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DOE OSTI2024

Supporting Greater Interactivity in the IPython Visualization Ecosystem

Interactive visualizations are invaluable tools for building intuition and supporting rapid exploration of datasets and models. Numerous libraries in Python support interactivity, and workflows that combine Jupyter and IPyWidgets in particular make it straightforward to build data analysis tools on the fly. However, the field is missing the ability to arbitrarily overlay widgets and plots on top of others to support more flexible details-on-demand techniques. This work discusses some limitations of the base IPyWidgets library, explains the benefits of IPyVuetify and how it addresses these limitations, and finally presents a new open-source solution that builds on IPyVuetify to provide easily integrated widget overlays in Jupyter.

Martindale, Nathan↗

DOE OSTI2020

Opportunities for an Integrated Web-Based Workbench for Data Access and Analysis - 20244

Management of environmental issues can require integration of multiple types of data and information, conducting data analysis and interpretation, and providing data visualization for effective communications. These data elements are important for site management to support regulator interactions and provide defensibility for remedial decisions. Databases and information repositories are core elements of managing data; however, efficient data access and analysis also enable effective site management. The U.S. Department of Energy (DOE) Hanford Site is an example of a complex site with a voluminous quantity of environmental data and a need for efficient site management. Different tiers of data and information tools have been developed and deployed to address site needs. These tools are configured for ready access via the web site interfaces and meet the rigorous quality requirements for environmental site management. Evolving efforts are focused on an integrated platform to meet site environmental management needs. In this platform, users can access site information at multiple levels of detail based on their need and permissions, so that data and associated analyses are presented within the context of the site mission and the user's management or technical needs. This concept is not only applicable at individual sites like Hanford but also applicable at other sites within the DOE complex. An integrated web-based architecture that links data visualization, data analytics, and management tools can provide holistic access to large data sets, minimize complexity, and maximize interactivity and technical communication. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

The U.S. Agrivoltaic Shading Tool: A National-Scale Interface for Modeling Light and Shade Patterns in Ten Common Agrivoltaic Configurations

Agrivoltaic systems are dual-use configurations that co-locate agriculture and photovoltaic (PV) infrastructure and require careful design to balance crop performance and energy generation. A critical element of agrivoltaic design is the spatial and temporal distribution of irradiance and shade within and around PV arrays. To support research, planning, and stakeholder decision-making, we introduce the U.S. Agrivoltaic Shading Tool, a novel web-based application that delivers high-resolution irradiance and photosynthetically active radiation (PAR) modeling for ten standardized PV configurations across the conterminous United States. The tool leverages the National Laboratory of the Rockies (NLR) System Advisor Model (SAM) to perform detailed irradiance simulations, using meteorological data from the National Solar Radiation Database (NSRDB). Outputs include seasonal, monthly, weekly, and diurnal patterns of available sunlight, amount of shade, irradiance, and PAR at ground level within agrivoltaic system footprints. For a user's selected location, these results are visualized through interactive visualizations, heatmaps, and time-series plots, designed to be accessible to both technical and non-technical users. In addition to facilitating rapid spatial exploration of agrivoltaic light environments, the tool will offer seamless integration with the InSPIRE Agrivoltaics Design and Analysis Model (ADAM). This optional workflow will allow users to port selected site and configuration parameters into a more advanced modeling environment for further customization of structural layouts, crop-system compatibility, power generation, and technoeconomic performance. Finally, to promote open science, the entire dataset will be hosted and available for open access through the OpenEI platform. By standardizing and disseminating high-quality irradiance data and design tools, the U.S. Agrivoltaic Shading Tool supports a wide range of users, including researchers, landowners, energy developers, and policymakers, in evaluating the agronomic and energetic feasibility of agrivoltaic systems across the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Database Management Module Framework for Dynamic Contingency Analysis and Visualization

The Dynamic Contingency Analysis Tool (DCAT) is being developed to mimic the response of generation dynamics, protection, and load components to extreme contingencies in power systems. Currently, DCAT generates a huge data set, with the analysis results stored in multiple subfolders using a great many files in different formats (power flow cases, time series, figures, spreadsheets). To help power system engineers thoroughly understand and analyze system behavior under many scenarios and contingencies, we developed a database management module (DBM) that enables future integration of DCAT with industry-grade Big Data analytical and interactive visualization platforms. In this paper, we demonstrate the DBM framework with interactive analytics and visualization for DCAT on the synthetic South Carolina 500-bus power system model using hurricane contingencies that capture possibilities for an extreme contingency. DCAT’s advanced data management and interactive visualization can help planning engineers to visually explore and analyze system behavior, all in one view.

Cascading, dynamic simulations, database managemen↗

DOE OSTI2018

Creating an Interprocedural Analyst-Oriented Data Flow Representation for Binary Analysts (CIAO)

National security missions require understanding third-party software binaries, a key element of which is reasoning about how data flows through a program. However, vulnerability analysts protecting software lack adequate tools for understanding data flow in binaries. To reduce the human time burden for these analysts, we used human factors methods in a rolling discovery process to derive user-centric visual representation requirements. We encountered three main challenges: analysis projects span weeks, analysis goals significantly affect approaches and required knowledge, and analyst tools, techniques, conventions, and prioritization are based on personal preference. To address these challenges, we initially focused our human factors methods on an attack surface characterization task. We generalized our results using a two-stage modified sorting task, creating requirements for a data flow visualization. We implemented these requirements partially in manual static visualizations, which we informally evaluated, and partially in automatically generated interactive visualizations, which have yet to be integrated into workflows for evaluation. Our observations and results indicate that 1) this data flow visualization has the potential to enable novel code navigation, information presentation, and information sharing, and 2) it is an excellent time to pursue research applying human factors methods to binary analysis workflows.

42 ENGINEERING↗

DOE OSTI2018

Interactive visualization of multi-data-set Rietveld analyses using Cinema:Debye-Scherrer [nteractive Visualization of Multi-Dataset Rietveld Analyses using Cinema:Debye-Scherrer]

A tool named Cinema:Debye-Scherrer to visualize the results of a series of Rietveld analyses is presented. The multi-axis visualization of the high-dimensional data sets resulting from powder diffraction analyses allows identification of analysis problems, prediction of suitable starting values, identification of gaps in the experimental parameter space and acceleration of scientific insight from the experimental data. The tool is demonstrated with analysis results from 59 U–Nb alloy samples with different compositions, annealing times and annealing temperatures as well as with a high-temperature study of the crystal structure of CsPbBr 3 . A script to extract parameters from a series of Rietveld analyses employing the widely used GSAS Rietveld software is also described. Finally, both software tools are available for download.

36 MATERIALS SCIENCE↗

DOE OSTI2019

In silico identification of key genes and signaling pathways targeted by a panel of signature microRNAs in prostate cancer

Accumulating evidence have suggested that some microRNAs are aberrantly expressed in prostate cancer. In our previous work, we had identified a panel of four differentially expressed microRNAs in prostate cancer. In the present study, we have investigated common molecular targets of this panel of miRNAs (DEMs) and key hub genes that can serve as potential candidate biomarkers in the pathogenesis and progression of prostate cancer. A joint bioinformatics approach was employed to identify differentially expressed genes (DEGs) in prostate cancer. Gene enrichment analysis followed by the protein–protein interaction (PPI) network construction and selection of hub genes was further performed using String and Cytoscape, respectively. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the identified hub genes was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. In total, 496 genes were identified to be common targets of DEMs in prostate cancer and 13 key hub genes were identified from three modules of the PPI network of the DEGs. Further top five genes viz Rhoa, PI3KCA, CDC42, MAPK3, TP53 were used for Enrichment analysis which revealed their association with vital cellular and functional pathways in prostate cancer indicating their potential as candidate biomarkers in prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2025

EnergyPlus-MCP: A model-context-protocol server for ai-driven building energy modeling

Traditional building energy modeling with the EnergyPlus building performance simulation engine requires domain expertise, programming skills, and intensive manual efforts limiting its effective adoption. This paper introduces EnergyPlus-MCP, the first open-source Model Context Protocol (MCP) server specifically designed for EnergyPlus simulation workflows, establishing a new foundational infrastructure for AI-driven building energy modeling. The MCP server implements a layered architecture with 35 specialized tools spanning model management, editing and analysis, HVAC and other systems configuration inspection, and simulation execution, enabling Large Language Models to interact with EnergyPlus through conversational interfaces. The server addresses critical workflow barriers by automating model validation, streamlining energy efficiency measures modification, and providing intelligent output management with interactive visualization. Through practical demonstrations using a multi-zone building retrofit analysis, we show how the EnergyPlus-MCP server significantly reduces manual efforts while maintaining full simulation rigor. By providing accessible natural language interfaces to sophisticated building energy analysis, this approach enables scalable deployment of simulation expertise across public and private organizations, educational institutions, and research teams, fundamentally transforming traditional building energy modeling practices.

AI↗

DOE OSTI2025

Ascribe XR v0.1.0

Ascribe XR is an immersive visualization software designed for scientists and engineers working with 3D data sets. Its key features include interactive exploration, multi-user collaboration, and flexible data import capabilities, supporting various formats such as meshes, volumes, and terrain maps. The software utilizes Godot, OpenXR and PC-VR technology to provide an immersive experience. Ascribe XR is used for data analysis, visualization, and collaboration in various fields, enabling users to gain deeper insights into complex data sets. Its advantages over similar technologies include its flexibility, customizability, and ease of use. Ascribe XR's interactive and immersive environment facilitates collaboration and accelerates the discovery process. Compared to traditional 2D visualization tools, Ascribe XR offers a more engaging and intuitive experience, allowing users to explore complex data sets in a more natural and interactive way. Its ability to support multi-user collaboration and flexible data import capabilities make it a versatile tool for various applications. Overall, Ascribe XR provides a unique combination of features, usability, and performance, making it an attractive solution for scientists and engineers working with 3D data sets.

Pandolfi, Ronald [Lawrence Berkeley National Labor↗

DOE OSTI2025

GenomeDepot v1.0

GenomeDepot is a web-based platform for annotation, management, and comparative analysis of microbial genomic sequences and associated data including ortholog families, protein domains, operons, regulatory interactions, strain taxonomy, and sample metadata. GenomeDepot supports rapid creation of web-sites for user-defined genome collections that include bioinformatic tools for interactive genome browsing, BLAST search, annotation search, comparative genomic neighborhood visualization, and sequence download. Gene function annotations are generated by a customizable annotation pipeline. The pipeline runs annotation tools in Conda environments and can be easily extended with additional user-specified tools.

Kazakov, Alexey [Lawrence Berkeley National Labora↗

DOE OSTI2022

Multimodal X-ray nano-spectromicroscopy analysis of chemically heterogeneous systems

Abstract Understanding the nanoscale chemical speciation of heterogeneous systems in their native environment is critical for several disciplines such as life and environmental sciences, biogeochemistry, and materials science. Synchrotron-based X-ray spectromicroscopy tools are widely used to understand the chemistry and morphology of complex material systems owing to their high penetration depth and sensitivity. The multidimensional (4D+) structure of spectromicroscopy data poses visualization and data-reduction challenges. This paper reports the strategies for the visualization and analysis of spectromicroscopy data. We created a new graphical user interface and data analysis platform named XMIDAS (X-ray multimodal image data analysis software) to visualize spectromicroscopy data from both image and spectrum representations. The interactive data analysis toolkit combined conventional analysis methods with well-established machine learning classification algorithms (e.g. nonnegative matrix factorization) for data reduction. The data visualization and analysis methodologies were then defined and optimized using a model particle aggregate with known chemical composition. Nanoprobe-based X-ray fluorescence (nano-XRF) and X-ray absorption near edge structure (nano-XANES) spectromicroscopy techniques were used to probe elemental and chemical state information of the aggregate sample. We illustrated the complete chemical speciation methodology of the model particle by using XMIDAS. Next, we demonstrated the application of this approach in detecting and characterizing nanoparticles associated with alveolar macrophages. Our multimodal approach combining nano-XRF, nano-XANES, and differential phase-contrast imaging efficiently visualizes the chemistry of localized nanostructure with the morphology. We believe that the optimized data-reduction strategies and tool development will facilitate the analysis of complex biological and environmental samples using X-ray spectromicroscopy techniques.

36 MATERIALS SCIENCE↗

DOE OSTI2026

GenomeDepot: data management system for microbial comparative genomics

Summary GenomeDepot is an open-source web-based platform for annotation, management, and comparative analysis of microbial genomic sequences and associated data including ortholog families, protein domains, operons, regulatory interactions, strain taxonomy, and sample metadata. GenomeDepot supports rapid creation of websites for user-defined genome collections that include bioinformatic tools for interactive genome browsing, Basic Local Alignment Search Tool (BLAST) search, annotation search, comparative genomic neighborhood visualization, and sequence download. Gene function annotations are generated by a customizable annotation pipeline. The pipeline runs annotation tools in Conda environments and can be easily extended with additional user-specified tools. Availability and implementation GenomeDepot is open source and distributed under the GNU General Public License via GitHub (https://github.com/aekazakov/genome-depot). GenomeDepot is implemented in Python and was tested in Ubuntu Linux. Full installation instructions and documentation are available at https://aekazakov.github.io/genome-depot/. GenomeDepot demo server is freely accessible at https://iseq.lbl.gov/demogd/.

Kazakov, Alexey [Lawrence Berkeley National Labora↗

DOE OSTI2019

XScan: An Integrated Tool for Understanding Open Source Community-Based Scientific Code

Many scientific communities have adopted community-based models that integrate multiple components to simulate whole system dynamics. The community software projects’ complexity, stems from the integration of multiple individual software components that were developed under different application requirements and various machine architectures, has become a challenge for effective software system understanding and continuous software development. The paper presents an integrated software toolkit called X-ray Software Scanner (in abbreviation, XScan) for a better understanding of large-scale community-based scientific codes. Our software tool provides support to quickly summarize the overall information of scientific codes, including the number of lines of code, programming languages, external library dependencies, as well as architecture-dependent parallel software features. The XScan toolkit also realizes a static software analysis component to collect detailed structural information and provides an interactive visualization and analysis of the functions. We use a large-scale community-based Earth System Model to demonstrate the workflow, functions and visualization of the toolkit. We also discuss the application of advanced graph analytics techniques to assist software modular design and component refactoring.

Zheng, Weijian↗

DOE OSTI2023

Multidisciplinary concurrent optimization framework for multi-phase building design process

Modern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the design (conceptual, preliminary, and detailed) and construction processes. The Architecture Engineering and Construction (AEC) community has recently shifted gears toward leveraging design optimization techniques to make well-informed decisions in the design of buildings. However, most of the building design optimization efforts are either multidisciplinary optimization confined to just a specific design phase (conceptual/preliminary/detailed) or single disciplinary optimization (structural/thermal/daylighting/energy) spanning across multiple phases. Complexity in changing the optimization setup as the design progresses through subsequent phases, interoperability issues between modeling and physics-based analysis tools used at later stages, and the lack of an appropriate level of design detail to get meaningful results from these sophisticated analysis tools are few challenges that limit multi-phase multidisciplinary design optimization (MDO) in the AEC field. Here this paper proposes a computational building design platform leveraging concurrent engineering techniques such as interactive problem structuring, simulation-based optimization using meta models for energy and daylighting (machine learning based) and tradespace visualization. The proposed multi-phase concurrent MDO framework is demonstrated by using it to design and optimize a sample office building for energy and daylighting objectives across multiple phases. Furthermore, limitations of the proposed framework and future avenues of research are listed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

A Scoping Review of Mixed Initiative Visual Analytics in the Automation Renaissance

Artificial agents are increasingly integrated into data analysis workflows, carrying out tasks that were primarily done by humans. Our research explores how the introduction of automation recalibrates the dynamic between humans and automating technology. To explore this question, we conducted a scoping review encompassing twenty years of mixed-initiative visual analytic systems. To describe and contrast the relationship between humans and automation, we developed an integrated taxonomy to delineate the objectives of these mixed-initiative visual analytics tools, how much automation they support, and the assumed roles of humans. Here, we describe our qualitative approach of integrating existing theoretical frameworks with new codes we developed. Our analysis shows that the visualization research literature lacks consensus on the definition of mixed-initiative systems and explores a limited potential of the collaborative interaction landscape between people and automation. Our research provides a scaffold to advance the discussion of human-AI collaboration during visual data analysis. Our integrated taxonomy is available in the form of a web application on https://smonadjemi.github.io/miva.

Monadjemi, Shayan [ORNL] (ORCID:0000000293855969)↗

DOE OSTI2025

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Low-Income Energy Affordability Data (LEAD) Tool Methodology

Methodology document describing the underlying data and analysis behind the Low-income Energy Affordability Data (LEAD) Tool, a web-accessible, interactive platform developed by U.S. Department of Energy and National Renewable Energy Laboratory that allows users to build their own national, state, city, or county profiles with estimated, locally specific low-income household energy characteristics. Users are able to visualize the profiles as well as compare differences among profiles. In addition, users will be able to save their profiles and download visualizations and data. characteristics. Users are able to visualize the profiles as well as compare differences among profiles. In addition, users will be able to save their profiles and download visualizations and data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗