Starfish Nabs Top Award for Accelerating Science at Arizona State

WALTHAM, Mass. – April 16, 2026 – Starfish Storage, a provider of scalable file and data management solutions, has been named the winner of the “Data Solution of the Year for Research” in the 7th annual Data Breakthrough Awards. The recognition, announced today by the independent market intelligence organization, highlights the company's impactful deployment at Arizona State University (ASU), where its platform transformed how researchers access and utilize decades of complex scientific data.

This award marks the second consecutive win for Starfish Storage in the prestigious program, following its 2025 selection as "Data Solution of the Year for Education." The back-to-back accolades across different verticals underscore the growing momentum of the company and the critical role its technology plays in solving entrenched data management problems in large-scale, data-intensive environments.

Unlocking Decades of Buried Data

The award-winning implementation took place at ASU's Center for Evolution and Medicine, home to the Tsimane Health and Life History Project. Researchers on this long-term study, which examines healthy aging, had amassed a vast CT imaging archive spanning more than 20 years. While invaluable, this data presented a monumental challenge: it was collected using multiple generations of scanners, resulting in wildly inconsistent metadata and file structures.

For scientists and their global collaborators, this inconsistency created a significant bottleneck. Finding a specific subset of images—for instance, scans of a particular body part with certain characteristics—required an arduous process of manual curation. Researchers often had to rely on IT staff to sift through the data, a task that could take days or even weeks to complete. This delay not only slowed the pace of discovery but also hampered collaboration and the timely publication of findings. The problem at ASU is a microcosm of a larger issue plaguing modern research, where irreplaceable legacy data often remains locked away, its potential unrealized due to outdated formats and manual processes.

A Metadata-Driven Breakthrough

Working closely with ASU's IT team, Starfish implemented a solution that automated this entire process. The first step involved developing a script to normalize the inconsistent metadata. The Starfish platform then went to work, automatically extracting and standardizing metadata from the trove of DICOM (Digital Imaging and Communications in Medicine) files. This created a consistent, searchable catalog across the entire two-decade archive.

The true innovation, however, lies in how this newly organized data is presented to the end-users. Instead of forcing researchers to learn complex database queries or rely on IT intervention, the Starfish solution dynamically generates familiar, user-friendly directory structures. These folders are organized based on criteria that are meaningful to the researchers themselves: body part, scan quality, patient demographics, and even consent status. The same underlying file can appear simultaneously in multiple organizational views, allowing different researchers to find what they need through simple folder navigation.

Furthermore, these directories are not static; they are automatically updated as new data is ingested, ensuring the catalog is always current. This self-service model has eliminated hours of manual labor and reduced data access time from weeks to minutes. Crucially, all access is governed by the project's stringent consent and privacy requirements, with an auditable trail ensuring that collaborators only see datasets for which they have explicit authorization.

"Research institutions have research studies that span decades and accumulate a lot of irreplaceable data, but inconsistent file formats, data standards, and metadata annotations, combined with manual curation processes means researchers and collaborators can't find what they need without waiting days or weeks for IT to help locate it," said Ari Berman, Chief Science Officer of Starfish Storage. "This innovation changes how collaborations work at scale and helps make science go faster."

A Pattern of Recognition and Growth

The significance of this achievement is amplified by the credibility of the Data Breakthrough Awards. The program, part of the broader Tech Breakthrough organization, attracts thousands of nominations from around the world and employs a rigorous judging process conducted by a panel of independent industry experts. Winning is considered a significant third-party validation of a company's technology and market impact.

For Starfish Storage, this year's win is not an isolated event. It builds on their 2025 award for "Data Solution of the Year for Education," signaling a clear pattern of success in applying its platform to the unique challenges of academic and research institutions. The company, which recently celebrated its 10th anniversary, now manages well over an exabyte of capacity for a client base that includes eight of the world's top ten pharmaceutical firms and seven of the eight Ivy League universities. This deep penetration into high-value, data-intensive sectors demonstrates a proven track record beyond a single award-winning project.

"Starfish’s solution offers a metadata-driven approach that removes research barriers while still honoring community commitments, and enabling responsible data sharing at scale,” commented Steve Johansson, Managing Director at Data Breakthrough. “Congratulations on winning ‘Data Solution of the Year for Research.’”

The Future of Scientific Data Management

The challenges Starfish addressed at ASU are emblematic of broader trends in scientific computing. Unstructured data—such as images, genomic sequences, and sensor logs—is projected to account for 80% of all global data by 2025. This data explosion has rendered traditional, manual management methods obsolete. The industry is rapidly shifting toward automated, metadata-driven, and vendor-agnostic platforms that can provide a unified view of data, regardless of where it is stored.

Starfish positions its platform, which combines an Unstructured Data Catalog (UDC) with a powerful Automation Engine, as a central nervous system for this new reality. Its vendor-agnostic approach allows it to manage data across a complex mix of high-performance computing file systems, scale-out NAS, and cloud object storage—a common scenario in large research universities. This capability not only accelerates research but also enables new models for cost optimization. Other universities have used the platform to implement sophisticated chargeback systems, saving millions of dollars in storage costs by providing clear visibility into data usage and identifying redundant or obsolete files.

As scientific discovery becomes increasingly data-driven, the ability to find, access, and securely share vast datasets is no longer a competitive advantage but a fundamental requirement. By transforming disorganized archives into discoverable, actionable assets, solutions like Starfish's are not just optimizing IT infrastructure; they are laying the groundwork for the next generation of scientific breakthroughs.