Data and Software Guidelines

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Data and Software Guidelines
U.S. Digital Response - Data and Software Guidelines
This document describes how we manage data and write software at U.S. Digital Response ("USDR"). If you have a good reason to request diverging from these policies, we need to hear from you at [email protected].
Guiding Principles
Open and Accessible by Default
USDR data, code, documentation, and projects are open and accessible by default. USDR efforts are meant to be replicated, reused, adapted, and otherwise available for collaboration. USDR data, code, documentation, and projects should be easily discoverable, and projects with a website should dedicate a public-facing point of contact with whom potential collaborators can get in touch with questions.
Consistent Design
Any website that will be operated by or represent a government entity should use the U.S. Web Design System. This design framework allows for rapid development using a standard pattern library, and ensures visual consistency between projects and with existing government design practices.
Data Guidelines
Given the nature of COVID-19 relief work and close collaboration with government partners, data is a critical component of many USDR projects. In all cases (even when the data itself has restricted access for good reasons), the use cases, access restrictions, and descriptions of any relevant datasets should be well-documented and shared openly. Note that some government partners may ask you to comply with specific data requirements — please share and review any such agreements with [email protected].
Open Data
Data used for USDR projects should be available in open and machine-readable formats wherever possible. The potential use cases, access mechanisms and descriptions of the data should be well-documented and made available with a Creative Commons Zero (CC0) license.
If the data is sensitive (e.g., PII, PHI, proprietary data, etc.) and access must be restricted, those reasons should be clearly explained in the documentation and the storage compliant with regulatory guidelines. Whenever applicable, the data should be accessible (via API or clear export pipelines) and made available to trusted government partners. All data collection, storage, retention, and access controls should be designed with privacy and security in mind.
USDR Team Data
For information on data retention and use, see our Privacy Policy and other resources shared on http://www.usdigitalresponse.org/.
Software Guidelines
Source Control
​The U.S. Digital Response GitHub organization houses any USDR repositories, and — as needed — forks of software developed elsewhere. If you have already started a project in another repository, please fork it into this organization and resume work here. For questions or access to our repository, email [email protected].
When assisting government partners through staff augmentation to perform software development, we recognize that source control is rare, and that we are unlikely to be in a position to influence licensing decisions. Whenever possible, we should encourage partners to develop in accessible GitHub accounts or make documentation publicly available.
Licensing
For a project that originated elsewhere but will be built with active collaboration from USDR (e.g. relies on connections to our government partners for user research and feedback, has volunteer support), the work must be published under an OSI-approved license, a Creative Commons Zero license, or committed to the public domain.
Projects originating with USDR must be licensed under the Apache 2.0 License. (If for some reason the Apache 2.0 license is not an approved partner license, use the MIT License.)
Projects originating with USDR that are not software (e.g. documentation-only repositories or GitBooks) should use the Creative Commons Attribution 4.0 License (CC BY 4.0) unless there is a specific reason to choose a different license.
Repository Standards
A README.md file should be present, identifying the purpose of the software and its creators, linking to documentation, providing screenshots (if relevant), a link to an example instance of the software (if relevant), a link to API documentation (if relevant), and a link to the license file. If the software is the work of an organization, also provide a link back to a page on that organization’s website to demonstrate the software’s provenance.
A LICENSE.md file should be present, specifying the licensing terms.
A CODE_OF_CONDUCT.md file should be present, defining the standards for the community, per GitHub’s specs. USDR-originated projects should use the Contributor Covenant.
A CONTRIBUTING.md file should be present, describing how to contribute to the project (if, indeed, contributions are welcome). That should make clear the license status of the software, which all contributors’ work will be released under when it is incorporated into the larger work.
Documentation
All dependencies must be listed and the licenses documented. (This can be done in the form of a machine-readable manifest, e.g. package.json, requirements.txt, composer.json, etc.) Major functionality in the software/source code must be documented. Individual methods should be documented inline using comments that permit the use of documentation-generation tools, such as JSDoc.
The README.md file should provide (or link to) step-by-step instructions for standing up the site locally (in Docker or a common equivalent), and likewise provide step-by-step instructions for deploying the site to a hosting environment. When relevant, infrastructure should be defined as code in e.g. Terraform or Kubernetes.
The README.md is required to include a "Data Inventory" section that lists 1) all data that will be collected or stored by the system, 2) how it's stored, and 3) whether the data is intended to be publicly accessible. This is extremely important to make sure we properly secure any data we collect.
Example Data Inventory
Our app collects information from a state's citizens and shares the contact information of doctors who have partnered with us.
name
data store
public
citizen emails
S3 bucket
false
citizen names
S3 bucket
false
citizen social security number
AWS RDS
false
doctor names
AWS RDS
true
doctor emails
AWS RDS
true
Commits
Commit messages should contain:
1.A single line summary of the change. Imagine some future engineer is skimming down a list of commits; will your summary tell them enough to decide whether they need to read it in detail?
2.A description that includes, at least, the goal (the "why" not "what") of the change. Depending on complexity you might also include a description of how it works, alternative approaches that were rejected, benchmarks etc.
3.A test plan: Whatever actions you took to verify the change was correct. These should be detailed enough so that another person could perform the same test. Without automated testing, this at least gives future engineers a chance to do a manual regression test on your changes.
Code Review and Automated Testing
Code review ensures we don’t have a single point of failure, have a shared understanding of how our systems work, and maintain a consistent level of quality across the codebase. All software commits should be reviewed by another engineer, e.g via a pull request. Given the time sensitivity of our work, responding to assigned reviews should be everyone’s top priority (i.e., review first, do your own work second).
Security review and threat modeling ensures that we consider all of the security risks that an application may face. Before going live with a project, please reach out in the #security Slack channel to partner with a security team member to review your project.
Automated testing ensures we can move fast with safety. However, effective testing is a substantial time commitment that needs to be weighed against our need to ship as fast as possible. Use good judgment here, and consider a) the consequences of something failing, b) how fragile it’s likely to be, and c) how much time investment is needed to correctly test the component.
Automated security testing ensures that we protect the applications we create and the data they will collect. All public repositories should have Snyk vulnerability and dependency scanning integrated. Snyk will automatically run on every PR and fail on high severity vulnerabilities that have a fix (dependency upgrade) available.
Contact Us
If you have any questions or concerns about these guidelines, contact us at [email protected].
Volunteer Security Protocol
Inclusion Guidelines
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Code Review and Automated Testing