Metadatify 🧪

Metadatify, or the Metadata Aggregation for Reproducible Science (MARS) project, is an open-source web-based tool to create, manage, and search scientific metadata.

Features

• Rich metadata entry and management, including support for file imports (CSV, JSON files)
• Export partial or complete metadata into multiple different file types (CSV, JSON files)
• Text-based search and advanced query system for searching deeply through metadata
• Manage metadata across projects and share with external users using Workspaces
• Establish relationships between metadata entries, visualize these relationships
• Edit history and version restore for metadata entries
• User accounts handled via ORCiD sign-in

Documentation

The wiki is actively maintained that covers the concepts introduced by Metadatify and how to use the platform. Documentation for API usage and self-hosting is coming soon.

Development

Install dependencies

1. Install dependencies for the overall project by running yarn in the root directory of the repository. These dependencies are required to run husky and setup the pre-commit hooks that run prettier prior to any git commits.
2. Install dependencies for the client by running yarn in the /client directory of the repository.
3. Install dependencies for the server by running yarn in the /server directory of the repository.

Setup environment variables

Metadatify uses Docker to containerize the server components. Before starting the Docker containers, three environment variables must be configured in an .env file that should be placed in the /server directory.

The .env file must have the following variables:

• CONNECTION_STRING: The local MongoDB database connection string, update the username and password.
• GRAPHQL_PORT: The port value for the GraphQL endpoint
• NODE_ENV: Specify the Node environment

The following variables are only required if deploying with ORCiD authentication, see ORCiD Developer Tools:

• CLIENT_ID: Client application ID
• CLIENT_SECRET: Client application secret

An example .env file is shown below:

```Text

Database variables

CONNECTIONSTRING=mongodb://:@localhost:27017/ GRAPHQLPORT=8000

Node environment

NODE_ENV=development

ORCiD ID API variables

CLIENTID= CLIENTSECRET= ```

Starting Docker containers

To start a fresh instance of the MongoDB database, use docker compose:

Bash docker compose up --build

This command will build all required containers before starting the containers required by the server. The MongoDB database can be browsed using the mongo-express interface accessible at localhost:8081.

Running Metadatify client and server

To start the client, run yarn start in the /client directory. Start the server by running yarn build and then yarn start in the /server directory. Both the client and server should be running alongside the Docker containers before attempting to access the interface at localhost:8080.

Testing

Metadatify includes Cypress tests and component tests for the client, and the server includes unit tests using Jest.

Testing - Client

To run component tests, run yarn test:components in the /client directory.

Cypress is used for testing the client UI. Before running client tests, add an .env file in the /client directory with the following variables:

• CONNECTION_STRING: The local MongoDB database connection string, update the username and password.

An example .env file is shown below:

```Text

Database variables

CONNECTION_STRING=mongodb://:@localhost:27017/ ```

Once the .env file has been configured, run yarn test:ui in the /client directory to run all Cypress tests in headless mode.

To run component tests, run yarn test in the /client directory. To run Cypress tests, run yarn cypress run in the root / directory of the repository. Ensure the server is running, otherwise the Cypress tests will fail.

Testing - Server

[!WARNING] Testing the server will erase the local MongoDB database!

To run unit tests, run yarn test in the /server directory.

Acknowledgements

Organizations:

• Department of Neuroscience, Washington University School of Medicine in St. Louis
• Brain Development and Disorders Lab, Washington University School of Medicine in St. Louis
• Scientific Software Engineering Center, Georgia Institute of Technology

Contributors:

• Henry Burgess
• Robin Fievet

License:

See the LICENSE file for license details.