OPEN SCIENCE at the
ALLEN INSTITUTE FOR NEURAL DYNAMICS

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• Mission & data• Open science and data sharing

alleninstitute.org|2Allen Institute for Neural Dynamics - Mission
Discover how the brain’s neurons produce our emotions, memories andactions.
Answers will be in terms of neural activity in defined neuron types interacting
across the whole brain and body.
This requires next-generation neurotechnologies.
Knowledge, data, and tools will be widely shared, to facilitate science elsewhere
and to support the development of therapies for brain disorders.

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Transcriptomic clusters

Cell types

Spatial transcriptomics à map of cell types

BICCN; AIBS

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4Transcriptomic clusters

Cell types

Spatial transcriptomics à map of cell types

BICCN; AIBS

Structure and connectivity à neural circuits

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5Cell types

Spatial transcriptomics à map of cell types

Neural signals à coding of information

Structure and connectivity à neural circuits

Transcriptomic clusters

BICCN; AIBS

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AIND organization: Groups
Behavior

Neural dynamics
Ephys

Neural dynamics
Ophys

Mapping brain-wideneural circuits

Machine-learningand theory

Cogito, ergosumInstrumentation

Scientific computing

David Feng

Project mgt & administration

Saskia de Vries

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UNESCO Recommendation on Open Science 2021

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Researchquestion

accessDesign &build

Collect data

Analyze data

Publishresults

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Researchquestion

accessDesign &build

Collect data

Analyze data

Publishresults

Open access/ Preprint

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Researchquestion

accessDesign &build

Materials &protocols

Collect data

Analyze data

Publishresults

Open access/ Preprint

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Researchquestion

accessDesign &build

Collect data

Analyze data

Publishresults

Materials &protocols

Open Data

Analysis
CodeOpen access

Sharing:
Tools, data, code, research findings

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Data re-use in neuroscience: MRI
Reuses of OpenNeuro datasets

OpenNeuro datasets*Markiewiscz et al., 2021
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Data re-use: cellular neurophysiology
CRCNS.org

Allen Brain Observatory / DANDI

Data reused in dozens of studies focused on theinterpretation of calcium imaging data

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Moving data is inefficient

University A

University B
alleninstitute.org|

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cloud is more efficient and powerfulalleninstitute.org|

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closedtransparent

Researchquestion

accessDesign &buildCollect data

Analyze data

Publishresults

Materials &protocols

Open Data

Analysis
CodeOpen access

Sharing:
Tools, data, code, research findings

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closedtransparent

Researchquestion

accessDesign &buildCollect data

Analyze data

Publishresults

Materials &protocols

Open Data

Analysis
pipeline

Open accessAnalysis
CodeOpen accessalleninstitute.org|19

Public cloud data lake architecture
Goals:

Approach:• Reproducibility•

Minimize on-prem footprint• Flexibility• Collaboration• Bring scientists to cloud data pipelines• Dissemination• Inclusion•

Accelerate, simplify data ingestion

Challenges• All data shareable the day of acquisition• Data rate, size (> 500 TB/w, 2 GB/s)• Metadata complexity• Use scientist-friendly cloud tools• Rate of change (science, tools, standards)• Cutting edge hardware, software• If possible buy/use, don't build

alleninstitute.org|20Ad-hoc Analysis
Acquisition

Data Lakecloud bucket +Scalable, reproducible
no-code docker, git
elastic, on-demand hardware

Ephys
Imaging

Data Transfer

Analysis Pipelines

BehaviorOphys...moreManage the labs
electronic lab notebooks
workflow management
separate schemas per lab+compress + upload

Automated, reproducible
results go back into lakelaunched on demand

Self-describing file sets
one per acquisition or analysis
JSON metadata validation
searchable via metadata

Analysis Views

Data Summaries
easy to build (avoid SQL)
updated automaticallyOn-premises

Cloudalleninstitute.org|

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Progress

Pain Points• Compression à save $• Poor support for cloud-friendly formats
o e.g. OME-Zarr, NWB-Zarr• Upload throughput
o Multi-node SLURM jobs
o 1-2GBps• Metadata schemao Inspiration from NWB, DANDI, HCA,BIDS• High-value desktop applications not supported
o e.g. imagej, napari, phy• Metadata standardization still very limited• Cloud archives prefer polished data

• Need more!
o Database agnostic, versioned• Expectation of free download/computealleninstitute.org|22Is Open Science Free?
Libre ("free speech") != Gratis ("free beer")
Academia expects both:
1. Download any data locally
2. Run any analysis (maybe on HPC)

Large, hidden, subsidized costs(network, storage, compute, admin)

Cloud pay-as-you-go makes costs very clear
Science must be Libre, but it is never Gratis.

The cloud is a better model, but who pays?

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Questions?

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