Ensuring Data Quality through a Lifecycle Approach: Examples and Lessons from the US Geological Survey
Abstract
The quality of data, sometimes referred to as "fitness for use", is critically dependent on numerous factors including the precision and accuracy of the collection, the robustness of the metadata, the data curation and preservation, and the accessibility. Adherence to these data life-cycle management standards, critical peer review of data, and appropriate citation of use and reuse, help ensure quality through the potentially long history of a given set of data. Presently, there are many diverse quality practices across domains and sub-domains, and as the conduct of earth systems science becomes more integrated, there are increasing opportunities for scientists to use data in modeling and other analyses that may not be appropriate or fit for the intended use. Science at the U.S. Geological Survey (USGS) is increasingly focused on complex modeling and analysis of systems utilizing a combination of field observation and sophisticated, often automated, monitoring systems and instrumentation. Understanding and expressing the uncertainty of data, integrating and quantifying observational data with instrument data, understanding the resolution and limitations of data, and using data from the growing sources outside of a scientist's domain or control are some of the current challenges USGS is trying to address. Some solutions being implemented include: working with and across scientific communities to adopt modeling, data quality, and uncertainty standards; implementing full life-cycle data management practices; establishing common protocols for collection and metadata; providing training and education on data quality and management; and implementing "fundamental science practices" that ensure the highest quality in the publication of science and data.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2011
- Bibcode:
- 2011AGUFM.U21C..01G
- Keywords:
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- 1904 INFORMATICS / Community standards;
- 1912 INFORMATICS / Data management;
- preservation;
- rescue;
- 1930 INFORMATICS / Data and information governance;
- 1990 INFORMATICS / Uncertainty