.

Periods of crisis create a greater need for transparency. In the age of Open Data, this observation is more true now that everyone can access massive amounts of data to help make better decisions. 

We all would like to know more about the impact of a stimulus policy on public health issues. For example, there are so many questions we ask ourselves every day in the age of COVID-19 — how is the vaccination campaign evolving? How many new contaminations per day? Are the intensive care units saturated?

The goal of Open Data is to put public data into the hands of citizens, which ultimately will improve our functioning democracy. In the U.S, the OPEN Government Data Act requires federal agencies to publish their information online as open data, using standardized, machine-readable data formats, with their metadata included in the Data.gov catalog. However, the idea of “data-for-all” is still a long way off.

Open data… for whom? 

The term Open Data refers to data made available to everyone by a government body. For public offices, the opening of data makes it possible to engage citizens in political life. A rich legislative framework has been put in place to institutionalize the publication of this data.

Yet, data must not simply be available and accessible, but must also be able to be reused by anyone. This implies a particular legal status and also technical specificities. When data is normalized to facilitate integration with other data sets, we are now talking about interoperability.

Interoperability is crucial for Open Data, but it concerns users who have the technical skills to manipulate the data tables. For the general public, however, this criterion has only a limited impact and for the uninitiated this all still depends on the goodwill of data experts. 

A matter of experts?  

No offense to tech lovers, but the right to  public information does not date from the digital revolution. At the birth of the United States, Thomas Jefferson wrote within the Declaration of Independence that “governments are instituted among men, deriving their just powers from the consent of the governed.” It is the responsibility of government bodies and public research institutes to keep the interested public informed.

So is Open Data really a revolution? Those who usually consult this public data are experts in their fields: economics, law, environmental sciences or public health. The big challenge is helping all citizens understand the data. For this, digital tools are an invaluable help. Governments have the responsibility to make information hidden in the jungles of tables and graphs immediately accessible. In the U.S., one such challenge is to inform the public about the evolution of the pandemic in an accessible manner. We’re now living in a world where the data that connects to public affairs needs to be accessible to more than just the experts.

The challenge of shared information 

Does the average citizen need an avalanche of statistics, however interesting they may be? Some may reason that as long as experts and decision-makers have access to the data, then everyone is in good hands. Others may believe that artificial intelligence will soon exempt us from the tedious exercise of interpretation. For instance, smart cities and their connected objects already promise algorithmic self-regulation; smart traffic lights will lessen traffic; and  autonomous cars will direct motorists to the least congested roads. The monotonous voice of on-board GPS will soon be a bad memory. 

It may be tempting to envision this technocratic utopia where algorithms and experts hold the reins of society. However, we choose to bet on democracy, where citizens, well-informed by Open Data, will vote for the common good. Data alone cannot drive the best decisions, but it is a compass that helps guide citizens towards the most just political choices. It is important to put it in everyone's hands. 

Charles Miglietti is the CEO and co-founder of modern BI platform Toucan Toco, which is trusted by more than 500 global clients to build insight culture at scale. He was previously an R&D engineer at Apple and a software engineer at Withings.

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