AIND Metadata Portal

metadata visualizations

Validation endpoints

The metadata portal hosts validation endpoints for the latest aind-data-schema release. You can hit these endpoints with:

Example

import requests
import json

with open("metadata.json", "r") as f:
    metadata = json.load(f)

response = requests.post(
    "https://metadata-portal.allenneuraldynamics-test.org/validate/metadata", 
    json=metadata
)

if response.status_code == 200:
    print("✅ Validation passed!")
else:
    print(f"❌ Validation failed: {response.json()}")

Files endpoint

You can also post a dictionary containing only the core files (i.e. not generated from a Metadata object). This can be useful when testing whether your metadata are valid prior to triggering the aind-data-transfer-service on a data asset.

import requests
import json

core_files = ["data_description", "acquisition", "instrument", "procedures", "subject"]

metadata = {}
for core_file in core_files:
    with open(f"{core_file}.json", "r") as f:
        metadata[core_file] = json.load(f)

response = requests.post(
    "https://metadata-portal.allenneuraldynamics-test.org/validate/metadata", 
    json=metadata
)

if response.status_code == 200:
    print("✅ Validation passed!")
else:
    print(f"❌ Validation failed: {response.json()}")

Individual validation endpoints

• /validate/subject - Subject metadata
• /validate/data_description - Data description metadata
• /validate/acquisition - Acquisition metadata
• /validate/instrument - Instrument metadata
• /validate/procedures - Procedures metadata
• /validate/processing - Processing metadata
• /validate/quality_control - Quality control metadata
• /validate/model - Model metadata

Example usage: requests.post("https://metadata-portal.allenneuraldynamics-test.org/validate/subject", json=subject_data)

Usage

Clone the repository and cd into the folder

Create a virtual environment and install the package, then launch panel.

python -m venv .venv
source .venv/bin/activate (or .venv/bin/Scripts/activate on Windows)
pip install -e .
panel serve ./src/aind_metadata_viz/app.py --show --autoreload

To launch the query and view apps replace the app.py with the appropriate launcher.

CI/CD

There is a Dockerfile which includes the entrypoint to launch the app.

Local dev

1. Build the Docker image locally and run a Docker container:

docker build -t aind-metadata-viz .
docker run -e ALLOW_WEBSOCKET_ORIGIN=localhost:8000 -p 8000:8000 aind-metadata-viz

2. Navigate to 'localhost:8000` to view the app.

AWS

1. On pushes to the dev or main branch, a GitHub Action will run to publish a Docker image to ghcr.io/allenneuraldynamics/aind-metadata-viz:dev or ghcr.io/allenneuraldynamics/aind-metadata-viz:latest.
2. The image can be used by a ECS Service in AWS to run a task container. Application Load Balancer can be used to serve the container from ECS. Please note that the task must be configured with the correct env variables (e.g. API_GATEWAY_HOST, ALLOW_WEBSOCKET_ORIGIN).