MRI: Track 2 Development of a Platform for Accessible Data-Intensive Science and Engineering

Low-cost, high-performance sensors are producing an explosion of data in every field, from the mysteries of the cosmos to the tiniest particles. Despite this abundance of data, the absence of robust infrastructure and tools impedes the ability to effectively analyze and utilize it. The Development of a Platform for Accessible Data-Intensive Science and Engineering (DISE) will be a system for data management, sharing, and analysis that allows automatic data collection and curation, instant access for computational analysis, and research result sharing for reproducibility.

The system will pave the way for new research in data-driven science – and scientific outcomes. A key issue that DISE addresses is the complexity and cost of data movement from storage to analysis sites, especially in cloud-based scenarios. DISE aims for a more cohesive system integrating data storage and analysis.

By making research findings more accessible to the public, DISE will provide increased return on research investments to the research community and society at large. Critically, DISE will serve to train the next generation of scientists in data-intensive research, ensuring accessibility for diverse learners, and contributing to an equitable scientific community.

DISE aims to advance data-intensive science and engineering and make research more accessible and reproducible, fostering equitable outcomes across all societal sectors. DISE will introduce an innovative platform that facilitates automatic data curation from scientific instruments, detailed metadata querying, intelligent tiering for instant data accessibility for computational workloads, interactive access to Graphics Processing Unit (GPU)-accelerated resources, hosting and sharing of containerized research products and deployment of self-healing micro-services for real-time data analysis.

The platform will be equipped with a 2-petabyte scientific data management system, a 500-terabyte all-flash high-performance parallel file system, and GPU-accelerated computation. These features promise not only to streamline data management but also to facilitate input/output operations per second (IOPS) intensive workflows, including data mining, data-driven research, foundations in AI, data-intensive computation for good, and reliable and trustworthy AI.

DISE is dedicated to aiding the exploration of new areas of study by utilizing community data repositories while simultaneously fostering the growth of the upcoming generation of scientists skilled in data-intensive research. DISE will also improve access to research data and computation, thus increasing the return on prior research investments. The automated curation feature of DISE is set to revolutionize how research data is organized and shared, making it accessible and interoperable beyond the originating researchers.

Additionally, DISE is committed to providing high-performance GPU resources to foster data-intensive science. The platform will connect with researchers across various disciplines and intends to further expand its reach by automating data curation from shared user facilities. In addition, the use of GPU-accelerated computing resources via an easily accessible JupyterHub will aid in educating and training the next generation of researchers.

Finally, DISE is committed to promoting diversity in the field by providing equitable access to resources and partnering with institutions such as Morgan State University to train a new generation of diverse data-intensive scientists and engineers.

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.