Name: Equity in the Age of COVID: A Mathematica Data Week DC Data Dive (Part I)
Start: 2021-10-07T12:00:00-04:00
End: 2021-10-07T14:00:00-04:00

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UPDATE
If you'd like to participate in this event but cannot attend the first day, you are welcome to get started asynchronously. A recording of the Day I session and session materials will be sent to all registered participants Thursday afternoon. We will also open access to the event Slack channel tomorrow morning. You may submit questions via the Slack channel at any time. We will respond to your questions as quickly as possible.

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Much has been made about how the COVID-19 pandemic has exacerbated and highlighted long-standing inequities in health, education, and access to critical government services. There are plenty of data to demonstrate the stark reality of this inequality, but what data can be used to actually address it?

Mathematica has developed a number of tools and visualizations to support COVID-19 response and recovery, such as:
> 19 and Me: https://19andme.covid19.mathematica.org/
> Teacher shortage dashboard: https://k12staffing.covid19.mathematica.org/
> COVID-19 K-12 School Testing Impact Estimator: https://covid-school-testing.mathematica.org/start
> COVID-19 Wastewater Dashboard: https://www.mathematica.org/dataviz/covid-19-wastewater-dashboard
> COVID-19 Youth Unemployment Tracker: https://www.mathematica.org/dataviz/youth-unemployment-tracker

During this TWO-DAY Data Week DC 2021 event—co-hosted by Mathematica and Data Education DC—participants will work in teams to explore local policy and program data to prototype their own decision support tools or interactive visualizations for a fictional regional foundation. The fictional funder would like to make an investment in COVID-19 recovery in the DC metropolitan area (including Maryland and Virginia suburbs) but would like to make an evidence-based decision about where to target their charitable dollars. Where might they make the biggest impact in 2022? The foundation has struggled to make a decision because they lack access to real-time data sources or adequate historical data to create predictive models. The foundation would like to award grants to community-based organizations and local agencies in one of four areas: health (including mental health), education, employment or housing.

With the support of Mathematica experts in these four domains, each team will be charged with developing and presenting a data-informed recommendation based on the visualization or tool they develop:
> Fei Xing, Associate Director, Data Science (https://www.mathematica.org/staff/fei-xing)
> Lauren Amos, Senior Researcher (https://www.mathematica.org/staff/lauren-amos)
> Cindy Hu, Lead Data Scientist (https://www.mathematica.org/staff/cindy-hu)
> Hande Inanc, Researcher (https://www.mathematica.org/staff/hande-inanc)

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REGISTRATION
This event is free but REGISTRATION IS REQUIRED to receive the Zoom link: https://www.eventbrite.com/e/equity-in-the-age-of-covid-a-mathematica-data-week-dc-data-dive-tickets-181212650917

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DATA DIVE DETAILS
You don’t have to be a data scientist to play! This event is open to all regardless of your level of data viz experience, background, training or profession—including anyone interested in learning more about developing compelling visualizations that can support evidence-based policymaking.

Participants can use the medium or platform of their choosing (e.g., D3, RShiny, Tableau, paper and pencil). Laptops and software will not be provided but access to a virtual collaborative workspace will be provided to project teams. Project teams will work together in Zoom breakout groups during the event.

Feel free to work individually or in small groups. Virtual breakout rooms and a collaborative workspace will be available so that teams can work together remotely.

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DATA SOURCES AND DATASETS
Data sources, sample datasets, and a sample code repository for the event will be available on or before October 6 to all registrants.

Lauren Amos

Data Community DC (DC2)

Data Education DC

Technology

Data Science

Machine Learning

Data Analytics

Applied Statistics

Data Visualization

R Project for Statistical Computing

Data Mining

Open Source

Big Data

Computer Programming

Software Development

College Students

Lloyd Brodsky

J o o n

Chris Bennett

Polly McKim Halloran

Rahul

Josh Touyz

Kent

Equity in the Age of COVID: A Mathematica Data Week DC Data Dive (Part I)

COVID-19

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Data Education DC

Equity in the Age of COVID: A Mathematica Data Week DC Data Dive (Part I)

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