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4 Simple Steps Enigma Took to Turn Public Data into Insight

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There is a nearly endless supply of open data ready for businesses and nonprofits to use. The challenge is that creating something useful with that data is not always easy. Open data comes in a variety of formats and doesn’t always make sense, especially when you’re trying to analyze data in a historical context.

But some companies are cracking the code with the help of location intelligence.

Last month, Enigma Labs launched the world’s first Sanctions Tracker, a website that visualizes and contextualizes changes to the US sanctions program. Imposing sanctions is an integral function of US foreign policy—and one that is driven heavily by executive action.

Enigma’s aim was to provide transparency into not only how the government relies on sanctions to shape policy, but how President Trump’s actions compare with those of presidents past.

Enigma is an operational data management and intelligence company. They work to empower people to interpret and improve the world around them. They deliver on that ambitious goal by placing data into the context of the real world and making it connected, open, and actionable.

Like lots of open data (and big data in general), sanctions data was only available in a raw format, which did not allow for interpretation, analysis, or contextualization.

Enigma applied the 4-step Location Intelligence process to take thousands of data points, enrich them, visualize them, analyse them, and enable users to take action by exploring how sanctions have evolved based on geography, administration, and relation to geopolitical events. They uncovered some interesting insights:

  • Sanctions programs for specific countries are global in nature. For example, the North Korea sanctions programs includes sanctions for entities in multiple countries around the world.
  • There is an interesting intersection of programs in specific localities. For example, Moscow currently has sanctions from 4 out of 5 of the programs depicted.
  • A number of sanctioned entities have addresses within the United States. People wouldn’t typically think that the Iran or Terrorism sanctions programs would include entities within the United States.

If you’re working with a large dataset and want to turn it into something useful, read below to see how Enigma applied location intelligence to their challenge:

Step 1: They got the data ready.

The Office of Foreign Assets Control (OFAC) publishes a wealth of historical sanctions records dating back to 1994. Unfortunately, they aren’t published in a format ready for analysis.

Like lots of open data, the OFAC data comes in giant blocks of text that must be parsed for unique identifiers like place of birth, passport & national id number, aliases, and addresses, which in turn must be cleanly formatted, geocoded, and deduplicated.

Enigma then aggregated the 69 sanctions programs into 33 more general categories to more cleanly visualize the larger historical trends at work.

Key to their success was working with subject matter experts to make sense of historical data. For example, OFAC has a list of current sanctions program but does not provide a list of historical ones. Enigma validated their data cleaning each step of the way with a subject matter expert to make sure they were making correct decisions.

Step 2: They visualized the data on a map.

Sanctions data had never been visualized spatially, though sanctions and compliance experts all recognize the global nature of sanctions programs.

Sanctions Tracker Map

It became clear that in order to derive real insight from this dataset, Enigma had to take a spatial approach to visualizing the data.

The visualization they chose shows 5 sanctions program over the past 23 years, each labeled with a distinct color on a dark matter basemap. This clearly shows the networked nature of sanctioned entities and the global nature of the sanctions program.

Step 3: They analyzed the data spatially.

Enigma conducted plenty of non-spatial analyses on their data, but some of the key findings were only apparent looking at the data through a spatial lens.

Enigma was looking at changes in a few critical programs over time. The map was key to demonstrating trends in geographic dispersion of sanctions and the time-based map makes very clear the growth in the size of the sanctions list over the past 20 years. The insights are endless, but a few key ones that popped out:

  • The North Korean and Iranian sanctions programs are truly global in nature. They include entities on multiple continents.
  • There is a visible shift in focus of the narcotics trafficking sanctions program from Colombia to Central America and Mexico.
  • You can see a sudden onset of the Russian sanctions program following the annexation of Crimea.

Just looking at this dataset through a rows and columns view or with a traditional BI tool wouldn’t have shown these spatial findings.

Step 4: They took action.

Enigma took the visualization they had created and made it accessible so that the public can stay informed about changes to sanctions programs. They now have access to sanctions data that is much more approachable and can better understand sanctioned entities in the context of their connections/relationships to the real world.

Sanctions are a huge part of our foreign policy. This data empowers those people working with the current administration to make better foreign policy decisions by showing how geopolitical events correlate with sanctions and how the actions of the current administration compare with those of previous administrations.

What could you do with old open data? CARTO encourages you to use Enigma’s Sanction Tracker as a prime example for the potential of taking your data and transforming it into real insight and outcomes. Enigma offers thousands of datasets, including this one, for free, so take a look and get started!


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