# Boss: A cloud-based data archive for electron microscopy and x-ray microtomography

> **NIH NIH R24** · JOHNS HOPKINS UNIVERSITY · 2024 · $761,835

## Abstract

ABSTRACT
The generation of scientifically rich, high resolution neuroimaging volumes continues to increase in extent and
rate due to the advancement of new Electron Microscopy (EM) and X-ray Microtomography (XRM) imaging sys-
tems and data processing methodologies. With the increased availability of these technologies throughout the
neuroscience community, and with sustained investment in new capability development and research program-
ming from the BRAIN initiative, there is a current and continued need for community data storage to support
future data generation, as well as to enable secondary science to help justify the extensive data collection and
processing costs for these data and to propagate new scientific workflows and discoveries.
Our BossDB data ecosystem currently serves as the BRAIN Initiative archive for high-resolution EM and XRM
data, storing nearly one petabyte of public image, segmentation, and connectomics data for multiple BRAIN
programs and for the broader neuroscience community. While the BossDB ecosystem continues to successfully
support multiple research endeavors, as we enter into a new phase of BRAIN programming and a new generation
of connectomics research with 10-100x larger petascale image volume collections, additional capabilities are
required to ensure efficient and performant data storage, processing, annotation, and access for anticipated
programmatic and community needs. Thus, in this proposed renewal of R24-MH114785 we will develop several
performance and scalability improvements to BossDB: improve the efficiency and cost-effectiveness of data
storage, support the integration of community tools and standards for data processing and annotation of large
scale neuroimagery, and provide an optimized query service to make it easier to conduct secondary analyses
of hosted datasets. Continued support of this critical community resource will make it possible for the world to
leverage petabytes of free, publicly available, and FAIR (Findable, Accessible, Interoperable, and Reusable) data
in BossDB that the neuroscience community already depends on for connectomics research.
The BossDB system will continue to be developed through an agile process to enable inputs from community
stakeholders, including from multiple ongoing BRAIN programs focused on data and experimental standards,
and multi-modal data ecosystem integration. As with the current BossDB system, we will continue to integrate
community tools for data storage, access, and visualization, with a focus on new tool integration for data process-
ing, annotation, and querying. Given the likelihood for more distributed data storage needs as data collections
increase significantly in scale, we will also develop more robust data export and local-cloud hybrid syncing
technologies. BossDB is a professionally-engineered community resource that has enabled many experiments
in connectomics and neuroscience research, and the developments proposed herein will further enable more
...

## Key facts

- **NIH application ID:** 10911373
- **Project number:** 5R24MH114785-07
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** BROCK A. WESTER
- **Activity code:** R24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $761,835
- **Award type:** 5
- **Project period:** 2018-08-24 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10911373

## Citation

> US National Institutes of Health, RePORTER application 10911373, Boss: A cloud-based data archive for electron microscopy and x-ray microtomography (5R24MH114785-07). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10911373. Licensed CC0.

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