Mo Moder derator r Rachel Yalowich , Project Director, National Academy for State Health Policy
Lo Logis.cs f gis.cs for the W r the Webinar ebinar • If you are unable to listen to the webinar through your computer speakers, please use your phone: Dial in: (866) 519-2796 Access Code: 725013 • Lines will not be open during this webinar. • Comments are encouraged. Please use that chat box on the lower leM corner of your screen. • The chat feature is available, but will not be visible in full screen mode
DATA VISUALIZATION JENNIFER LYONS lyonsvisualiation@gmail.com
Why is data viz so important? Communicate Need Take Action Efficiency Make Change Illuminate Findings Funding Data Driven Decisions
Access to space must be a naPonal priority.
VISUALIZATION PROCESS
VISUALIZATION PROCESS 2. Break it down 1. Build it 3. Emphasize your story
VISUALIZATION PROCESS 2. Break it down 1. Build it 3. Emphasize your story
55% 34% 45% 55% 34% 45% 55% 45% 34%
55% 34% 45% 55% 34% 45% CHART FUNK? 55% 45% 34%
CHOOSING THE RIGHT CHART
Over the course of the year, sales decreased. 20 30 100 42 40 80 50 55 75 60 80 50 Jan Feb Mar April May June July Aug Sept Oct Nov Dec
Over the course of the year, sales decreased . 100 80 80 75 60 55 50 50 42 40 30 20 Jan Feb Mar April May June July Aug Sept Oct Nov Dec
Washington Missouri Kentucky Utah Kansas South Dakota Oklahoma New Hampshire Florida Oregon New Jersey Georgia North Carolina Michigan Illinois Louisiana Vermont Virginia California Texas Nevada Minnesota Delaware Maryland West Virginia New York Idaho Montana Colorado Alaska MassachuseZs Arkansas Wyoming Maine 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
VISUALIZATION PROCESS 2. Break it down 1. Build it 3. Emphasize your story
REDUCE CLUTTER
Protein Preference Beans Pork Extremely Dislike Dislike Tofu Slightly Dislike Neutral Fish Slightly Like Like Extremely Like Beef Chicken 0 50 100 150 200 250
Of all protein opPons, most people dislike tofu . Tofu 210 10 45 120 10 135 Pork 115 20 130 Beans Fish 60 50 155 Beef 45 20 200 30 20 215 Chicken Dislike Neutral Like
GESTALT
Proximity
Example from Evergreen Data’s blog “Directly Labeling in Excel”
Example from Evergreen Data’s blog “Directly Labeling in Excel”
YES! NO Example from Stephanie Evergreen and Jennifer Lyons research on “The Link Between Graphic Design and Actual Report Use”
Focal Point
There is an average in-flow of 8 veterans coming into our homeless system every month. 13 12 11 11 11 10 8 6 5 4 4 4 2 Jan. Feb. Mar. April May June July Aug. Sept. Oct. Nov. Dec.
There is an average in-flow of 8 veterans coming into our homeless system every month. 13 12 11 11 11 10 8 6 5 4 4 4 2 Jan. Feb. Mar. April May June July Aug. Sept. Oct. Nov. Dec.
ConHnuity
There is an average in-flow of 8 veterans coming into our homeless system every month. 13 12 11 11 11 10 8 6 5 4 4 4 2 Jan. Feb. Mar. April May June July Aug. Sept. Oct. Nov. Dec.
There is an average in-flow of 8 veterans coming into our homeless system every month. 13 12 11 11 11 10 8 6 5 4 4 4 2 Jan. Feb. Mar. April May June July Aug. Sept. Oct. Nov. Dec.
VISUALIZATION PROCESS 2. Break it down 1. Build it 3. Emphasize your story
STRATEGIC TEXT
Example from Ann Emery’s Blog
Example from Ann Emery’s Blog
DescripHve Title AcHve Title
DescripHve Title AcHve Title Protein Preferences
DescripHve Title AcHve Title Protein Preferences Of all protein options, most people dislike tofu.
DescripHve Title AcHve Title Protein Preferences Protein Preferences Of all protein options, most Of all protein options, most people dislike tofu. people dislike tofu. 2015 vs. 2016 Program Enrollment by Race
DescripHve Title AcHve Title Protein Preferences Of all protein options, most people dislike tofu. 2015 vs. 2016 Program 2016 enrollment for people of Enrollment by Race color has increased by 5%.
DescripHve Title AcHve Title Protein Preferences Of all protein options, most people dislike tofu. 2015 vs. 2016 Program 2016 enrollment for people of Enrollment by Race color has increased by 5%. Customer Satisfaction Survey Results
DescripHve Title AcHve Title Protein Preferences Of all protein options, most people dislike tofu. 2015 vs. 2016 Program 2016 enrollment for people of Enrollment by Race color has increased by 5%. Customer Satisfaction Overall, respondents were Survey Results most satisfied by our organization’s customer service and follow-up.
COLOR
I love learning about data visualization. It is so great to learn all of these new data best practices I will apply the things I have learned today to the data I use in my own work. Data visualization helps me better tell my story and communicate with my intended audience.
I love learning about data visualization. It is so great to learn all of these new data best practices I will apply the things I have learned today to the data I use in my own work. Data visualization helps me better tell my story and communicate with my intended audience.
2 out of 10 people receiving 2 out of 10 people our services are women . receiving our services VS. are women.
Regional sales for 2015 80% 70% 60% 50% 40% 30% 20% Jan Feb Mar April May June July Aug Sept Oct Nov Dec Region 1 Region 2 Region 3 Region4 Region 5
Region three sustained the usual summer sales slump. 80% Region 5 70% Region 1 60% Region 2 50% Region 4 Region 3 40% 30% 20% Jan Feb Mar April May June July Aug Sept Oct Nov Dec
All sales increased significantly during the holiday season. 80% Region 5 70% Region 1 60% Region 2 50% Region 4 Region 3 40% 30% 20% Jan Feb Mar April May June July Aug Sept Oct Nov Dec
C O L O R Example from Evergreen Data’s Blog
SOCIAL MEDIA
P R E S S
D A S H B O A R D Example from Natalya Wawrin’s work with the VA in Ann Arbor
DATA VISUALIZATION JENNIFER LYONS lyonsvisualiation@gmail.com
MA DEPARTMENT OF PUBLIC HEALTH Monica Bharel, MD MPH Commissioner of Public Health
HIV/AIDS IN MASSACHUSETTS July 2017
People Diagnosed with HIV Infection by Exposure Mode 2013 - 2015 by Exposure Mode: Massachusetts, 2013–2015 MSM/IDU Other Injection Drug 2% 1% Use Heterosexual 6% Sex 6% Male-to-Male Presumed Sex Heterosexual 44% Sex (Females) 13% Undetermined 28% N=1,994 Data Source: MDPH HIV/AIDS Surveillance Program, Data as of 1/1/17
Individuals Diagnosed with HIV Infection by Exposure Mode and Year of Diagnosis: Massachusetts, 2005–2015 400 350 MSM 300 HIV Diagnoses 250 200 NIR 150 IDU Pres. HTSX HTSX 100 50 MSM/IDU Other 0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Year of Diagnosis Data Source: MDPH HIV/AIDS Surveillance Program; Data as of 1/1/17
Percentage Distribution of Deaths among People Reported with HIV/ AIDS: Selected Exposure Modes & Year of Death: 2005–2014 Percent 60% Injection Drug Use 50% 40% 30% Male-to-Male Sex 20% Undetermined HTSX 10% PRES. HTSX 0% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year of Diagnosis N=2,732; HTSX = Heterosexual Sex; Pres. HTSX = Presumed Heterosexual Sex Data Source: MDPH HIV/AIDS Surveillance Program; Data are current as of 3/1/16 and may be subject to change
Proportion of Individuals Diagnosed with HIV Infection Among PWID by Race and Year of Diagnosis: Massachusetts, 2012–2015 Data Source: MDPH HIV/AIDS Surveillance Program; Data as of 1/1/17
OPIOIDS: USING DATA TO UNCOVER TRUTHS AND GUIDE POLICY July 2017
Opioid Related Deaths Figure 1. Opioid 1 -Related Deaths, All Intents Massachusetts Residents: January 2000 - December 2016 Confirmed Estimated 2,200 2,069 2,000 1,793 S R A 1,800 E Y Number of deaths 6 1 N 1,933 I 1,600 E S A E 1,651 R C 1,400 N I % 6 4 4 1,361 1,200 1,000 961 800 600 742 660 656 642 638 614 622 575 560 400 526 506 514 379 200 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 70% OF OPIOID DEATHS IN 2016 HAD THE PRESENCE OF FENTANYL
Opioid Related Deaths Figure 4. Percent of Opioid Deaths with Specific Drugs Present MA: 2014-2016 90 80 Fentanyl¹ 70 60 Likely Heroin 50 Percent Prescription Opioid² 40 Benzodiazepine 30 Cocaine 20 10 0 1 2 3 4 1 2 3 4 1 2 3 4 2014 2015 2016 Year and Quarter
Opioid Related Deaths
Opioid Overdose Death Rates, All Intents Massachusetts: 2011-2013 vs. 2014 - 2016
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