*Editor’s Note: This was part of my data story “Vegetable, Mineral, No More Animal” for Journalism 309: Data Storytelling. This biography explains the work I did to compile my data and extract insights from it, as well as the various sources I used. By doing this assignment, I advanced my skills using Microsoft Excel and Microsoft Word, and my proficiency using Tableau to visually display my insights.
Lifecycle of the Project
When this project was first introduced to us, I had no idea what my topic was going to be. While we were given a spreadsheet full of data about Kansas High Schools, I knew that I wanted to challenge myself. I wanted to do a project about something that I was passionate about, knowing my passion for my topic would help motivate me to do the work.
Having an interest in sustainability, environmental conservation and the protection of natural life, I was on the World Wildlife Fund’s website one day and found their species directory, including the 60 most-endangered animals in the world. The idea was planted in my mind and blossomed from there.
Data Orgin
The dataset primarily comes from the World Wildlife Fund. The World Wildlife Fund is one of the most trusted non-profit charities for animal conservation and environmental sustainability. They have a huge network of researchers, volunteers and educators they promote. I used their species directory as a general guide for the breakdown of the 60 most-endangered animals and then filled in individual animal pages by going to individual animal profiles.
My second most used source is the NOAA, the National Oceanic Atmospheric Administration. The NOAA is a U.S. government organization focused on understanding, predicting and mapping scientific data around weather patterns and the oceans. This extends to the conservation and education of species in and around the oceans, while also funding and promoting research of these habitats.
The 30+ additional sources are linked in my Excel Sheet, which complies all of the collected data. The other sources are usually organizations dedicated to specific animals or educational institutions like zoos and aquariums.
Spreadsheet Compilation
My Excel spreadsheet is 61 rows by 16 columns. Each row, after the title row, is each of the 60 most-endangered animals separated by conservation status. Each column is a different analytical value such as name, natural habitat location, the primary/ secondary threats and the low and high population estimates, among others. These columns are intended to bring context to the data and help provide as much of a complete picture as possible.
Data Transformation
The transformation of the data was a multi-step process. I am a visual processor, so I colored the data according to conservation status in order to have a clearer visual divide between the categories I was analyzing. Additionally, I organized the animals within each category by the low estimated population size.
I also simplified the data by splitting the age range, estimated length and height, and estimated population into a high/low estimate. This set up the data easier for analysis without having to worry about varying numerals.
Data Analysis
Similarly to the data transformation, the analysis was a multistep process. This was the element I spent the most time completing due to the extent I analyzed each data category.
The majority of analysis occurred within Microsoft Excel using the Pivot Table functions. This work was then compiled on a Google document. The analysis began with a univariate analysis of each data category. After that, each Pivot Table compared two or more data points.
For example, some analysis was between primary threat and animal name in order to determine the breakdown of animals and which threats they primarily face. In a more complex example, one analysis included a high weight estimate by animal name by low estimated population to see if a clear correlation could be drawn between animal weight and estimated population. The results of this analysis were inconclusive because factors such as primary/ secondary threats were more influential.
Story Writing
In putting together my story, I wanted to combine words and different types of visuals in order to tell a clear, well-rounded story that would resonate with people. The nature of my topic allowed me to rely more on visual communication as animals are visual creatures, and connection with them is largely dependent on exposure to the animal either in person or through pictures and videos. While reading about these threats is one thing, seeing what it looks like when they occur is far more memorable and impactful.
The Written Story
For the written part of my story, I wanted to make the language simple and easy to understand so that my audience wouldn’t lose the main message in-between complex language and analysis.
Additionally, I wanted my introduction to really draw people in and hit them hard. While writing, I was very attuned to the fact that some people don’t care about environmental and animal conservation to the extent that I do. So how do I get those potential lost readers invested in my work? I make my work relevant to them. And what better way to do that than with a harsh emotional reality?
Furthermore, I was aware of how depressing the bulk of this information is. Because of this, I added an additional part to my story. Part Four: The Solutions, was not initially a part of my plan for this story. However, I didn’t want to set up an entire story about the death of animals and leave my readers without restoring a little hope. Even though it added to my workload, I believe Part Four: The Solutions is necessary for a balanced and well-proportioned story.
The Visual Story
As for the visuals I chose to include, I knew there were going to be two kinds. I had my data visualizations from work we had completed in class, but I wanted to visually tell my story with more than charts. Speaking from experience, I know people tend to lose interest in a story- no matter the topic- when graphs, data and numbers are the dominant visual representation. With my data visuals, I wanted to focus on colors, easy-to-read text and numbers, and simple data. My data visuals were designed to help dissect the data for the reader and add content to the written narrative.
Outside of the data visuals, I wanted to include images. Images help take a topic and transition it from a hypothetical one into an observable reality. It’s much easier to connect with a topic when you watch it happen. For this story about endangered animals, it’s also much easier to explain the severity of each threat and the extent to which this is an issue if you see what the consequences are. You can’t ignore the issue if it’s staring at you in the face.
Each image in my story has a deliberate purpose. I wanted to have cute pictures of animals so that the reader would care about the animals. My audience connects with the animals and feels for them. Then, I chose pictures that display the atrocities of the threats affecting animals so the reader understands the brutality of the offenses against animals. I want my reader to be horrified. I want them to be uncomfortable. That unease forces the reader to care. That unease makes this issue real.
In the preparation for the publication of this project in my portfolio, I also researched copyright law to guarantee that I could legally use my chosen photographs. My use of these photographs is protected by Fair Use under Copyright law. I am a student, and these photos are being used for academic purposes. This project is a news article and I am compiling various photos from various locations in order to tell a new story. I have given credit to the original publication and photographer of the photos. Additionally, I am not taking large amounts of work from the original creator, nor am I profiting off the publication of these images. Under these classifications, I am legally able to publish these photos.
The Anthology of a Curio 