Open mHealth Storage Endpoint

This repository contains the Java reference implementation of an Open mHealth Data Point API storage endpoint.

This code is in its early stages and requires further work and testing. Please do not use it in production without proper testing.

tl;dr

• this repository contains a secure endpoint that offers an API for storing and retrieving data points
• data points conform to the Open mHealth data point schema
• the code consists of an OAuth 2.0 authorization server and resource server
• the authorization server manages access tokens
• the resource server implements the data point API documented here
• the servers are written in Java using the Spring Framework, Spring Security OAuth 2.0 and Spring Boot
• the authorization server needs PostgreSQL to store client credentials and access tokens, and MongoDB to store user accounts
• the resource server needs PostgreSQL to read access tokens and MongoDB to store data points
• you can get everything up and running in a few commands using Docker Compose
• you can pull Docker containers for both servers from our Docker Hub page
• you can use a Postman collection to easily issue API requests

Overview

A data point is a JSON document that represents a piece of data and conforms to the data-point schema. The header of a data point conforms to the header schema, and the body can conform to any schema you like. The header is designed to contain operational metadata, such as identifiers and provenance, whereas the body contains the data being acquired or computed.

The data point API is a simple RESTful API that supports the creation, retrieval, and deletion of data points. The API authorizes access using OAuth 2.0.

This implementation uses two components that reflect the OAuth 2.0 specification. A resource server manages data point resources and implements the data point API. The resource server authorizes requests using OAuth 2.0 access tokens. An authorization server manages the granting of access tokens.

Installation

There are two ways to get up and running.

1. You can use Docker.

• This is the fastest way to get up and running and isolates the install from your system.

1. You can build all the code from source and run it natively.

Option 1. Using Docker containers

If you don't have Docker, Docker Compose, and Docker Machine installed, download Docker Toolbox and follow the installation instructions for your platform. If you don't have a running Docker machine, follow these instructions to deploy one locally, or these instructions to deploy to the cloud on any of these cloud platforms.

Once you have a running Docker host, in a terminal

1. Clone this Git repository.
2. Run docker-machine ls to find the name and IP address of your active Docker host.
3. Run eval "$(docker-machine env host)" to prepare environment variables, replacing host with the name of your Docker host.

Now, if you want to use pre-built Docker containers,

1. Run docker-compose -f docker-compose-init-postgres.yml up -d to download and run the containers.

• If you want to keep the containers in the foreground and see logs, omit the -d.
• If you want to just want to see logs, run docker-compose -f docker-compose-init-postgres.yml logs.

Otherwise, if you prefer to build and run your own containers, e.g. to customize them,

1. Run ./gradlew build -x test to compile the code while skipping tests.

• If you want to run the tests, you'll need to bring up a MongoDB instance with hostname omh-mongo.

1. Run docker-compose -f docker-compose-build.yml up -d to build and run the containers.

• If you want to keep the containers in the foreground and see logs, omit the -d.
• If you want to just want to see logs, run docker-compose -f docker-compose-build.yml logs.

The authorization and resource servers will start running on ports 8082 and 8083, respectively. It can take up to a minute for the containers to start up.

Option 2. Building from source and running natively

1. Get a Mongo instance and a Postgres instance up and running.
2. Source the two SQL scripts in resources/rdbms/postgresql in Postgres.
3. Source the SQL script resources/rdbms/common/oauth2-sample-data.sql in Postgres to create an OAuth 2.0 test client.
4. Update the spring.data.mongodb and spring.datasource properties in authorization-server/src/main/resources/application.yml and ./resource-server/src/main/resources/application.yml to match the settings of your Mongo and Postgres instances.
5. In one terminal, run ./gradlew authorization-server:bootRun to start the authorization server.
6. In another terminal, run ./gradlew resource-server:bootRun to start the resource server.
7. To stop the servers, press Ctrl-C in the terminals.

Configuring the servers

The authorization server configuration file and resource server configuration file are written in YAML using Spring Boot conventions.

If you want to override the default configuration, you can either

• Add environment variables to the Docker Compose file.
  • e.g. setting logging.level.org.springframework: DEBUG will change the logging level
  • e.g. setting spring.data.mongodb.host: foo will change the MongoDB host
• Create an application.yml file in the /opt/omh-dsu-ri/*-server directory with the overriding YAML properties.

It is possible to use multiple resource servers with the same authorization server.

Adding clients

The authorization server manages the granting of access tokens to clients according to the OAuth 2.0 specification. Since it is good practice to not roll your own security infrastructure, we leverage Spring Security OAuth 2.0 in this implementation. You can find the Spring Security OAuth 2.0 developer guide here.

It is beyond the scope of this document to explain the workings of OAuth 2.0, Spring Security and Spring Security OAuth. The configuration information in this document is meant to help you get started, but is in no way a replacement for reading the documentation of the respective standards and projects.

The authorization server uses Spring Security OAuth 2.0's JdbcClientDetailsService to store OAuth 2.0 client credentials. This necessitates access to a PostgreSQL database, although we intend to release a MongoDB service down the road to require either MongoDB or PostgreSQL, but not both.

The client details in the oauth_client_details table controls the identity and authentication of clients, the grant types they can use to show they have been granted authorization, and the resources they can access and actions they can take once they have an access token. Specifically, the client details table contains

• the identity of the client (column client_id)
• the resource identifiers (column resource_ids) the client can access , dataPoints in our case
• the client secret, if any (column client_secret)
• the scope (column scope) to which the client is limited, in our case some comma-separated combination of
  • read_data_points if the client is allowed to read data points
  • write_data_points if the client is allowed to write data points
  • delete_data_points if the client is allowed to delete data points
• the authorization grant types (column authorized_grant_types) the client is limited to, some comma-separated combination of
  • authorization_code, documented in the Authorization Code section of the OAuth 2.0 spec
  • implicit, documented in the Implicit section
  • password, documented in the Resource Owner Password Credentials section of the OAuth 2.0 spec
  • refresh_token, documented in the Refresh Token section
  • N.B. the client_credentials grant type in the Client Credentials section is not yet supported, but slated to be
• the Spring Security authorities (column authorities) the token bearer has, in our case ROLE_CLIENT

To create a client,

1. Connect to the omh PostgreSQL database.
2. Add a row to the oauth_client_details table, as shown in this sample script.

Adding end-users

The data points accessible over the data point API belong to a user. In OAuth 2.0, this user is called the resource owner or end-user. A client requests authorization from the authorization server to access the data points of one or more users.

The authorization server includes a simple RESTful endpoint to create users. To create a user, either execute the following command

curl -H "Content-Type:application/json" --data '{"username": "testUser", "password": "testUserPassword"}' http://host:8082/users

or use the create an end-user/success or conflict request in the Postman collection discussed below.

The user creation endpoint is primitive by design; it is only meant as a way to bootstrap a couple users when first starting out. In general, the creation of users is typically the concern of a user management component, not the authorization server. And it's quite common for integrators to already have a user management system complete with its own user account database before introducing the authorization server.

To integrate a user management system with the authorization server, you would

1. Disable the org.openmhealth.dsu.controller.EndUserController, usually by commenting out the @Controller annotation.
2. Provide your own implementation of either the org.openmhealth.dsu.service.EndUserService or the org.openmhealth.dsu.repository.EndUserRepository, populating org.openmhealth.dsu.domain.EndUser instances with data read from your own data stores or APIs.

Issuing requests with Postman

Your code interacts with the authorization and resource servers by sending them HTTP requests. To make learning about those requests easier, we've created a Postman collection that contains a predefined set of requests for different actions and outcomes. Postman is a Chrome packaged application whose UI lets you craft and send HTTP requests.

These instructions are written for Postman 1.0.1. If you're using a newer version and they don't work, let us know and we'll fix them.

To set up the collection,

1. Download Postman.
2. Start it.
3. Click the Import button, choose the Download from link tab and paste https://www.getpostman.com/collections/18e6065476d59772c748
4. The collection should now be available. The folder names describe the requests, and the request names describe the expected outcome.
5. Create an environment. Environments provide values for the {{...}} placeholders in the collection. Add the following environment keys and values, possibly changing the values if you've customised the installation.
   • authorizationServer.host - IP address of your Docker host (on Mac OS X and Windows, docker-machine ip <host> will print this IP to the console)
   • authorizationServer.port - 8082
   • resourceServer.host - IP address of your Docker host
   • resourceServer.port - 8083
   • accessToken - issue the get access token using RO password grant/success request and copy the access_token value from the response here, without quotes
   • apiVersion - 1.0.M1

To send a request, pick the request and click its Send button. The different requests should be self-explanatory, and correspond to the verbs and resources in the data point API.

The folders also have descriptions, which you can currently only see by clicking the corresponding Edit folder button (but Postman are working on that). You can see the request descriptions by selecting the request.

Using the authorization server

We may add documentation here if we find that the Postman collection isn't sufficient.

Using the resource server

The data point API is documented in a RAML file to avoid ambiguity.

A data point looks something like this

{
    "header": {
        "id": "123e4567-e89b-12d3-a456-426655440000",
        "creation_date_time": "2013-02-05T07:25:00Z",
        "schema_id": {
            "namespace": "omh",
            "name": "physical-activity",
            "version": "1.0"
        },
        "acquisition_provenance": {
            "source_name": "RunKeeper",
            "modality": "sensed"
        },
        "user_id": "joe"
    },
    "body": {
        "activity_name": "walking",
        "distance": {
            "value": 1.5,
            "unit": "mi"
        },
        "reported_activity_intensity": "moderate",
        "effective_time_frame": {
            "time_interval": {
                "date": "2013-02-05",
                "part_of_day": "morning"
            }
        }
    }
}

We may add documentation here if we find that the Postman collection isn't sufficient.

Roadmap

The following features are scheduled for future milestones

• support the client credentials grant type
• improve test coverage
• support refresh tokens
• make it easier to customise the authorization code and implicit grant forms
• support SSL out of the box
• filter data points based on effective time frames
• filter data points based on their bodies

If you have other feature requests, create an issue for each and we'll figure out how to prioritise them.

Contributing

If you'd like to contribute any code

1. Open an issue to let us know what you're going to work on.
2. This lets us give you feedback early and lets us put you in touch with people who can help.
3. Fork this repository.
4. Create your feature branch feature/do-x-y-z from the develop branch.
5. Commit and push your changes to your fork.
6. Create a pull request.