5 Megatrends Fueling the Rise of Data Storytelling
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5 Megatrends Fueling the Rise of Data Storytelling

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Infographic explaining the Rise of Data Storytelling

Infographic: The Rise of Data Storytelling

Humanity is creating more data than ever before, and more of that data is publicly accessible.

While “data is the new oil” has almost become a cliché, the impact that data abundance is having on the world is undeniable. All of the world’s most valuable companies are heavily reliant on data for their continued success. Even oil giant Saudi Aramco, the world’s most valuable company, runs a 6,000 m² data center, and is partnering with Google Cloud.

In a world where nearly everything is quantified, communicating insights from that data becomes a massive opportunity. This is where data storytelling comes in. In simple terms, it’s the difference between simply making a chart, and actually explaining what it means, why it’s important, and how it fits into the broader context. This style of data-driven communication is cropping up everywhere, from newsrooms to corporate communications.

Here, we examine five megatrends fueling the rise of data storytelling.

① Information Overload

It’s estimated that between 2015 and 2025, the world will see a 16-fold increase in data.

  • The bad news: The rising tide of information is growing faster than our ability to harness it
  • The good news: This growing universe of data holds the promise of more insight, if properly utilized

Thankfully, data storytelling is an emerging field that thrives on information abundance.

As our society and economy grow more complex, more high-quality, actionable information is critical for today’s decision makers.

② Declining Trust in Media

Trust in news media has been declining for decades, and in many countries around the world, the majority of people don’t feel that media is a trustworthy source of information.

Trust in social media is similarly shaky. Only one-third of people surveyed around the world believe that social media is a trustworthy source of information. As well, a recent poll found that 75% of U.S. adults felt that political views were likely being censored by social media platforms.

The mass media ecosystem as it currently exists is facing a crisis of confidence. When a system is no longer adequately serving the needs of its users, that system is ripe for disruption.

③ Winner-Take-All Dynamics

This information abundance should be propelling humankind forward, but more often than not, valuable insights are lost in the noise—either poorly presented or pushed to the margins by clickbait and other distractions.

Today, most of us rely on algorithms and aggregators to deliver information to us. Over time, those systems become very good at feeding us information that is generally what we’re looking for. The downside, however, is that engagement-driven algorithms reward only the most compelling narratives. The handful of stories you see are the result of fierce, darwinistic competition on platforms like Twitter or Medium.

This hyper-competitive environment is part of the reason there are so many problems with media today—clickbait and tabloidization being two prominent examples.

Data storytelling takes potentially dry, complex topics and makes them more accessible, compelling, and more likely to win the battle for people’s attention.

④ Moving Beyond Text

Many of our existing systems look the way they do in part because of past technological limitations.

Search engines, for example, are still largely driven by text-based considerations. This makes sense as the early internet was essentially a collection of pages with text and hyperlinks.

Today, search engines are much better taking other forms of information into consideration, and technological advancements are breaking new ground in analyzing video and data visualizations. Advancements in AI could soon allow users to search for visualizations in ways that don’t even involve text keywords.

In a future where searching for information in a visual format is as intuitive as a Google search today, the utility and reach of data storytelling will increase dramatically.

⑤ Democratization of Data Storytelling

Even as the number of people with professional credentials in data analytics, data science, and other similar professions is on the rise, it’s never been easier for laypersons to create and publish high quality visualizations.

Free tools which are usable on almost any device have broken down barriers of access for millions of people around the world. There is now a universe of resources for people and organizations looking to convert data into a compelling visual format.

Below is a shortlist of data storytelling resources ranging from the intuitive design tools to powerful coding language libraries:

Resources for getting started   
Visualization selectionData Viz ProjectFrom Data to VizStorytelling With Data
Color selectionAdobe Color CCPalettonColors on the Web
Beginner friendlyInfogramPiktochartVenngage
Bringing data to life   
ClassicMicrosoft ExcelAdobe Creative SuiteGoogle Data Studio
BI-focusedPowerBITableauDomo
Web appsRAW GraphsFlourishDatawrapper
Powerful, specialized resources   
JavaScript librariesd3.jsChart.jsHighCharts
MappingArcGisMapBoxPolymaps
Programming languagesRPythonMatlab

Of course there are many more resources out there, and we’ll be covering this more comprehensively in the future.

The Last Mile

The concept of “the last mile” is typically associated with e-commerce. Fulfillment can be centralized in massive hubs and delivery can be optimized with uniform trucks and precise routes, but neighborhoods and residences refuse to conform to rigid standards. The last mile is where the orderly world of logistics fragments into randomness, making this leg of the journey the thorniest problem for companies like Amazon to solve.

This last mile analogy lends itself to communication as well. Analytics and datasets can be polished and made publicly accessible, but the real world is messy. Humans are unpredictable, each with their own style of learning and varying levels of data literacy.

Also, unlike e-commerce—which begins with a defined request—insight comes in unexpected flashes. Those moments of serendipity need the right conditions to occur, and the fact of the matter is, most sources of high quality information (databases, white papers, reports, etc.) are only accessed by the small number of people who conduct research for a living.

This is the great opportunity presented by data storytelling. High quality information is distilled into a form that is more digestible, memorable, and sharable, allowing more people to benefit from this era of information abundance.

Put simply: data storytelling bridges the gap between under-utilized knowledge and the growing number of people who are striving to separate the signal from the noise.

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Misc

Visualizing Two Decades of Reported Hate Crimes in the U.S.

Hate crimes across the U.S. have been on the rise since 2014. Here’s a look at the most common types of offenses over the years.

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Two Decades of Hate Crimes in the U.S.

Visualizing Two Decades of Reported Hate Crimes in the U.S.

Across the U.S., thousands of hate crimes are committed each year, with many different motivating biases.

In 2020 alone, more than 10,000 unique hate crime incidents were reported to the Federal Bureau of Investigation (FBI)—and it’s likely that thousands more were committed that didn’t get reported to law enforcement.

What are the most commonly reported motivating biases, and how have hate crime rates evolved over the years? This graphic uses data from the FBI to visualize two decades of reported hate crime incidents across America.

What is Considered a Hate Crime?

Before diving in, it’s important to determine what constitutes a hate crime.

According to the U.S. Department of Justice, a hate crime is a crime that’s “committed on the basis of the victim’s perceived or actual race, color, religion, national origin, sexual orientation, gender, gender identity, or disability.”

These types of crimes are a threat to society, as they have a broader impact on communities than other types of crimes do. This is because hate crimes can foster fear and intimidate large groups of people or marginalized communities, making them feel unwelcome, unsafe, or othered.

Hate Crimes on the Rise

Hate crimes have been rising across the U.S. in nearly every year since 2014. By 2020, reported crimes across America reached record-level highs not seen in over two decades.

YearNumber of Reported Incidents% Change (y-o-y)
2001973018.4%
20027485-23.1%
200375450.8%
200476851.9%
20057411-3.6%
200677154.1%
20077625-1.2%
200880395.4%
20096613-17.7%
201066330.3%
20116299-5.0%
201265944.7%
20136044-8.3%
20145599-7.4%
201558714.9%
201662766.9%
2017732116.7%
20187170-2.1%
2019789210.1%
20201029930.5%

And sadly, these figures are likely a vast undercount. Law enforcement submit this data to the FBI of their own volition, and in 2020, thousands of agencies did not submit their crime statistics.

Race-Related Hate Crimes are Most Common

Historically, the most reported hate crimes in the U.S. are related to race. In 2020, about 66% of incidents were motivated by discrimination against the victim’s race or ethnicity.

Type of BiasTotal Number of Crimes (2020)% of Total
Race/Ethnicity679366.0%
Religion162615.8%
Sexual Orientation131112.7%
Other5695.5%
Total10299--

While race is the most commonly reported hate crime, incidents related to gender and gender identity are on the rise—in 2020, there was a 9% increase in gender-related incidents, and a 34% increase in gender identity-related incidents, compared to 2019 figures.

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Science

Visualizing the Relationship Between Cancer and Lifespan

New research links mutation rates and lifespan. We visualize the data supporting this new framework for understanding cancer.

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Cancer and lifespan

A Newfound Link Between Cancer and Aging?

A new study in 2022 reveals a thought-provoking relationship between how long animals live and how quickly their genetic codes mutate.

Cancer is a product of time and mutations, and so researchers investigated its onset and impact within 16 unique mammals. A new perspective on DNA mutation broadens our understanding of aging and cancer development—and how we might be able to control it.

Mutations, Aging, and Cancer: A Primer

Cancer is the uncontrolled growth of cells. It is not a pathogen that infects the body, but a normal body process gone wrong.

Cells divide and multiply in our bodies all the time. Sometimes, during DNA replication, tiny mistakes (called mutations) appear randomly within the genetic code. Our bodies have mechanisms to correct these errors, and for much of our youth we remain strong and healthy as a result of these corrective measures.

However, these protections weaken as we age. Developing cancer becomes more likely as mutations slip past our defenses and continue to multiply. The longer we live, the more mutations we carry, and the likelihood of them manifesting into cancer increases.

A Biological Conundrum

Since mutations can occur randomly, biologists expect larger lifeforms (those with more cells) to have greater chances of developing cancer than smaller lifeforms.

Strangely, no association exists.

It is one of biology’s biggest mysteries as to why massive creatures like whales or elephants rarely seem to experience cancer. This is called Peto’s Paradox. Even stranger: some smaller creatures, like the naked mole rat, are completely resistant to cancer.

This phenomenon motivates researchers to look into the genetics of naked mole rats and whales. And while we’ve discovered that special genetic bonuses (like extra tumor-suppressing genes) benefit these creatures, a pattern for cancer rates across all other species is still poorly understood.

Cancer May Be Closely Associated with Lifespan

Researchers at the Wellcome Sanger Institute report the first study to look at how mutation rates compare with animal lifespans.

Mutation rates are simply the speed at which species beget mutations. Mammals with shorter lifespans have average mutation rates that are very fast. A mouse undergoes nearly 800 mutations in each of its four short years on Earth. Mammals with longer lifespans have average mutation rates that are much slower. In humans (average lifespan of roughly 84 years), it comes to fewer than 50 mutations per year.

The study also compares the number of mutations at time of death with other traits, like body mass and lifespan. For example, a giraffe has roughly 40,000 times more cells than a mouse. Or a human lives 90 times longer than a mouse. What surprised researchers was that the number of mutations at time of death differed only by a factor of three.

Such small differentiation suggests there may be a total number of mutations a species can collect before it dies. Since the mammals reached this number at different speeds, finding ways to control the rate of mutations may help stall cancer development, set back aging, and prolong life.

The Future of Cancer Research

The findings in this study ignite new questions for understanding cancer.

Confirming that mutation rate and lifespan are strongly correlated needs comparison to lifeforms beyond mammals, like fishes, birds, and even plants.

It will also be necessary to understand what factors control mutation rates. The answer to this likely lies within the complexities of DNA. Geneticists and oncologists are continuing to investigate genetic curiosities like tumor-suppressing genes and how they might impact mutation rates.

Aging is likely to be a confluence of many issues, like epigenetic changes or telomere shortening, but if mutations are involved then there may be hopes of slowing genetic damage—or even reversing it.

While just a first step, linking mutation rates to lifespan is a reframing of our understanding of cancer development, and it may open doors to new strategies and therapies for treating cancer or taming the number of health-related concerns that come with aging.

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