One Photo is worth 1000 Words – One Visualization is worth 1000 Stories – Together they add Emotion to the Data – Together they Propel Action
What if I were to tell you that Hurricane Florence poured over North Carolina in Sept. 2018 as much as the average rainfall for an entire year in Seattle?! Are you able to imagine the devastation? Since the ODTUG main offices are located in North Carolina, ODTUGers jumped in to help with their technical skills by creating an Oracle APEX Road Closure Navigation App that would display the most up to date road closures from the North Carolina Department of Transportation. Oracle DV was used to visualize the NCDOT dataset with the goal of creating a data-rich visual perception of the road closures’ impact across the state. Here’s a quick preview of the app, and the story behind it.
What if I were to show you that seeing a real photo of one flooded road would look very similar as one visualization of 365 flooded roads?! We believe the latter would awaken you to a fuller experience of this natural disaster. Seems like the NYC Oracle Analytics Nov. Workshop participants agreed with that statement after I showcased the visualizations. I even got an Oracle branded Tile for the good work. (out of all practical applications for Tiles, the first thought that came to me was a treasure hunt… go figure!)
My original goal for this blog post was to first walk you through the Data Collection, Data Wrangling, Data Exploration, Data Visualization & Explanation steps that were necessary to take to finally tell the visual story behind Hurricane Florence’s road closure impact across North Carolina. Hopefully along with Oracle BI Expert, Wayne D. Van Sluys, we will hopefully give you all those details in a #Kscope19 session (fingers crossed). If you haven’t registered yet for one of the best Oracle technical conferences of the year… you are certainly missing out 😉
Another reason that I’m going to skip this part is the fact that along with my fellow GE EPM/BI enthusiast, Gary Adashek, we soon plan to use Oracle DV to visualize the data sets of the Data.World #MakeoverMonday community. Along that journey we will share:
- Tips on how to prep, and clean up source data before loading it to Oracle DV.
- The different ways to modify data in Oracle DV from the Data tab, Visualize tab etc.
- How to update the settings for each visualization (Ex: Node labels, Legend, Data display options, Axis sorting etc.), and other topics.
One Flooded Road out of …
Back to the original goal of this post: What if I were to show you that seeing a real photo of one flooded road would look very similar as one visualization of 365 flooded roads?! Would your experience of this natural disaster become more comprehensible? Every time I see the below side by side visualization, I’m overwhelmed at the thought of imagining hundreds of roads in a similar situation.
When I initially created this Parallel Coordinates visualization I asked myself: “What message am I trying to convey with this mess!! This is going to confuse everyone if they don’t see it the way I picture it in my head…”
As a stand-alone visualization, you would have a hard time understanding that what you’re seeing is actually a link between the name of the flooded roads, and the North Carolina counties that those flooded roads crossed through. All you would see is hundreds of blue lines intersecting, creating a what seems like a river full of water… or perhaps an imaginary flooded road!
This is where my love for photography (Flickr Portfolio) and data visualization complement each other. It is an example of how a stand-alone real world representation of one data point can be showcased side by side with the visualization of hundreds of data points to convey a more complete emotional experience. It is then that your audience will get the full story, it is after that moment when your audience will be propelled to take action. In this specific case, the action might be as simple as donating to hurricane relief funds, volunteering to aid the impacted communities, join a #climateaction local group etc.
After all, what is the point of data visualization if not to convey a true message in an easy to understand, and direct way to a general public with the goal of influencing their opinions and their actions?!
One Photo is worth 1000 Words
One Visualization is worth 1000 Stories
Together they add Emotion to the Data
Together they Propel Action
One Flooded Neighborhood out of …
In another example, I used a Tag Cloud visualization to show the North Carolina counties most impacted by flooded roads. As a stand-alone visualization you would just get the dry facts. It is then up to the individual to be able to translate those facts into an emotional reaction and then a concrete action.
In the below visualization, I aimed to mirror the word representing a county to the equally sized image of one flooded house. After all, a spacial view of a flooded neighborhood does look similar to a Tag Cloud visualization. Yet another example of how a stand-alone real world representation of one zoomed in data point can be showcased side by side with the visualization of hundreds of data points to convey a more complete emotional experience.
Probably after seeing the image of just one flooded neighborhood alongside a visualization of the the most impacted counties, you would be able to visualize the whole impact, you would then be able to translate the data into real visuals, you would truly ‘see’ the thousands of houses in a similar situation across the most impacted North Carolina counties.
Recommended by one of my good friends, I recently attended Edward R. Tufte’s class: Presenting Data & Information. In his book “The Visual Display of Quantitative Information” he quotes: “Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space.”
I have a feeling that pairing a real world image of one data point that visually aligns with the design of the visualization of the whole data set would indeed help you reach the goal of visual storytelling in a concise, direct, and emotional way.
One Hurricane out of …
After creating a Radar Bar visualization of all the flooded roads of North Carolina during Hurricane Florence, I had the idea to add on the side an image of the hurricane itself. Both the visualization, and the spacial hurricane photo have a similar circular shape, with the visualization’s bars visually aligning with the hurricane’s rotating arms.
On the right you see a photo of the cause of this natural disaster: the hurricane. On the left you see a visualization of the impact of this natural disaster: the hundreds of flooded roads. Seeing only the data visualization would leave you somehow emotionally dry when it comes to experiencing a fuller understanding of what happened in North Carolina on Sept. 2018, unless you combine Data Viz + Real Image => Getting the Picture
One Data Set out of …
One of my goals for 2019 is to visualize the natural disaster occurrences of the past year, and showcase how that trend relates to Climate Change. That visualization will most likely be published on fabe: forallabeautiful.earth as part of my commitment to reducing consumption on an individual level in our collective journey towards healing our planet, and creating a better world. Florence was only one hurricane out of many in 2018, climate change is indeed making storms like Hurricane Florence worse.
This blog post gives you one example of how we can translate an Excel data set into meaningful visualizations to educate, and influence a community.
In 2019, along with other #orclBI enthusiasts, I hope to use Oracle DV to:
- Bring to life data sets published in the Data.World #MakeoverMonday community with the goal of improving how we visualize, and analyze data one chart at a time.
- Harness the power of data visualization for social change, and empower nonprofits through data stories via the #VizForSocialGood community.
As you can see below I started a little bit earlier 🙂
In this visualization I have depicted in icy pale blue the years where the ice surface area was higher. As we progress through the past two decades the color changes to a darker ocean blue, representing the melting ice mass. That visual effect looks similar to what’s happening in reality as you can see in the 2 images on the left.
In a stand-alone visualization, you would just see the facts. Paired with the contrasting images of how the Arctic Ice has shrinked in between only two data points (years), you would most likely experience what you’re seeing with some bonus emotions. Once the data and the view of reality overwhelm your visual sense of understanding you would hopefully be more prone to acting upon what you’re seeing.
Sr. Technical Product Manager
Finance EPM at General Electric
If you’re curious to see how this story-line started, check out the original blog post: A #TechGivesBack Story: Hurricane Florence NCDOT Road Closure, GasBuddy Navigation App