BossDB – Brain Observatory Storage Service and Database

Type: Optics / Microscopy,

Type: Software,

Keywords: Database, Archive, Neuroscience, Electron Microscopy (EM), X-Ray Microtomography (XRM), Cloud, Volumetric, Connectomics, Scalable

Resource ID: SCR_017273

BossDB is a scalable cloud-based data ecosystem for storing large-scale volumetric neuroscience data from Electron Microscopy and X-ray Microtomography

BossDB (Brain Observatory Storage Service and Database, is a cloud-based data ecosystem for large-scale volumetric 3D and 4D neuroimaging data. BossDB focuses primarily on storing volumetric Electron Microscopy (EM) and X-Ray Microtomography (XRM) datasets generated as a part of the BRAIN Initiative. BossDB stores high resolution, multi-channel image data with registered segmentations, annotations, and meshes, and connects to a number of community resources for data access and data visualization. BossDB also stores connectomics datasets and contains a number of software tools and interfaces for querying and searching connectomes.

* Volumetric neuroscience data ecosystem (multi-channel neuroimaging data, metadata, annotations, connectomes)
* Resilient, multi-tier cloud data storage & data caching for public and private data
Scalable, highly available RESTful interfaces and load balancing through multiple endpoints
* Serverless system
* User authentication / authorization (SSO)
* API with numerous core services, supported clients, integrated software and visualization tools

* Connectomics Research
* Neuroanatomical Research
* Neurally-inspired Artificial Intelligence Research

* Large scale high-resolution neuroimaging data analysis and visualization
Connectomics searching and analysis tools

* Mouse
* Fly (Drosophila Melanogaster)
* Nematode (Caenorhabditis elegans)
* Zebrafinch
* Zebrafish

* Scalability
* High-speed data access
* High-speed data ingest

* An internet connection and web browser are the main requirements to get started, reach out to us at with any questions!

Hider, 2022, “The Brain Observatory Storage Service and Database (BossDB): A Cloud-Native Approach for Petascale Neuroscience Discovery,” Frontiers in Neuroinformatics,

Matelsky, 2022, “Scalable graph analysis tools for the connectomics community,” bioRxiv,

Sanchez, 2022, “Annotation Metadata Standardization for Increased Accessibility and Queryability, Frontiers in Neuroinformatics,”

Matelsky, 2021, “An Integrated Toolkit for Extensible and Reproducible Neuroscience,” IEEE EMBC 2021,

Bishop, 2021, “CONFIRMS: A Toolkit for Scalable, Black Box Connectome Assessment and Investigation,” IEEE EMBC 2021,

Matelsky, 2021, “DotMotif: An open-source tool for connectome subgraph isomorphism search and graph queries,” Nature Scientific Reports,

Johnson, 2020, “Toward a scalable framework for reproducible processing of volumetric, nanoscale neuroimaging datasets,” Gigascience,

Drenkow, 2020, “Leveraging Tools from Autonomous Navigation for Rapid, Robust Neuron Connectivity,” MICCAI 2020,″


Brock Wester, PI


Johns Hopkins University Applied Physics Laboratory (JHU/APL), Laurel, MD



William Gray-Roncal, Key Personnel, JHU/APL
Sandy Hider, Key Personnel, Software Lead, JHU/APL
Daniel Xenes, Software Developer, JHU/APL
Jordan Matelsky, Software Developer, JHU/APL
Tim Gion, Software Developer, JHU/APL
Erik C Johnson, Software Developer, Standards Lead, JHU/APL



* R24MH114785