Water Educator Network Symposium

Innovative Water Education in the 21st Century

Visual storytelling, using technology to share

Colorado’s Water StoriesNovember 17, 2016

Steve Malers, Open Water Foundation

steve.malers@openwaterfoundation.org

www.openwaterfoundation.org

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Open Water FoundationSocial enterprise 501(c)3 nonprofit focusing on developing open source software tools to help make better decisions about water resources. Water is a public resource, and water data and software tools should also be public.

openwaterfoundation.org

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Telling Your Story with Data

“There are two goals

when presenting data:

convey your story and

establish credibility.”

-Edward Tufte

https://en.wikipedia.org/wiki/Edward_Tufte

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Make the Complicated…Simple

“Making the simple

complicated is

commonplace.

Making the

complicated simple,

awesomely simple,

that’s creativity”

-Charles Mingushttps://en.wikiquote.org/wiki/Charles_Mingus

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Resource: 2015 Presentation“Water Education through Stories Using Open and Big Data”

2015 Sustaining Colorado’s Watersheds, October 8, 2015

http://openwaterfoundation.org/wp-content/uploads/2016/04/SCW-2015-Malers.pdf

(1854) London Cholera outbreak (1858) Where does Paris get its beef?

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Resource: 2016 SMP Presentation“Step 5 – Existing Data Collection / Data as a Platform”

Stream Management Plan Workshop, Aug 23-24, 2016

http://openwaterfoundation.org/wp-content/uploads/2016/08/CWC-2016-SMP-Workshop-Step5-Malers.pdf

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Overview of Publishing Story for Web

Your dataset

Someone else’s dataset

Derived dataset

Cloud-hosted dataset

Get your datasets

in order

Context / Credibility / Visualization / Story / (Re)Action

Visualize / Tell Story

Raw Data View

Analytics

Dashboard

Story

Infographic

What is the complexity and

cost (money, effort)?

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Nothing is ever easy…until it is

Simple approach:

“Just tell me what I

need to do”

…but… “you mean I can’t do THAT?”

80/20 rule

Complex approach:

“Learn the

technologies”

…and… “I can do whatever I want”

(until you need to learn more)

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Cloud Data Hosting

• Dropbox

• Google Drive

• Amazon

• Microsoft Azure

• Box

• Many others

• Hosting integrated with visualization

• How to do I load datasets?• How does software get to the datasets?• What are features and limitations?• How much does it cost?• Can I change my mind later?

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data.colorado.gov

http://www.edwardtufte.com/bboard/q-and-a-fetch-msg?msg_id=0002N4“dataset” = often a table or map layer

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opencolorado.org

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coloradodata.statesales.opendata.arcgis.com

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Cloud Data Hosting for Spatial Data

• DataBasin.org

• ArcGIS Online

• Carto

• MapBox

• Mango

• Google Maps

• Many others

• Can treat as files using file hosting services• How to do I load datasets?• How does software get to the datasets?• What are features and limitations?• How much does it cost?• Can I change my mind later?

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DataBasin.org

National-level

resource

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CDSS and CWCB Map Viewers

Good for locating data, ad hoc queries

Limitation – limited data download, lack of automation

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Stream Mile Representation Framework

Stream mile + Excel = simple

E&R Attributes

Instream Flow Reaches

Projects & Methods

Stream Gages

Diversion Headgates

Organization Extent

Master Plans

and more…

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Citizen Science Platforms

http://pubs.usgs.gov/sir/2015/5015/

http://www.cocorahs.org

Also see citsci.org

High Groundwater

CoCoRaHS

Citizen-reported

precipitation

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Raw Data View

• Graph

• Table

• Simple map

• Static image/page or interactive

• Perhaps with download link

Goal is data access

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Raw Data Example

Annotations go a

long way towards

providing context

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Raw Data Example

Sometimes the data

speaks for itself

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Analytics

“Analytics is the discovery, interpretation, and

communication of meaningful patterns in

data.” - Wikipedia

“Data visualization

communicates insight.”

• Tableau• Zeppelinhub.com• D3.js• Others

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Analytics Example

“raster graph” or

“heat map”

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Analytics Example

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Analytics Example

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Dashboard

• “Dashboards often provide at-a-glance views

of key performance indicators (KPIs) relevant

to a particular objective or business

process.” – Wikipedia

• Often a combination of visualizations.

= real-time-ish data?

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Dashboard Example

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Telling Stories

• Characters – roles, perspective

• Plot

• Narrative point of view

• Purpose: share values, pass

knowledge, generate outcome

http://www.compassonline.org/

https://en.wikipedia.org/wiki/Storytelling

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Example Story

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The Most Common Jobs in Each State

1978 1990

2000 2014

http://apps.npr.org/dailygraphics/graphics/hist-job-map-90/child.html

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Irrigated Agriculture Dry Up

1956 1976

1987 2010Open Water Foundation

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Infographics

“Information graphics or infographics

are graphic, visual representations of

information, data, or knowledge

intended to present information

quickly and clearly.” - Wikipedia

Often include annotations and

clever visualization techniques

“What is urban water use efficiency?”

Groundwater withdrawals

Wholesale

provider

(raw/treated)

Springs

Water

treatment

plant

Wastewater

treatment

plant

Non-potable water

Potable water

Wastewater

Treated wastewater

Distributed

non-potable water

Distributed potable water

Municipal/

Utility

Facility

Commercial,

Industrial,

and

Institutional

(CII)

Residential-Single-family

-Multi-family

Irrigation

only

Resale

entity

Wholesale & agricultural sales

Treated wastewater effluent

Raw water supply

2016-01-31

Urban Water

Provider

System Components

Downstream

Effluent

treatment

plant

System

losses

Treated effluent reuse

Sewage collection system

Surface water diversions

Stormwater

/

stormsewer

Irrigation return flows

Precipitation

Precipitation

or

Upstream

Surface and subsurface (delayed) flows

Surface and subsurface (delayed) flows

Irrigated

Agriculture

Collection /

Detention /

Runoff

Environment

& Recreation

Storage

Self-Supplied

Industry

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The “Snake” Diagram

http://www.nytimes.com/2010/04/27/world/27powerpoint.html

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Colorado Water Economy

http://www.denverwater.org/docs/assets/4bea7503-0237-e833-64a3f4c3447f588c/frwc_econ_report.pdf

“Water and

the Colorado

Economy”,

Front Range

Water Council,

2009

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Rain Barrels

Denver Water

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Virtual Water Balance

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Summary

• Get your data house in order…figure out the

datasets and the data flow.

• Determine the story you want to tell and what

datasets are needed…do you have the datasets you

need?

• Select technologies.

• Visualize dataset(s). Provide context.

• Organize visualizations for impact…as dashboard,

story, etc.

• Keep it relevant…keep investing in new data, better

visualization, technology updates.

• There will be a cost.

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Share ItThe content of this presentation is licensed under the Creative Commons Attribution NonCommercial License:

http://creativecommons.org/licenses/by-nc/4.0

openwaterfoundation.org