Brainstorm DOC - https://docs.google.com/document/d/1h1tq6URVTEinGAatKxs6Adybji50wT9O8ceLaoPGd0E/edit?usp=sharing
Github Org - https://github.com/Data-Transparency-Task-Force
Hackathon Vids - https://www.youtube.com/playlist?list=PLvTrX8LNPbPn4HiPG6jdmScrP4VGCNy5y
Power Point - https://docs.google.com/presentation/d/1DHZlcC9lX0p13apiiNP8EgSh69lSIHsSNtk_cf5wuD0/edit#slide=id.p
5/1 TODO
- 1UP Health setup - WIP
- add meeting notes
- data discussion today @ 5:30 ideally
- brain storm how to transform 5 data metrics into -> easy to understand confidence metric
- come up with concrete questions for @profmike.
April 30th TODO
- intros
- react js demo
- discussion points
- phased approach to metric creation/feedback gathering
- decide on 1st 3 phases criterion
- mascot
- iterate on github workflow - https://gist.github.com/blackfalcon/8428401
- zk snarks discussion
Discussion Points
Official team doge/mascot “Henry” for inspiration!
Metric (DTS??) - The metric itself should instill confidence. Calculations should be as transparent as possible
-
Current colloquial metric is number of people deceased - lags several weeks behind what’s happening
-
The second metric we all know is the number of cases tested positive. This too isn’t helpful because it ignores the number of people who could already be infected but haven’t yet ‘tested’ positive, or could soon be infected because of a particular relationship between population density infection rates. It ignores the context that number is couched in.
-
It is also critical to know how many people have been tested;
- current testing data is wholly inadequate to provide for any of the needs listed above, and indeed our current struggles reflect this
Phased Approach to metric creation
Phase 0.0 - A ok or maybe not so good (MVP) confidence metric
Metrics to focus on for a given area (state):
- Deaths
- Confirmed cases
- Tests administered
- Risk factors - don’t see a lot
- Resources available - don’t see a lot
We need help in determining where to pull our data from and how to synthesize this into our ELI5ish confidence metric:
MVP - map of location w/ heatmap radius and statistics on hover (aggregated from AWS data lake)
- one state
- county specific information
- can scale up to phase 1 or 2
Phase 1 - MVP+ - WIP
Phase 2 -
How to contribute <- TODO: made need updating
- Click “Gitpod Ready-to-Code” badge to start up a new coding workspace.
- Under the Source Control: git menu select “Fork” -
- Press enter to confirm selection
u should receive confirmation you successfully switched git url in the lower right cornern
- Make modifications
git add *
git commit -m <DESCRIPTION_OF_WHAT_CHANGES_I_MADE>
git push
<- from here you can make a pull request w/ changes between our org repo and the forked repo.
Architecture Planning
Discussion of DTF Software Architecture Repo
- Application for Healthcare Workers - MAP w/ Data Transparency Score (DTS) - create mockup w/ react - **WIP**
- Data Models for Storing Factors -
- Query Resource Databases - compile list
- Verified Real-Time Data Guaranteed Via Smart Contract
- Secure File Storage with Agile Referencing
use JS based tech
- NodeJS - https://github.com/nodejs/node
- SQL - https://aws.amazon.com/blogs/big-data/a-public-data-lake-for-analysis-of-covid-19-data/
- IPFS-JS - https://github.com/ipfs/js-ipfs
- ReactJS - https://github.com/facebook/react
UI - web dashboard (world map)
- Google Maps API - https://www.npmjs.com/package/google-map-react
- HTML5
- Google Maps Reach Component gives us a lot of functionality for free but is not open source
- new forked https://www.newline.co/fullstack-react/articles/how-to-write-a-google-maps-react-component/
IPFS for storage
- Hash Based Linking
- Secure SHA Encryption
- Scalable File Structure
ZK-snarks
- TODO:
Determine whether we should use zero knowledge proofs to preserve user privacy
Review ZKP presentation: \
- [ ] reach out to expert and ask for her opinion? - Hadas Zeilberger, ConsenSys Health's ZK specialist to present on ZK's and lead a Q&A session about privacy and zero-knowledge solutions
- [ ] thoughts?
- ZKP's are complex
Data lakes/sets etc.
1UP
https://1up.health/dev/fhir-analytics <- this look interesting and has office hours tom
CALIFORNIA
https://healthdata.gov/dataset/california-covid-19-hospital-data-and-case-statistics
AWS
COVID-19 data sets provided by AWS: <- need to query Amazon COVID-19 data lake w/ SQL.
-
https://aws.amazon.com/blogs/big-data/a-public-data-lake-for-analysis-of-covid-19-data/
-
https://covid19.healthdata.org/united-states-of-america
-
https://github.com/CSSEGISandData/COVID-19
-
https://datascience.nih.gov/covid-19-open-access-resources
Other:
-
https://c19hcc.org/resource-library/
-
https://covidtracking.com/data
As we are watching this unfold we are getting mess of metrics scientific community + individuals what does this mean huge limitations cases per day is not reliable deaths per day when they die they die more clean cut death data on mondays ->
risk and uncertainty calculation
a (un)certainty metric
existence of metric should make people want to increase testing testing key
Meeting Flow
Intros
overall metric idea
react google maps library - UI dev
metric discussion
moving forward, questions, and feedback
Meeting w/ chris morning 30th MVP discussion
MVP - map of location w/ heatmap radius and statistics on hover (aggregated from AWS data lake)
- one state
- county specific information
- can scale up to phase 1 or 2
CDC for data - state level data - local health department private clinic data - having trouble getting data under reporting gon federal level non centralizd health system hopkins uva supply data GIS hospitals, race, sex demograhic data
green/red - recommend trends positive or negative correlation not sure on data source for public measures
PPE might be tough - facilities and beds local or state health department resources
4/30/10
- [] github cleanup
- gitcoin response data scientist
- schedule discussions w/ chris
- @ 5:30 sync make sure to update chris + max on schedule