In a world where AI is making computers more brain-like, it's time to question our outdated data storage methods. Traditional databases rely on structured silos of information, but our brains don’t work that way – they’re masters of improvisation, piecing together unstructured facts in real-time. This article challenges the status quo, proposing a shift to eVaults and a Web 3.0 Data Space where data is stored in its most natural form, just like in our minds. Could this human-inspired approach be the key to fully leveraging AI and information systems' potential? Dive in to find out.
The Illusion of Structured Information
We’ve all gotten used to the idea that in our modern world, information lives in neatly structured databases. Want to know when a house was built? Check the cadastral database. Need to confirm its color? Pop into the municipal records. It all feels quite normal and natural to us.
The surprise is: our brains don’t work that way at all. There’s no neatly organized database in our heads, not even close. Instead, our brain is a master improviser, constantly piecing together information from random facts.
The surprise is: our brains don’t work that way at all. There’s no neatly organized database in our heads, not even close. Instead, our brain is a master improviser, constantly piecing together information from random facts.
The Kettle Test: How We Really Process Information
Let’s say you’re about to make tea and wonder if the kettle is hot. You don’t have a mental database tracking the kettle’s temperature. But you do recall that five minutes ago, as you passed the kitchen, you noticed the heating light was on. From this little tidbit, your brain concludes the kettle probably just boiled.
Color Confusion: Why Relying on Databases Can Mislead
Or consider the color of your parents’ house. If someone asks you about it, you won’t be diving into a municipal database. But you do remember two facts: last summer, it was red, and two weeks ago, you helped your parents order green paint for the facade online. From these, you deduce the house is likely green by now.
Oddly enough, the official municipal database still insists the house is red. And if you check the real estate agent’s or insurer’s records, they’ll tell you it’s blue – just like it was when it was bought ten years ago.
Oddly enough, the official municipal database still insists the house is red. And if you check the real estate agent’s or insurer’s records, they’ll tell you it’s blue – just like it was when it was bought ten years ago.
Connecting the Dots: How We Make Sense of the World
So, every time our brain "connects the dots," it pieces together the information we need from a jumble of random, unstructured facts. For instance, spotting the kettle’s heating light might lead you to assume that your wife also wanted tea (since no one else is home—another clue), and you cheerfully invite her to join you. These mental "calculations" happen in our heads all the time. Our brain effortlessly pulls the right facts from memory, even if years have passed and the events are miles apart in context.
A New Role for AI: Learning from Human Thought
If our brain can pull off these mental gymnastics, surely modern AI can too. Maybe it’s time to rethink how we build information systems, the internet, and especially, databases. Why bother storing information about a house in dozens of different databases (cadastral, municipal, fire department, architecture, insurance, energy, etc.) if the data is anyway often inconsistent, outdated, or just plain wrong? Wouldn't it make more sense if the house had its own server – an "eVault" – where all organizations store their data (facts). Instead of each maintaining its own separate databases, they could simply work with a single, complete and original data. To make it interchangeable, every element of information from any stakeholder will be recorded in a form of “linked data”, invented by the father of the Web Sir Tim Berners-Lee.
The eVault Concept: Storing Information Where It Belongs
Think of it this way about your house data: the cadastral office logs the cadastral passport to it, the municipality updates the address, the painter files a report on the new facade color, the solar panel manufacturer uploads data on electricity generation, the water supplier tracks consumption, the fire inspector notes the safety inspection, the appraiser enters their valuation, Google adds Street View photos, the electronic lock records every opening and closing, and the homeowner jots down notes on minor repairs. They all input their data in whatever format suits them, without stressing over structure, formats, or inconsistencies.
When you need to find something out – like the wall color, for instance – any AI service processes all these raw facts and comes to a conclusion, just like you came to about your parents house above. And since there’s just one eVault with original data, not scattered copies, you can have as many AI algorithms as you like to analyze it. If one gets it wrong, another will get it right. This competition among AIs working off the same data will quickly push the quality of their conclusions to heights unimaginable with the current systems.
When you need to find something out – like the wall color, for instance – any AI service processes all these raw facts and comes to a conclusion, just like you came to about your parents house above. And since there’s just one eVault with original data, not scattered copies, you can have as many AI algorithms as you like to analyze it. If one gets it wrong, another will get it right. This competition among AIs working off the same data will quickly push the quality of their conclusions to heights unimaginable with the current systems.
Web 3.0 Data Space (W3DS): Redefining Data Storage for the Future
So, forget about a single, neatly organized database on the house’s eVault where "reliable" details like wall color or roofing material are stored. Instead, you’d have a collection of simple, straightforward facts: "On December 15, the owner’s friend mentioned in an email that the facade needed repairs", "On January 23, facade paint was purchased", "On February 15, the painting crew was paid". In Linked Data terms, these "facts" are known as "triples."
Every time you need information, it would be calculated afresh based on all the known facts about the house, recorded in these triples (yet caching the results is an option). This is how we envision the world of W3DS, tackling the issues of data formats and inconsistencies from various sources head-on.
Every time you need information, it would be calculated afresh based on all the known facts about the house, recorded in these triples (yet caching the results is an option). This is how we envision the world of W3DS, tackling the issues of data formats and inconsistencies from various sources head-on.
Why This Approach is More Natural Than It Seems
Does it sound wild and wildly inefficient? In reality, this approach might be far more natural than you think – we already use it every day. This is how humans process information. And now, it’s how computers are starting to process it too.
Final Thoughts: Adopting eVaults and AI for W3DS
Data should be stored right where it belongs. In our example, that means on the eVault server of the house itself.
This idea was first articulated by Sir Tim Berners-Lee, and our Web 3.0 Data Space concept is simply the next generation of his “Solid PODs”.
So, forget those outdated databases – the data will live in the house itself (in our example), separated from dozens of platforms. This is the Web 3.0 Data Space.
This idea was first articulated by Sir Tim Berners-Lee, and our Web 3.0 Data Space concept is simply the next generation of his “Solid PODs”.
So, forget those outdated databases – the data will live in the house itself (in our example), separated from dozens of platforms. This is the Web 3.0 Data Space.