- public users
- federal staffer (USA)
- federal staffer (foreign)
- foreign staffer
- compliance officer
- policy staffer
- political stakeholder
- standards body staffer (NIST)
- product developer (implementer of auth/login solution)
- vendor developer (developer of auth/login solution)
A key distinction I find a little hard to communicate is the difference between "just a list of things" to a "structured dataset".
Informal lists can be easy, but they tend to lack 1) structure and 2) governance - and because of this, these lists tend to get duplicated for many audiences, and thus 1) lose provenance 2) lack authority and 3) increase information glut or "noise".
https://en.wikipedia.org/wiki/Model%E2%80%93view%E2%80%93controller acknowledges how managed "Model" data can be projected in multiple "Views" based on varying user needs.
The general flow is something like the following.
- (necessary) find or perceive an issue in a software application
- (necessary) describe the issue in a way that's reproducable or recognizable, by creating an
Issue
in a project/repository - (optional) conceive of a fix for the issue
- (optional) test that the fix actually works - by updating code in a dev console or in a local instance of the app, for example
- (optional) submit the changed code fix as a Pull Request in the repo
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require 'open-uri' | |
require 'json' | |
require 'csv' | |
api_key = "YOUR-API-DATA-GOV-API-KEY-THAT-IS-ALSO-ENTERED-IN-TOUCHPOINTS-GOES-HERE" | |
url = "https://api.gsa.gov/analytics/touchpoints/v1/websites.json?API_KEY=#{api_key}" | |
# Make the API request | |
response = URI.open(url).read |