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sewer_overflow_data_challenge's Introduction

Sewer_Overflow_Data_Challenge

One month data open data challenge to win a summer informatics internship with ARGO!

Why visualize Sanitary Sewer Outflows?

No one wants sewage in their street! "A sanitary sewer overflow (SSO) is any overflow, spill, release, discharge or diversion of untreated or partially treated wastewater from a sanitary sewer system."

Moreover, California signed in to law the Open and Transparent Water Data Act last year and the goal of this visualization challenge is to support state implementation by showing what is possible with modern digital tools.

The Data Challenge

Create an epic visualization of Sanitary Sewer Outflows (SSO)! The data is available in the SSO_Data folder in this repo and the original files can be found at the following link.

Note in particular that "The SSO Data tables above are all keyed on the sanitary system WDID number."

Also note that the data fields are defined on that Glossary of Terms at the top of the page on the orignal file link above and directly here.

Please leave any questions about the datasets in the GitHub issues on this page so they form a reausable resource for future participants! A helpful guide to GitHub issues is available here.

Questions to Explore

Again you can find the glossary of terms used in the datasets available here. In particular we recommend looking at SSO.csv and digging into the following questions:

(1) where and how bad (volume, made it to receiving water, etc.) are the sewage leaks (SSOs)? (2) how are sewage leaks changing over time? (3) which agencies have the most (by occurence, by volume, etc.) sewage leaks? (4) what other data can be brought to bear on this topic (precip, storm water dry weather flows, etc.)? (5) find other patterns and unique insights!

An example operational report analyzing this data can be found here.

Resources

See here for the results of the CA Water Data Challenge last year to get inspired! For potential visualization tools, see https://infogr.am/, https://www.silk.co/, datavizforall.org and https://public.tableau.com/s/.

Timeline

Please submit your final responses as a pull request from a fork of this repo by Friday May 26th at 5 PM PST. We will have office hours on Thursday May 18th in person at the LA Clean Technology Incubator from 2:30-3:30 PM. If there's interest we can also do a virtual video chat as well during that time to answer questions.

The Prize

The best submission will win a $250 prize and quality submission are eligible for a paid summer internship with ARGO on our big water data or other urban analytics projects! That and the opportunity to build a brighter future for California!

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sewer_overflow_data_challenge's Issues

Incorrect Latitude And Longitude Values.

There are a few errors in the Longitude values of certain places in the SSO dataset.
The values are positive wherein they should be negative to be correctly mapped to a county inside of California.
For instance,a number of WDID's from the Sacramento county when plotted on a map are mapping to places in North Korea and the yellow sea.
while, some of the values can be corrected by just introducing a negative sign, some other are noted incorrectly and cannot be corrected in this manner.

Feature to subset the data

Hello Sir,

Can you please tell me the feature that should be selected to subset the data for analysis.

Do you want the graphs to display analysis of each WDID as that would contain more than 1092 subsets to do our analysis on
or do you want the analysis to be done for each county,in that case there would be 58 subsets.

Description Of column Names

The links provided in the description do explain the meaning of the datasets whereas it would be quite helpful if we could get a brief description of the column names inside of each dataset.
Some of the columns are self explanatory while some aren't.
It would be very helpful if we could get some description of the column names inside of the data sets.

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