What is ESS-DIVE?
The U.S. Department of Energy’s (DOE) Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) is a new data repository for Earth and environmental science data funded by the Data Management program within the Climate and Environmental Science Division. It stores and enhances access to critical information generated from research funded by or related to the DOE’s Office of Science Biological and Environmental Research program (BER) under its Subsurface Biogeochemical Research (SBR) and Terrestrial Ecosystem Science (TES) Programs in the Environmental Systems Science (ESS) activity.
The mission of ESS-DIVE is to preserve, expand access to, and improve usability of critical data generated through DOE-sponsored research of terrestrial and subsurface ecosystems in support of the DOE’s efforts to address some of society’s most pressing energy and environmental challenges.
ESS-DIVE is a member of the DataONE Federation, and the Federation of Earth System Information Partners (ESIP).
Scientists with expertise in Earth and Environmental Sciences and Computing Sciences from Berkeley Lab are developing ESS-DIVE in collaboration with the ESS community. The repository’s infrastructure is being developed in collaboration with the National Energy Research Scientific Computing Center (NERSC), the National Center for Ecological Analysis and Synthesis (NCEAS) .
Why we need ESS-DIVE?
ESS scientists examine hydro-biogeochemical and ecosystem processes taking place from molecular to global scales over environments spanning bedrock through soil and vegetation to the atmospheric interface. Their study of important processes like nutrient and water cycling, or carbon and energy fluxes is relevant to knowing how various ecosystems will behave over decades, or even centuries. For example, ESS researchers develop models to predict how arctic and forest landscapes drive and respond to global and environmental change, or how watersheds evolve over time.
ESS scientists typically work in large interdisciplinary teams to conduct field observations and experiments that are coupled with modeling exercises. This model-experimental (MODEX) approach enables iterative co-development of experiments and models, and ensures that experimental data needed to parameterize and test models are collected. Ultimately, this approach drives the collection of diverse datasets from various sciences that include hydrology, geology, ecology, geochemistry, biology, climate and geophysics.
As a result, the data, models and software generated by ESS researchers are critical to understanding and predicting how our terrestrial and subsurface environments function and evolve. ESS data can extensively be used to evaluate process, global and regional Earth System Models through tools like ILAMB. ESS data and model results provide information needed for effective planning related to energy, environment and infrastructure–and serve as a resource for scientists, policy makers, and other stakeholders including water utilities, farmers, and environmental remediation managers.
Over the past several years, data volumes in earth and environmental disciplines have risen sharply to unprecedented levels (terrabytes to petabytes). Moreover, the complexity and diversity of this research data—including simulations, observations and reanalysis—have expanded significantly, posing new challenges for data capture, storage, verification, analysis, integration, and sharing.
Yet much of this important information remains unarchived, difficult to access or unusable since many scientists lack the resources, access and ability to archive and share their data using consistent methods. At the same time, across the sciences, the requirement for reporting data is not what it once was. It’s become more common for journals to demand access to open data and for researchers to establish standards for how research data is stored and used. Likewise, systems are being put in place to determine where that data will be stored to ensure long-term access to it by those who need it.
ESS-DIVE is the DOE’s answer to the question of where to store data generated during ESS research activities. ESS-DIVE provides DOE scientists a centralized location to archive their environmental research data for long-term preservation, and the ability to publicly release data in standardized formats to enhance scientific collaboration and data reuse.
What does ESS-DIVE do?
ESS-DIVE enables the scientific community to archive and manage critical environmental data around consistent standards and protocols. It seeks to expand access to and use of data generated by DOE-funded research.
|ESS-DIVE allows data contributors to archive, manage and share various types of data in consistent formats, and obtain digital object identifiers that can be used to cite and track usage of the data.||ESS-DIVE users are able to find and obtain data generated by ESS researchers that is organized for better interpretation, analysis, and integration.|
ESS-DIVE is designed as a scalable framework that incentivizes data providers to contribute well-structured, high-quality data to the archive and that enables the user community to easily build data processing, synthesis, and analysis capabilities using those data.
Why use ESS-DIVE?
Our vision is that ESS-DIVE becomes the preferred location for archiving ESS data due to:
- the ease of storing, versioning, organizing data by citation and tracking data usage
- the ability to search and retrieve data via web and programmatic portals
- the built-in support for data standards, formats and protocols preferred by the ESS community
- the services that enable community-built tools to process, integrate and analyze the data
- increased awareness of ESS research data, which will be searchable across international data catalogs