Data, Analysis, and Visualization

Data management, data analysis, and scientific visualization at NREL improves researchers' ability to capture, mine, analyze, and visualize data to address scientific and technical goals.

Meet the experienced team responsible for bringing data to life in the visualization cave at NREL’s Energy Systems Integration Facility.
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The process of moving renewable energy technologies from basic research to real-world application is becoming an increasingly data-intensive enterprise. Methods at NREL based on experimentation, simulation, and observation are producing tens of terabytes of data and millions of related records because of the continuing evolution of digital technology. At NREL, our data management, data analysis, and scientific visualization capabilities help move the needle on high-impact projects dealing with complex, large-scale data.


NREL's data, analysis, and visualization capabilities include the following.

Scientific Visualization

State-of-the-art immersive, collaborative, and high-resolution visualization capabilities located at the Energy System Integration Facility's Insight Center. Advanced visualization techniques and hardware include remote HPC visualization, visual mining, and visual exploratory tools for energy systems integration and other science research at NREL. Qualitative and quantitative approaches to understand large-scale, complex scientific data.

Computational Statistics, Bio-Informatics, Data Science and Advanced Analysis

Statistical modeling and prediction applied to energy grid and renewable penetration research and development, and statistical validation of models and prediction scenarios. Data science and advanced analysis techniques for Big Data problems. Expertise and capabilities in bioinformatics modeling and workflows, as well as computational approaches to image analysis and computer vision.

Data Management and Big Data

Systems, software, and tools to support the capture and management of experimental, observational, and Big Data sources, including high-throughput and combinatorial experimental data (i.e., photovoltaics, bioenergy, materials), time-series data such as observational and meter data management, real time and streaming data such as during energy systems hardware-in-the-loop experiments, image data from microscopy and experimental X-ray diffraction and fluorescence, and HPC modeling and simulation data management with next-generation database clusters and storage systems.


Learn about the Insight Center.


Kristi Potter

Group Manager, Data, Analysis, and Visualization