Addressing Model Data Archiving Needs for the Department of Energy’s Environmental System Science Community

Abstract:

Researchers in the Department of Energy’s Environmental System Science (ESS) program use a variety of models to advance robust, scale-aware predictions of terrestrial and subsurface ecosystems. ESS projects typically conduct field observations and experiments coupled with modeling exercises using a model-experimental (ModEx) approach that enables iterative co-development of experiments and models, and ensures that experimental data needed to parameterize and test models are collected. Thus, preserving the “model data” comprising the outputs from simulations, as well as driving, parameterization and validation data with associated codes is becoming increasingly important. The Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) repository currently stores all types of data associated with ESS projects; however, it has not yet been optimized for ingesting and serving large data volumes associated with model outputs. Furthermore, we have lacked community consensus on which model data are scientifically useful to archive. Thus, to scale and optimize ESS-DIVE for model data, we surveyed and interviewed the ESS community to identify the needs for archiving, sharing, and utilizing model data, and to begin developing archiving guidelines to ensure that archived data are scientifically useful, findable, and accessible. Here, we present the results of the survey and the proposed guidelines. This initial assessment of the community needs is an important step in supporting ESS-DIVE’s long-term vision to broadly enable data-model integration, and knowledge generation from model and observational data. This vision will be achieved through close partnerships with the ESS community.