Data Quality

The NCO develops and delivers raw and value-added phenology data and data products to advance science, to inform decisions, and to communicate the value of phenology. These products include observational and gridded phenology data and derived products, which are processed to maximize the data quality and value.

Observational data products

Observational plant and animal data in the National Phenology Database are collected by naturalists, professional researchers, high school students and park visitors, and more. We ensure that data are robust for use in scientific analyses and decision-making, via a range of quality assurance (QA) processes, which target species identification, phenophase status evaluation, and data entry. We also apply quality control (QC) measures, to evaluate and flag data according to standards of plausibility, validity, and reliability. QA and QC processes and activities are described in Appendix 2 of the USA-NPN Observational Data Documentation.

This dashboard summarizes real-time data quality metrics for our observational data, including the proportion of observation records are flagged as a conflict and the temporal precision with which estimates of phenophase onset and end are captured.

Gridded data products

The USA-NPN NCO offers historical and forecasted gridded data products including the Spring Indices and Accumulated Growing Degree Day maps. As with all gridded data products, the USA-NPN gridded products contain uncertainty or error arising from multiple sources, including error propagated forward from underlying climate data and from models used in the calculations. We aim to identify and report measures of uncertainty to support the use of these data products in research and decision-making. The sources of uncertainty and the actions employed by the NCO to quantify this uncertainty are described in detail in the USA National Phenology Network Gridded Products Documentation.

For dashboards exploring data quality for these products, see product landing pages: Spring Indices, Accumulated Growing Degree Days.