Mining the USGS Data Landscape

The scientific legacy of the USGS is the data and the scientific knowledge derived from it gathered over 130 years of research. However, it is widely assumed, and in some cases known, that high quality data, particularly legacy data critical for large time-scale analyses such as climate change and habitat change, is hidden away in case files, file cabinets, and hard drives housed in USGS science centers and field stations (both hereafter “science centers”). Many USGS science centers, such as the Fort Collins Science Center, have long, established research histories, are known repositories of data sets, and conduct periodic “file room cleanout” days that establish and enforce some minimal data lifecycle management and maintains a cursory inventory of maintainable data – data that is of high enough interest/impact that they should be maintained at a minimum readable format for future access and use. But science centers currently lack a clear understanding of data lifecycle management best practices and simple inventory tools to manage their data through its lifecycle. We proposed testing the CDI lifecycle framework by applying it to a handful of known data, and documenting the considerations and requirements of effectively applying the CDI data lifecycle framework. Further, we proposed creating a simple “USGS Data Mine” tool that enables science centers to conduct and maintain their data inventories, while contributing to and assisting with the growing greater USGS data landscape.

Principal Investigator : Anthony L Everette, Susan K Skagen