Data, Startups And Doing Things That Matter

Prominent voices in tech journalism are criticizing the global startup community for building software products and services that cater to the 1 percent or have zero societal value. They claim that curated shopping services are not really revolutionary; that food delivery services aren’t changing the world; and that ridesharing is nice but not exactly earth-shattering. And, clearly, building ways to sell more ads adds nothing to the global karmic bottom line.

Everything about Silicon Valley is a lie. So goes the thinking about the lack of meaningful startups.

However, in my world, I see numerous critical tools and services coming from startups that have world-changing potential. These tools and services help mere mortals wrangle data and use it to greater effect.

Data is power. Those who can wield data effectively or collect data where previously it was unavailable can fight powerful monied adversaries and force social change. We call it the “data revolution.” It’s a real thing and it will leave a tremendous positive legacy for the world.

Breaking down data

The Bellingcat Ukraine Vehicle Tracking Project, a nonprofit citizen journalism collaborative that investigates conflict zones using off-the-shelf data, geolocation and image-analysis tools, is one small example of this. They publish the results of their investigations online and grab big headlines that cause uncomfortable conversations in the corridors of power.

For instance, Bellingcat provided compelling evidence that the Syrian government had used nerve gas on its own people and that the missile that shot down Flight MH17 likely was fired from a part of the Ukraine controlled by Russian separatists.

Bellingcat was launching an effort to crowdsource sightings of Russian armor, vehicles and heavy weapons moving in and around the Ukraine. Eliot Higgins, the leader of Bellingcat, wanted to build maps that would let the public and the media see where the tanks, howitzers and rockets had been sighted. He also wanted to categorize the types of vehicles and analyze trends for sightings. The ultimate goal was to provide close to irrefutable, data-driven evidence that Russia was sending heavy arms and assistance into the Ukraine.

Higgins and his team tapped a network of contributors on the ground who risked their lives snapping pictures with smartphones of tanks and rockets all over the contested Donbas area. The Bellingcat collective also scanned videos, satellite photos and other media to find images of Russian weapons in the Ukraine within the timeframe of the conflict.

Each sighting was uploaded into Checkdesk, a new collaborative blogging platform that works as a curation and verification vehicle for data-driven observations. The team checked the sighting location and added information about type of weapon or vehicle, markings, dates and other key data.

Those who can wield data effectively or collect data where previously it was unavailable can fight powerful monied adversaries and force social change.

After the sighting and images had met the criteria set by Bellingcat and knowledgeable moderators for accuracy, Higgins and his collaborators pushed the pictures and details about each of the sightings into Silk. For Bellingcat, Silk offered unique data publishing and storytelling capabilities — the ability to mix structured data, dynamic visualizations, text, videos and audio easily using powerful a graph database managed through a simple GUI.

Once published in Silk, Bellingcat’s data then populated mobile-friendly maps and charts. Any of the charts could be used as embeds by bloggers or media companies. Each sighting has its own webpage and its own SEO value, making the data on that page easy to find and highly visible. Anyone, too, can see the live data and reconfigure it into different visualization types for republishing. Any user — not just an editor — could convert a map of weapons sightings into a chart showing the percentage breakdowns of weapon types and republish that view in their own site.

After steadily collecting sightings for a month, Bellingcat launched the Bellingcat Ukraine Vehicles Tracking Project. The effect was electric. Over a dozen mainstream media sites embedded the maps and linked to the project. Bulletin boards all around the Baltic Region lit up with commentary driven by the revelations and images.

The Supreme Allied Commander of NATO, James Breedlove, tweeted and posted the Bellingcat Vehicles project on Facebook, citing it as a model of open source intelligence gathering. Millions of people saw the maps and sighting data.

The project cost? Zero. No one wrote any code. All the tools used to build the Bellingcat Vehicles database are free and require no special expertise. The data, though, is better than anything else out there – even better than satellite data because snapshots at ground level reveal information inaccessible from the sky. (No, there isn’t an easy way to update Google Street View in a conflict zone.)

Bellingcat’s data was not only part of the dialogue but also became part of the historical record, a transparent and searchable repository of contested history. That’s the data revolution and there are dozens of venture-backed startups in New York and Silicon Valley that are ensuring its success.

Checkdesk is a tool that shows people how to democratize data. Making it easier, cheaper and faster to analyze and publish data for public good, not just profits. Tableau (now a publicly traded company) offers a free public version that is heavily used for data analysis and public advocacy.

Import.io and Kimono Labs make it incredibly easy to harvest data from the public web and put it in a spreadsheet. NationBuilder simplifies and democratizes the formerly complex task of marshalling data resources for political or advocacy campaigns. All of these tools are making a big impact and being used by journalists, NGOs, citizen groups and more.

Backing the data revolution

Why are VCs backing companies in the data revolution? Because it turns out that businesses have the same need to better collect, organize, visualize and publish data. Marketing teams inside companies large and small are using DIY data tools to build content marketing efforts and internal content repositories. Sales and analytics teams use lightweight data tools such as DataHero (which just raised $6.2 million) to let anyone mix and match data sources in a dashboard.

By making data searchable, accessible, and easy to publish or visualize, we move from the realm of the perceived, the viewed, and the written to the realm of facts.

This helps non-techies map prospects, analyze sales numbers, and gain insights into trends. To this end, tools are being used inside of many large businesses by teams that want to harness the power of data but don’t want to learn how to build visualizations, manage databases or wrangle code. Government organizations, too, are paying significant dollars to support data tools that help them fulfill transparency requirements.

What’s more, these types of data tools are among the fastest-growing segments in SaaS. The quant-focused venture investor Tomas Tunguz found in research that the SaaS “…startups are growing faster than ever before. Publicly traded SaaS companies founded from 2008 through 2014 needed 50% less time to reach $50M than their counterparts founded between 1998 and 2005.” Tunguz also found growth is accelerating with newer SaaS companies hitting the $50 million mark even sooner.

There are now dozens of startups in the data revolution space, and they aim to follow in the footsteps of Google, Twitter, YouTube and Facebook. Those big four democratized publishing and made information more accessible. The results are self-evident. Social media and freely accessible information both documented and fueled the Arab Spring, Maidan in the Ukraine and many other movements.

These social and search giants were all once startups before growing and getting the scale needed to change the world. The next wave will go even further. By making data searchable, accessible, and easy to publish or visualize, we move from the realm of the perceived, the viewed, and the written to the realm of facts.

This is a powerful transition. No doubt, some unicorns will emerge in the data revolution (Tableau has already hit that mark).

Data and information is valuable and more perfect information is significantly more valuable. The transition is in the initial stages of gathering momentum. When we look back in 10 years, we will see that projects like Bellingcat Vehicles are the early indicators for the next big shift in how everyone uses technology to marshall the power of data. Startups are making this happen right now. It’s just not as obvious as ordering a pizza on your smartphone…yet.