Data Visualization through NASA’s TESS Mission Exoplanets

Data visualization is a robust tool to represent complex data to readers. Taking it a step further; narrative visualization allows us to craft data stories that transform information right into a series of compelling scenes. This approach tailors the experience for the audience.

Narrative visualization is about crafting scenes that guide the audience through the information. It represents data in an revolutionary way making a story through it. This story emphasizes the critical points to extend interactivity and enables the audience to relate to the charts. Each visual element must be fastidiously woven together right into a meaningful story. Thus, this data informs the audience while actively resonating with their senses. This passive data encounter allows the audience to retain vital information for a time frame.

This text will explore the concept of narrative visualization and its uses in data communication. The exoplanet discoveries made by NASA’s Transiting Exoplanet Survey Satellite (TESS) mission will function a lens through which we will examine the narrative visuals. We may even take a look at D3, a robust JavaScript library for creating data-driven documents.

Narrative visualization is about making visually appealing charts, and taking your audience on a journey to find the information. The information is briefly introduced at first; it’s profoundly explored in the center and concludes with shedding light on the important thing insights or providing flexible exploration tools, thus forming an interactive story.

It’s a process that organizes data into a particular structure crafting a visible story as a substitute of randomly presenting facts and figures. Subsequently, the information becomes the characters in a story, and your job because the narrator is to bring these characters to life using visuals. The audience engages with the information story while drawing connections and recognizing patterns that may easily be retained in the long term.

There are three essential structures that narrative visualizations can take:

1. Writer-driven narratives: The writer provides a particular path through the information and dictates the story direction, leading the audience through the information in a structured way. Writer-driven visuals are effective in clearly communicating insights, akin to videos.
2. Reader-driven narratives: This approach gives control to the audience. It provides a more interactive experience where the audience can explore the information at their very own pace and follow their path. This might be effective in encouraging engagement and exploration. An example of that is interactive dashboards.
3. Hybrid narratives: combines elements of each author-driven and reader-driven narratives. They typically start with an author-driven introduction, followed by a reader-driven exploration section. This provides a balance between guided storytelling and interactive exploration. An example of that is Martini Glass data representation.

In our upcoming sections, we are going to use the “Martini Glass” structure, a preferred hybrid narrative, to visualise the information from NASA’s TESS mission. This structure provides an initial author-driven overview (the stem of the glass), followed by a reader-driven exploration space (the bowl of the glass). Allowing us to guide the audience through the important thing points of the information before letting them explore the information in additional depth.

In 2018, NASA launched into an exploratory journey to find exoplanets beyond our solar system by launching the Transiting Exoplanet Survey Satellite (TESS) mission.

The TESS mission has proved to be an astronomical treasure. NASA, through this mission, has amassed greater than 90 data points. These points consist of worthwhile details about each exoplanet contributing to solving a cosmic puzzle. This data includes the exoplanets’ names, their host stars and the invention 12 months, together with their physical characteristics: size, shape, eccentricity, and orbital period. These datasets encapsulate each exoplanet’s story making the TESS mission’s facts and figures unravel compelling cosmic stories.

We are going to use TESS data to create a narrative visualization that tells the story of exoplanet discoveries through the years with the flexible tool at the top for in-depth evaluation.

Scene 1: Overview of Discovered Exoplanet
The narrative begins with an outline of the exoplanets discovered by TESS from 2018 to 2023, highlighting the trends over time and comparing some characteristics with Earth ranges at high levels. This sets the stage for our story, providing context concerning the breadth and scope of the TESS mission. The primary scene breaks down into three specific visualizations designed to showcase a singular overview of the information:

• Histogram of Discoveries per 12 months: this showcases the variety of discovered exoplanets every year. The peak of every bar corresponds to the variety of discoveries. To supply an interactive experience, clicking on the bar filter the information in the opposite charts for a focused evaluation of the discoveries made in that individual 12 months.
• Scatter Plot of Equilibrium Temperature vs Orbital Eccentricity: this scatter plot provides a view of the exoplanets’ characteristics by comparing their equilibrium temperature and orbital eccentricity. The equilibrium temperature, illustrated on the x-axis, approximates the common temperature of an exoplanet. The orbital eccentricity, displayed on the y-axis, indicates how much the exoplanet’s orbit deviates from an ideal circle. Interactive elements enable users to explore the information further: hovering over a circle reveals overview of the information, while clicking transitions the user to the second scene for an in depth exploration view.
• Scatter Plot of Stellar Mass vs Radius: shifting the deal with the host stars, this visualization plots stellar mass against the radius, each represented by a circle. As with the previous visualization, interactive features allow users to explore specific planet characteristics.

Scene 2: In-depth Exploration of Individual Exoplanets
Next, we dive into the person exoplanets by clicking on them, exploring their unique characteristics, and comparing these features to ranges found on Earth. The values are presented using a series of horizontal bars describing a particular parameter and comparing the exoplanet value with an approximate corresponding Earth range.

This scene provides a better take a look at the properties that make each planet unique akin to equilibrium temperature, planetary radius, orbital semi-major axis, orbital eccentricity, and the host star’s radius and mass.

Scene 3: Interactive Exploration of TESS Data
The ultimate scene provides an interactive exploration tool that permits users to vary various comparison ranges and choose which features to check. On this scene we allowing for a personalised exploration experience.

This case study demonstrates the ability of narrative visualization in making complex data accessible and fascinating. In the subsequent section we are going to explore the implementation details.

D3.js is a javascript framework for interactive data visualizations on the net. Before we start constructing the TESS narrative visualization, let’s explore some basic functionality of D3.

Choosing Elements:

Considered one of D3’s essential features is the ‘select’ method. This lets us discover elements in an HTML document that we want to regulate. For instance:

d3.select("#visualization")

Appending and Manipulating Elements:

D3 can construct and manage SVG elements using the methods `append`, `attr`, and `style`.

• `append` introduces latest elements (circles, rectangles, etc.) into an SVG, each representing different data points.
• The `attr` and `style` adjust the attributes and properties of those elements, like their positions, sizes, and colours.

Binding Data:

Using the `data` method, D3 binds data to visual elements. This grounds its strength in creating data-driven visuals, allowing dynamic updates.

Scaling:

Scaling maps an input domain to an output range, adjusting the drawing area to your data. For example, `d3.scaleLinear()` uses a linear scaling where any given number within the input domain corresponds on to a number within the output range.

Now that we all know the fundamentals of D3, we will construct an enticing narrative using the TESS mission data (available here). For brevity, the fundamentals of the primary two scenes are discussed intimately in this text. You possibly can try the GitHub Repository for comprehensive scene implementation.

Prepare the html

Load the d3 library within the header

Then prepare a container div to attract the charts:

Scene 1: Overview of Discovered Exoplanets

Here’s how we create the primary scene:

1. The TESS data is loaded and stored in a variable using the `d3.csv` function.
2. A scatter plot represents the exoplanets discovered by TESS over time.
3. Interactivity is added, allowing users to click on specific exoplanets and navigate to Scene 2.

Load the information and call the code to attract the primary scene:

d3.csv("data/tess_confirmed_plannets.csv").then(function(myData) {
data = myData;
// Scene 1: Overview
drawScene1(myData);
});

Let’s draw a sample from the primary scene by showing the exoplanets in scatter plot, check line comments for the implementation details:

Scene 2: Detailed Exploration of Individual Exoplanets

We’ll create the second scene by following these steps:

1. Create the `drawScene2` function to make use of data from a specific exoplanet.
2. Create visual elements that showcase the person features of chosen exoplanets and compare them with Earth’s range.

The given code is a simplified version for Scene 1 and Scene 2. The entire code, with interactive elements and features, might be sourced from the linked GitHub repository.

You possibly can check the ultimate narrative final result below:

https://barqawiz.github.io/NASA_TESS_Narrative/

In conclusion, narrative visualization deviates from the monotonous data communication path and undertakes a journey. The information is presented in a structural yet appealing strategy to capture the audience’s attention. These data stories engage the audience in an individualized manner. Nonetheless, the curators of those stories can select their narrative structures deliberately for efficient data storytelling, whether author-driven, reader-driven, or hybrid narrative.

NASA’s Transiting Exoplanet Survey Satellite mission data was used as a case study to reveal narrative visualization. This TESS mission discovered exoplanets beyond our solar system with over 90 features. The hybrid Martini Glass approach is used to speak this data to the audiences. The narrative begins with an author-driven approach after which transitions to details concerning the exoplanets through a reader-driven method for interactive and personalized exploration.

Crafting a visible narrative is an art where being certain about your ultimate goal and the audience and choosing the structure of your story is crucial to the implicit meaning of your data and fascinating the audiences.

• NASA TESS mission gallery: link
• NASA exoplanet archive: link
• NASA content policy: link
• Earth fact sheet: link
• Github repo with the total code: link
• The used data after cleansing: link
• UIUC course “CS 416: Data Visualization”.

Quotation: NASA content (images, videos, audio, etc) is usually not copyrighted and will be used for educational or informational purposes with no need explicit permissions.