Every mission to Mars in a single visualization


In today’s highly connected and instantaneous world, we have access to a massive amount of information at our fingertips.

Historically, however, this has not always been the case.

Travel back in time from just 20 years ago to 2002, and you’ll notice that the vast majority of people were still waiting for the daily or evening news to help fill the information void.

In fact, for most of 2002, Google lagged in search engine market share behind Yahoo! and MSN. Meanwhile, the first incarnations of social media (MySpace, Friendster, etc.) were just beginning to go live, and not all of Facebook, YouTube, Twitter, and the iPhone existed.

Media waves so far

From time to time, the dominant form of communication is upended by new technological developments and changing societal preferences.

These transitions seem to be happening faster over time, aligning with accelerating advances in technology.

  • Proto-Media (over 50,000 years)
    Humans could only spread their message through human activity. Speech, oral tradition and hand-written text were the most common means of conveying a message.
  • Analog Media and Early Digital Media (1430-2004)
    The invention of the printing press, and later of radio, television, and the computer, opened up powerful, inexpensive, one-way forms of communication to the masses.
  • Connected media (2004-current)
    The birth of Web 2.0 and social media allows participation and content creation for everyone. A tweet, blog post or TikTok video from anyone can go viral and reach the world.

Each new wave of media has its pros and cons.

For example, Connected Media was a huge step forward in allowing everyone to be part of the conversation. On the other hand, the algorithms and the amount of content to wade through have also created a lot of downsides. To name just a few problems with the media today: filter bubbles, sensationalism, clickbait, etc.

Before we dive into what we think will be the next wave of media, let’s first break down the attributes and common issues of previous waves.

Wave Zero: Proto-Media

Before the first media wave, amplifying a message required dedication and a lifetime.

Add to that the fact that even in the year 1500, only 4% of the world’s citizens lived in cities, and you can see how difficult it would be to communicate effectively with the masses at that time.

Or, to paint a more vivid picture of what proto-media was: information could only travel at the speed of a horse.

Wave 1: Analog Media and Early Digital Media

In this first wave, new technological advances enabled large-scale communication for the first time in history.

Newspapers, books, magazines, radio, television, movies, and early websites all fit into this framework, allowing the owners of these assets to spread their message widely.

With large amounts of infrastructure needed to print books or broadcast television news programs, it required capital or connections to access it. For this reason, big business and governments were usually the gatekeepers, and ordinary citizens had limited influence.

Attribute The description
📡 News Feed One way
💰 Barriers to entry Very high
📰 Broadcast Controlled by mass media companies and the government
🏆 Incentive To expand the network and not alienate viewers or advertisers

Importantly, these media only allowed one-way communication, meaning they could deliver a message, but the general public was limited in how they could respond (i.e. a letter to editor or a phone call to a radio station).

Wave 2: Connected Media

Innovations like Web 2.0 and social media have changed the game.

From the mid-2000s, barriers to entry began to fall, and it eventually became free and easy for anyone to air their opinion online. As the internet exploded in content, sorting it out became the number one problem to solve.

For better or worse, algorithms started feeding people what they liked, so they could consume even more. The ripple effect was that everyone competing for eyeballs suddenly found themselves optimizing content to try and “win” the algorithm game to achieve virality.

Attribute The description
📡 News Feed Bidirectional
💰 Barriers to entry Very slow
📰 Broadcast Controlled by tech companies and algorithms
🏆 Incentive To cast a narrow net, to engage and mobilize a specific audience

Viral content is often engaging and interesting, but it comes with tradeoffs. Content can be made artificially appealing by sensationalizing, using clickbait, or playing with facts. It can be ultra-focused to resonate emotionally within a particular filter bubble. It can be designed to infuriate a certain group and mobilize them into action, even if it is extreme.

Despite the many benefits of connected media, we are seeing more polarization in society than ever before. Groups of people can’t identify with each other or discuss issues because they can’t even agree on basic facts.

Perhaps the most frustrating of all? Many people are unaware that they are at the bottom of their own bubble in which they only receive information that they agree with. They are unaware that there are other legitimate points of view. Everything is black and white, and gray thinking is increasingly rare.

Wave 3: Data carriers

Between 2015 and 2025, the amount of data captured, created and replicated globally will increase by 1600%.

For the first time, a significant amount of data is becoming “open source” and accessible to everyone. There have been tremendous advancements in how data is stored and verified, and even ownership of information can now be tracked on the blockchain. The media and the population are becoming more data savvy, and they are also becoming aware of the societal disadvantages arising from connected media.

As this new wave emerges, it is worth taking a closer look at some of its connecting attributes and concepts:

  • Transparency:
    Data-savvy users will begin to demand that the data be transparent and come from trusted, fact-based sources. Or if a source is not rock solid, users will demand that the limitations of the methodology or any biases be openly disclosed and discussed.
  • Verifiability and Trust:
    How do we know that the data displayed is legitimate and authentic? Platforms and media will increasingly want to prove to users that the data has been verified, tracing it back to the original source.
  • Decentralization and Web3:
    Anyone can tap into the vast amounts of public data available today, which means that reports, analyses, insights and insights can come from a growing set of actors. Web3 and decentralized registries will allow us to provide trust, attribution, accountability and even ownership of content where needed. This can cut out the middleman, which is often big tech companies, and can allow users to monetize their content more directly.
  • Data scenario
    The growing data culture and explosion of data storytelling is a key approach to making sense of large amounts of data, by combining data visualization, storytelling and powerful insights.
  • Economy of data creators:
    The democratization of data and the rise of storytelling are intersecting to create a potential new ecosystem for data storytellers. This is increasingly what we focus on at Visual Capitalist, and we encourage you to support our Kickstarter project on this. (more than 6 daysat time of publication)
  • Open ecosystem:
    Just as open source has revolutionized the software industry, we will begin to see more and more data available at scale. In some cases, the incentives can shift from keeping the data confidential to releasing it into the open so that others can use it, remix it and publish it, and attribute it to the original source.
  • Data > Reviews:
    Data media will be biased towards facts rather than opinion. It is less about experts, biases, manipulation and telling others what they should think, and more about allowing an increasingly data-savvy population to have access to the facts themselves and to develop their own nuanced opinion about them.
  • Global data standards:
    As data continues to proliferate, it will be important to codify and unify it where possible. This will lead to global standards that will make communication even easier.

Early Data Media Pioneers

The Data Media ecosystem is just starting to emerge, but here are some pioneers we like:

  • Our world in data:
    Led by economist Max Roser, OWiD does a great job of merging global economic data into one place and enabling others to remix and communicate this information effectively.
  • USA Facts:
    Founded by Steve Ballmer of Microsoft fame to be a nonpartisan source of US government data.
  • Fred:
    This tool from the Federal Reserve Bank of St. Louis is just one example of the many tools that have sprung up over the years to democratize data that was previously proprietary or difficult to access. Other similar tools have been created by the IMF, World Bank, etc.
  • Five Thirty Eight:
    FiveThirtyEight uses statistical analysis, data journalism and forecasting to cover politics, sports and other topics in a unique way.
  • Data flow :
    At FlowData, data visualization expert Nathan Yau explores a wide variety of data and visualization themes.
  • Data Journalists:
    There are incredible data reporters in publications like The Economist, The Washington Post, The New York Times and Reuters tapping into the early beginnings of what is possible. Many of these publications have also made their work on COVID-19 freely available during the pandemic, which is certainly commendable.

The growth of data journalism and the emergence of these pioneers give you a sense of the beginnings of data media, but we believe they only scratch the surface of what is possible.

What data carriers are not

In a way, it’s easier to define what Data Media is not.

Data media are not partisan pundits arguing with each other on a newscast, and they are not fake news, misinformation, or clickbait designed to generate easy clicks. Data media is not an echo chamber that only reinforces existing biases. Because the data is also less subjective, it is less susceptible to censorship as we see today.

Data isn’t perfect, but it can help change the conversations we have as a society to be more meaningful and inclusive. We hope you agree!


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