Pose phase i: transitioning openvisus to a sustainable and robust open-source ecosystem

Grant Award Summary

Visus LLC received a $319,975 Project Grant from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships program (CFDA 47.084) effective September 1, 2025, through August 31, 2026. This Phase I award supports the development of a sustainable and robust open-source ecosystem for OpenVisus, an advanced software framework designed to manage, process, and visualize large scientific datasets. OpenVisus provides researchers and professionals in engineering, materials science, and biology with accessible, user-friendly tools for multi-resolution, out-of-core visualization of massive datasets that cannot fit in system memory. The software emphasizes efficient data streaming, remote access capabilities, and error-bound encoding/decoding, enabling interactive analysis with limited bandwidth constraints—directly addressing bottlenecks in scientific data management and visualization workflows.

The project deliverables focus on establishing a sustainable infrastructure for the OpenVisus open-source ecosystem, making sophisticated data analysis capabilities accessible to audiences without specialized computer science expertise. By reducing barriers to entry for complex data processing, the initiative aims to accelerate scientific discoveries, improve workflow efficiencies, and reduce time and cost requirements for handling massive datasets across academic and industry sectors. This work supports the NSF TIP program's broader mission to advance breakthrough technologies addressing national challenges, positioning the United States competitively in data-driven research and technology innovation while benefiting instructors, researchers, and industry professionals requiring robust solutions for big data analysis.

Abstract

This pathways to enable open-source ecosystems (pose) project improves how we manage and process gigantic scientific data collections using an open-source, easy-to-use software framework called openvisus. The project addresses the growing problem that researchers and professionals in areas such as engineering, materials science, and biology face, as they typically deal with very large datasets. The project makes sophisticated data tools accessible to a wider audience, including those without specialized computer science expertise. This availability will accelerate scientific discoveries, improve workflow efficiencies, and reduce the cost and time requirements for handling massive data sets. The new framework enhances science and technology comprehension by facilitating rapid, interactive analysis of complex data, fostering collaboration, and supporting education. This approach provides the united states with a competitive advantage in data-driven research and technology. This advantage benefits instructors, researchers, and industry professionals who require robust and agile solutions for big data challenges. This pathways to enable open-source ecosystems (pose) project establishes a sustainable and robust open-source ecosystem for openvisus, which manages and visualizes large, gridded datasets. Openvisus provides a user-friendly framework for multi-resolution, out-of-core visualization of massive datasets. IT is optimized for efficient streaming and remote access of data that cannot fit in memory, as well as error-bound encoding and decoding. Users can interact with subsets of data as IT loads, making IT suitable for use in environments with limited bandwidth or remote access. Emphasizing fast data reading and writing for analysis, openvisus addresses bottlenecks in non-destructive evaluation caused by large-scale data management and visualization. Modern scanning methods produce image collections from tens to hundreds of gigabytes, increasing the challenge. Openvisus's data ordering enables efficient access to arbitrary subsets of large multi-dimensional images. Progressively streaming data in a coarse-to-fine manner ensures responsiveness and interactivity regardless of data size or network bandwidth. The project is fostering a community of early adopters who benefit from the technology's data solutions, enabling effective simulation for design, evaluation, and discovery. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are planned for this award.