Truly digital data, why does it matter?

Reading time: 4 minutes

In this article, we explain the difference between truly digital data — the kind you can get from aviowiki — and other types of data transmitted in digital format, and why such a difference matters.

Truly Digital Data is data that is collected, stored and delivered in a fully machine-understandable notation.

Our world is filled with truly digital data, but the aviation industry acts exceptionally.

So welcome aviowiki! A program born to bring digital aviation data to the masses. But, why do aviators and humans think that this is so important?

Digitization is the primary enabler of integration and automation. You cannot make two pieces of software talk with one another if they cannot exchange data in a common format, they must communicate too!

Making data truly digital

Merely exchanging information in electronic format like an email or a text message does not mean we are exchanging truly digital data. Instead, we humans must write such data in a language understood by these high-power machines, which can exploit the data to render decisions.

On a positive note, when machines can understand data, that data can easily be translated into human languages. But the inverse is much more complicated. For example, in computer language, you may represent that an airport is open 24/7 by writing:

  "airport_code": "EGSS",
  "always_open": true

A piece of software could take the code-language above and formulate a sentence in any human language by spitting out words based on the digital information that we wrote about this airport in a computer-friendly language.

For instance, the computer would spit out “the airport EGSS is always open,” but if always_open was set to false, the computer would spew that “the airport EGSS is not always open.

The inverse is much more complicated. If one asks 10 different people the same question for the same airport, “when is the airport open?” we would certainly receive different answers, with effectively the same meaning:

  • “Always”
  • “24 hours a day”
  • “Every day at any time”
  • “All the times”
  • “H24”
  • “24/7”

Fine. This suffices if only a human needs to understand, but a machine will meet substantial difficulty when comprehending, or attempting to comprehend this non-machine language. Because such textual information is served by API or spreadsheet, this information does not constitute truly digital data because a piece of software would have trouble making a decision with this information!

Why does it matter?

The main advantage of possessing truly digital data is not to display it to a human, but to enable automation in the human’s processes. With the digital representation of the opening hours that we gave, a piece of software can easily say if it is safe to plan a flight to airport EGSS at a certain time, because it knows that the airport is open at all times.

At aviowiki, we believe that repetitive tasks performed by humans are boring and undermine the safety of the aviation industry. So, we must digitize manual processes to enable pilots, dispatchers, ground crew, engineers, air traffic controllers, and everyone involved in the preparation and execution of a flight, to put their brain powers only into decisions that require the creativity and problem-solving skills unique to humans.

Truly Digital Data is the key enabler of digital processes.

If you are interested in learning more about how digital airport data can support your business, get in touch! There’s always a digital solution to a human problem.

We welcome your comments on LinkedIn and Twitter using the hashtags #aviowiki or mentioning @aviowiki.

In this article, we purposely omit to explain how Natural Language Processing is capable of reading a text and extract information from it. This process is doable, as much as Siri can understand your sentences, however, we believe that encoding data properly at the source is a much better exercise than writing some text for machines to understand it through a costly process. If you are interested in discovering more about this topic, we suggest you start from the excellent Wikipedia article on Natural Language Processing.

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