Our world is filled with truly digital data, but the aviation industry acts exceptionally.
So welcome aviowiki! A company 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. This is very similar to two persons trying to communicate with one another: they need to be speaking the same language!
Making data truly digital
Merely exchanging information in electronic formats, like an email or a text message, does not mean we are exchanging digital data. “Digital” is more about how the data is written than about how it is processed or transmitted. We can call it Digital when the data itself is written in a language that can be understood by computers, which can then exploit the data to render decisions.
Don’t be scared though, this doesn’t mean that humans cannot easily make sense of digital data! When machines can understand data, that data can easily be translated into human language, and in any of our thousands of languages and dialects! 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 persons 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. Just because such textual information is served via API or spreadsheet, it doesn’t automatically get the qualification of “digital”. This is simply because a piece of software would have trouble making a decision with this information!
Why does it matter?
The main advantage in using truly digital data is not to display it to a human (although this can easily be done), but to enable automation in the 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’s power only into decisions that require the creativity and problem-solving skills unique to humans.
In short, digitising the industry brings about automation. Automation releases humans from repetitive tasks with little value while putting them in the centre of managing processes and exceptions.
Truly Digital Data is the key enabler of automated 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. Natural Language Processing is also not an exact science, so might not entirely fit the bill for Aviation and its stringent quality and safety standards. If you are interested in discovering more about this topic, we suggest you start with the excellent Wikipedia article on Natural Language Processing.