Mar
4
9:30 am09:30

Open water rate spectactular

  • 418 Bamboo Lane, Suite A Los Angeles, CA 90012

How much did Californians pay last month for water? Do consumer prices vary by ethnicity, income, or location? 

To help answer these questions and more, please join CaDC’s as we celebrate International Open Data Day. Our goal is to increase the portion of California’s water agencies represented in CaDC’s Open Water Rate Specification (OWRS). With OWRS, CaDC aims to standardize each of the state’s retail water rates and make them accessible in a common, machine-readable data format. With these data, we may better understand water use in California and enable regional water agencies to prepare for an uncertain future.

Participants in CaDC’s International Open Data Day will contribute to the project by documenting water prices from agencies across the state. Many of these prices are reported in PDFs rather than in machine-readable files. With your help, we can turn these PDFs into interoperable machine-readable data. CaDC staff will offer training to any participants new to GitHub and data serialization.

OWRS has been prototyped and piloted by member agencies within the CaDC coalition. You can see the latest work on our open source GitHub repository here: https://github.com/California-Data-Collaborative/Open-Water-Rate-Specification. OWRS is ready to be implemented with more utilities, increasing the transparency of water rates and improving CaDC open source analytics, which support effective water management. 

  • 9:30am - Doors
  • 10:00 - Kickoff, Overview of CaDC's work and Water Data Rates
  • 11:00 - Create OWRS files!

Please register here to participate.  

Many thanks to RDN consulting for sponsoring this event and providing delicious lunch for all participants! 

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Sep
9
8:00 am08:00

Water Data Summit at Stanford GSB!

  • Stanford Graduate School of Business

Mark your calendars for the Collaborative's much anticipated Water Data Summit on Friday,September 9th at Stanford GSB. This day-long event will feature interactive panels on how big water data integration is supporting water managers in California. Our aim is to bring together leading water professionals across California in order to scale these early successes for statewide impact. 

Jul
12
10:00 am10:00

Optimizing System Operations

  • Inland Empire Utilities Agency

This technical working group meeting will discuss the implications of granular water demand data for water system operations and the broader water world.  We're working to see if we can get the leader of the research group at NYU CUSP developing next generation energy star score metrics and massive sensor applications to present.

Please see here for an example visualization Chris built for that research group and here for a description of one of their grander ongoing projects: Hudson Yards, America's largest ever real estate development and first ever quantified community.

This time series shows preliminary demand forecasting results from an experimental collaboration with DataKind, a nonprofit organization backed by the Clinton Global Initiative that brings talented volunteer data scientists to bear on important public problems

This time series shows preliminary demand forecasting results from an experimental collaboration with DataKind, a nonprofit organization backed by the Clinton Global Initiative that brings talented volunteer data scientists to bear on important public problems

 
Jun
8
10:00 am10:00

Lessons learned for statewide water efficiency

Task 1.2 of the MOU requests that we surface lessons learned from our pilot project for statewide water efficiency.  In the four months since launch, we've learned a great deal about water data management best practices to enable water efficiency analytics.  We've also discussed how evapotranspiration, irrigable area and population growth can provide key context to supplement existing statewide reports of urban water use.  There's no statewide repository of irrigable area information and we're working with our "remote sensing brain trust" to scope how to best reconcile that by leveraging freely available NAIP imagery and developing robust accuracy assessments of vendors using proprietary imagery.

Classification of ground cover types from free NAIP imagery. Left shows an unaltered NAIP image with parcel polygon. Right shows the classifier output with colors representing different ground covers. Turfgrass is visible as bright green.

Classification of ground cover types from free NAIP imagery. Left shows an unaltered
NAIP image with parcel polygon. Right shows the classifier output with colors representing different ground covers. Turfgrass is visible as bright green.