Difference between revisions of "Data Quality"
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| − | == | + | == Discussion of Observational Data Quality == |
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| + | NEON data products span several scientific fields, addressing NEON's scientific design (see http://www.neoninc.org/science-design for more). These data products will undergo an iterative quality assurance program, which is currently in development. In addition, NEON seeks to freely offer data to the public as constructed sites begin collecting data. To accommodate these needs, NEON has instituted a "quality spectrum" for its data products. | ||
Initially NEON is releasing "preliminary" data products that have undergone limited quality control procedures, such as range checking and spike identification. As additional, in-depth inspection and analysis of the products are performed, subsequent releases of "provisional", and, later, "science grade", data products will follow, which will reflect the heightened analysis undertaken. While NEON expects that its data products will be useful at any quality level, NEON's "science grade" data products will be of the highest quality and suitable for a broad spectrum of research purposes. | Initially NEON is releasing "preliminary" data products that have undergone limited quality control procedures, such as range checking and spike identification. As additional, in-depth inspection and analysis of the products are performed, subsequent releases of "provisional", and, later, "science grade", data products will follow, which will reflect the heightened analysis undertaken. While NEON expects that its data products will be useful at any quality level, NEON's "science grade" data products will be of the highest quality and suitable for a broad spectrum of research purposes. | ||
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It should be noted that data quality incorporates both scientific quality measures (e.g. uncertainty, QA/QC procedures, sensor validations) and engineering measures (e.g., system verification, sensor calibrations). Data products are designed specifically to include this information along with the results of the scientific measurements and observations. | It should be noted that data quality incorporates both scientific quality measures (e.g. uncertainty, QA/QC procedures, sensor validations) and engineering measures (e.g., system verification, sensor calibrations). Data products are designed specifically to include this information along with the results of the scientific measurements and observations. | ||
| + | == NEON Data Web Site == | ||
*[http://data.neoninc.org/web/neondata/-/about-neon-data-products NEON Web Site] | *[http://data.neoninc.org/web/neondata/-/about-neon-data-products NEON Web Site] | ||
== Related Entries == | == Related Entries == | ||
| − | *[[Data | + | *[[Data Citation Levels]] |
*[[Data Management]] | *[[Data Management]] | ||
*[[Main Page]] | *[[Main Page]] | ||
Latest revision as of 18:11, 5 August 2015
Discussion of Observational Data Quality
NEON data products span several scientific fields, addressing NEON's scientific design (see http://www.neoninc.org/science-design for more). These data products will undergo an iterative quality assurance program, which is currently in development. In addition, NEON seeks to freely offer data to the public as constructed sites begin collecting data. To accommodate these needs, NEON has instituted a "quality spectrum" for its data products.
Initially NEON is releasing "preliminary" data products that have undergone limited quality control procedures, such as range checking and spike identification. As additional, in-depth inspection and analysis of the products are performed, subsequent releases of "provisional", and, later, "science grade", data products will follow, which will reflect the heightened analysis undertaken. While NEON expects that its data products will be useful at any quality level, NEON's "science grade" data products will be of the highest quality and suitable for a broad spectrum of research purposes.
It should be noted that data quality incorporates both scientific quality measures (e.g. uncertainty, QA/QC procedures, sensor validations) and engineering measures (e.g., system verification, sensor calibrations). Data products are designed specifically to include this information along with the results of the scientific measurements and observations.
