the NOAA OneStop Metadata Team following . This template was built from the ISO 19115-2 schema validation file. 41% of the required fields can be mapped to ACDD attributes in netCDF data and 48% are static template fields or can be sourced from the parent collection metadata. ISOLite uses the minimum content that is necessary for the granule data discovery uses, thus it is lightweight, but efficient. A comparison between the old ISO granule metadata and the ISOLite granule metadata shows a clear decrease in the metadata file size. The reduced of the file size also improved the performance of metadata indexing to the discovery portal.

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