[ESIP-all] 2 AGU Sessions addressing: Data Preservation and Provenance
Kempler, Steven J. (GSFC-5860) via ESIP-all
esip-all at lists.esipfed.org
Mon Jul 7 22:10:33 EDT 2014
In case you have not heard, AGU is still coming again this year... in December.
Please allow me to bring your attention to 2 more sessions that specifically address Data Preservation and Provenance. These sessions are associated with Earth and Space Science Informatics, but here also, conveners are very interested in insights and experiences from the physical science communities, as well as from the informatics community. See you in SF.
Life Cycle Planning for Science Data Preservation
Session ID#: 2756
A key necessity of a science data archive is ensuring long term preservation of its data holdings and documentation. Science data stewards and providers have made strides, ensuring that unique remote sensing measurements are preserved, and better understanding the need to plan for data preservation at various stages of the science Data Life Cycle, thereby maximizing long term data usefulness. Life cycle stages at which time information to be preserved must be captured include: Project development, measurement, information generation, calibration, and archive. Organizations that contribute data documentation needing to be preserved, include: Data instrument, science, and management teams, data architects, and data stewards. This session seeks data preservers and data providers to present their data preservation planning experiences and life cycle plans for ensuring data and documentation is preserved. Suggested topics include, but are not limited to: Ensuring data quality, maintainability, formats, media, standards, data documentation capture.
Steven J Kempler
Hampapuram K Ramapriyan, Mirko Albani, Kenneth S Casey
Provenance enablement in Earth and space science
Session ID#: 2448
Provenance is information about entities, procedures, people and organizations involved in the production of research findings and the supporting datasets and methods. For the field of geospatial science, provenance is also known as the lineage of data. Capturing and presenting provenance have been of great importance to ensure reproducibility for many aspects of Earth and space science practice. Within the Open Geospatial Consortium (OGC), geospatial provenance has been widely discussed, such as those represented in the ISO 19115 and ISO 19115-2 lineage models. A recent effort in this field is the PROV data model and its support ontology (PROV-O) recommended by the World Wide Web Consortium (W3C), which provides an initial basis for capturing, representing and linking provenance. Best practices for implementing standards for provenance management are now emerging. This session welcomes contributions that demonstrate how provenance contributes to meeting scientific or engineering goals in Earth and space science works.
Wenwen Li, Deborah L McGuinness, Curt Tilmes
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