| layout | category | title | tagline | comments |
|---|---|---|---|---|
default |
sac2050 |
Get Started |
Instructions for the November 14, 2015 Civic Datathon |
true |
| Time | Activity |
|---|---|
| 9:30am | Check-in for Team Leads |
| 9:45am | Check-in for Participants |
| 10am | Datathon Begins |
| Noon | Lunch (provided) + Awesome Video |
| 1pm | Datathon Continues |
| 1:30pm | Submit Data + Presentations |
| 2pm | Datathon Ends (...or does it?) |
First of all, thanks for being part of the Sacramento region's first Quality of Life Civic Datathon! We truly appreciate you taking time out of your weekend to help us crowdsource critical datasets to measure quality of life in our communities. This website would not exist without your help.
You're here to help us crowdsource key quality of life indicator data. That data will be used to create dynamic dashboards on this website to inform a regional conversation about where we’re at, where we want to go, and how we’re going to get there.
We'll have six teams at the datathon focused on the following topics:
- The Economy
- K-12 and Higher Education
- Health and Families
- Public Safety
- Environmental Sustainability
- Transportation and Housing
Once you've decided on a topic, assign yourself to a team here. Each topic page has an existing list of indicators.
Your job is to go get the dataset for one of the indicators listed on your topic page. Among your team, divide and conquer. It's reasonable for each participant to tackle one or two indicators for the day.
No problem. If you're interested in working on a different indicator, just let your team leader know and we'll make sure we can include your dataset.
If you're not already an expert, do some research on your indicator. Find out if it's in the news. Google the term and "Sacramento" to see what results appear. This will help you spot important trends.
Now it's time to get the raw data. Again, use Google. Or check out some of these other indicator efforts to discover raw data sources:
We are looking for both longitudinal (over time) and cross-sectional (across geographies or other categories) data. It's great if you can find 10 years of data. Even better if you can find 20 years of data.
What's the story? Is the trend improving, declining, or holding steady? Are there disparities across race/ethnicity or cities/counties? Try to come up with a punchy summary that's 2-3 sentences in length.
Email your dataset file (e.g., .csv, .xlsx, etc.) to [email protected].
If you prefer to get in touch via email, drop us a line at [email protected].