The DataJoint Customer Experience

Progress increasingly requires studying biological systems as a whole. That’s meant new instruments, multi-modality techniques, and a massive increase in complexity. Labs have stretched their teams and processes, but without good systems they’re inefficient and struggling to keep up.

Trusted by Premier Research Institutions

Leading labs choose DataJoint to manage their most complex and valuable data.

Competitive Advantage at the *Scientific Frontier*

Labs come to DataJoint when they want to do more than keep up. They want a decisive edge – to replace their ad hoc, manual work with automated, reproducible workflows, and to bring structure and transparency to their data and operations. This not only relieves their burdens, it prepares them to meet new regulatory mandates and provides the foundation for the reliable use of AI.

Reproducibility and transparency are the first two pillars of the new US policy on the conduct and management of scientific activities.

See Executive Order, restoring gold standard science § 3(a)(i)-(ii), May 23, 2025.

The *SciOps Maturity Model*

A Framework for Operational Excellence

The SciOps Maturity Model provides a practical roadmap to assess and enhance a lab’s data management and research practices. It charts the path from foundational data practices to highly efficient, automated, and AI-enabled collaborative science.

This Model is a collaborative effort, developed and maintained by DataJoint and the Applied Physics Laboratory at Johns Hopkins University together with a coalition of collaborators from the scientific community (the “SciOps Alliance”). Any research team can use its principles to evaluate their capabilities, set goals, and prioritize initiatives to boost their performance and research impact.

“SciOps is a methodology that unifies experimental design, data collection, processing, analysis, and dissemination into a seamless, repeatable pipeline that enhances efficiency, reproducibility, and scalability in scientific research.”

Erik Johnson
et al., SciOps: A New Operational Model for Reproducible Science (2024) (under review by Nature Methods)
Before
Level 1

Initial

Ad Hoc Processes
Ad Hoc Processes
DIY Custom Development
Results with
Level 2

Managed

Established Processes
Repeatable Processes
Role Specialization
Quality Control
Level 3

Defined

Sharable Processes
Open-Source Ecosystems
FAIR Data
FAIR Workflows
Level 4

Scalable

Automated Workflows
SciOps Pipeline
Collaborative Environments
Teamflow
Level 5

Optimizing

Closed-loop Discovery
AI + Human in the Loop
Before
Results with
Adopting DataJoint

Operational Excellence *in Practice*

Our team of SciOps scientists and engineers partners with you to level up your lab's operations.

Here’s the steps in a typical onboarding:

Collaborative Pipeline Design

Your DataJoint subscription typically includes in-depth consultation with our SciOps team. We begin by understanding your lab's specific scientific aims, processes, and challenges. We then collaborate to architect the optimal DataJoint pipeline, defining the data models and automated workflows specific to your research.

Systems Integration

We work closely with your team (and often your research computing and IT departments) to integrate DataJoint with your lab’s existing environment:

Instruments

We establish automated pathways to ingest data from your scientific instruments (e.g., microscopes, electrophysiology rigs, behavioral systems) into the DataJoint pipeline, ensuring data integrity and provenance from the source.

Scientific Software

We help integrate your lab’s custom analysis scripts and specialized software into the DataJoint pipeline with all appropriate inputs, outputs, and error handling.

Computing and Storage

You can choose our secure cloud computing and storage, or we can work with your systems admins to use on-premises resources in your lab or institution.

External Data Systems

We can integrate your pipeline to pull metadata from lab systems such as Electronic Lab Notebooks (ELNs), Laboratory Information Management Systems (LIMS), or Animal Care Systems, and can serve data to external systems as needed.

Orchestration Configuration

Once your pipeline is designed, we configure each computational step by assigning it to an environment with appropriate computing resources (CPU, GPU, memory) and software dependencies, including correct library versions.

Continuous Integration (CI) & Continuous Deployment (CD)

We help your lab establish collaborative software development practices – i.e., code development, review, and submission (using GitHub). We also establish the CI/CD pipeline to ensure that code updates are automatically tested, integrated, containerized, and deployed into your production environment.

Notebook Environments

We set up integrated Jupyter notebook environments tailored to your lab’s analysis needs including, for example, GPU-accelerated notebooks for computationally intensive analyses.

Graphical User Interfaces

We help design or customize data entry screens suited to your research needs (e.g., entering session information, creating new parameter sets). We work with your team to integrate existing visualizations, or to develop new ones. And we help create dashboards for your project, using the integrated Plotly Dash engine to render plots, data tables, and interactive elements  in any combination.

Testing

Before handoff, we thoroughly test the entire pipeline, from data ingestion through all processing stages, to ensure everything operates correctly and meets your lab's approval.

Training

A subscription includes comprehensive training for your entire team. We provide hands-on sessions, detailed documentation, and ongoing support to ensure everyone is proficient and comfortable using DataJoint to its full potential.

UCL

Project Aeon

Aeon’s 2-meter arena simulates natural environments to study multi-animal social interactions: Researchers gain a front-row seat to the brain in action, unraveling natural behaviors through scalable, multi-animal tracking in massive arenas over months.

“DataJoint enables fast and intuitive data querying and an easy way to standardize data for sharing around the world."

Tiago Branco
Group Leader
Tom Mrsic-Flogel
Prof & Director

Researchers gain a front-row seat to the brain in action, unraveling natural behaviors through scalable, multi-animal tracking in massive arenas over months.

University of Houston

Nurminen Lab

Using electrophysiology and behavior tracking, we investigate visual cortex interactions and their role in perception. Automating electrophysiology processing speeds insights into how disrupted neural circuits impact visual perception.

“The reason I am paying for DataJoint is so that I can come back in ten years and won’t need to remember how my sessions were represented in the analysis.”

Lauri Nurminen
Ass't Professor

Using ephys and behavior tracking, the lab investigates visual cortex interactions and their role in perception.

Johns Hopkins University

Hussain Shuler Lab

DataJoint is enabling the Hussain Shuler Lab to develop better models for Alzheimer’s disease and how degeneration of the cholinergic system can impair decision-making.

"With DataJoint, we save months of compute time. Without DataJoint, some of our experiments are not even doable.”

Marshall Hussain Shuler
Assoc. Professor

Time spent on a pursuit is divided by opportunity and apportionment costs, determining its true value.

Indiana University Bloomington

Lu Lab

The Lu Lab explores how prenatal cannabis exposure impacts brain development, later behavior, and future therapies.

"DataJoint's open science approach will allow future comparisons of data from labs across the world."

Hui-Chen Lu
Director & Chair

3D brain slice visualization from a study exploring the neural impact of prenatal cannabis exposure

UCSF

Cadwell Lab

Patch-seq helps scientists explore individual cells’ traits, like finding hidden instructions in a puzzle. By revealing its cellular diversity, this tech is a game-changer for fighting gliomas, one of the deadliest brain tumors.

“I am really happy with DataJoint support! We’ve tested our pipelines with real data … my lab can take it from here.”

Cathryn Cadwell
Ass't Professor

Patch-seq helps scientists explore individual cells’ traits, like finding hidden instructions in a puzzle.

Baylor

Reimer Lab

Simultaneous recordings of mouse on spherical treadmill with eye and whisker cameras, electrophysiology, calcium imaging, and visual stimuli.

"With DataJoint, we submitted for publication four months after discovery. Without DataJoint, it would have taken two years.”

Jake Reimer
Ass't Professor

Simultaneous recordings of mouse on spherical treadmill with eye and whisker cameras, electrophysiology, calcium imaging, and visual stimuli.

Power Up *Your Lab*

Ask us how we can help you level up your lab’s operations.

Don’t just manage your data – accelerate your science. With DataJoint, you can eliminate the friction and streamline your path to discovery.