Semantic Web

The third generation of the World Wide Web
What is the semantic Web 3.0? This chain of tweets posted by Chris Dixon explains it very well:
Why Web3 matters:
  • Web1 (roughly 1990-2005) was about open protocols that were decentralized and community-governed. Most of the value accrued to the edges of the network — users and builders.
  • Web2 (roughly 2005-2020) was about siloed, centralized services run by corporations. Most of the value accrued to a handful of companies like Google, Apple, Amazon, and Facebook.
  • We are now at the beginning of the Web3 era, which combines the decentralized, community-governed ethos of Web1 with the advanced, modern functionality of Web2.
  • Web3 is the internet owned by the builders and users, orchestrated with tokens!
  • Web3 offers a new way that combines the best aspects of the previous eras. It’s very early in this movement and a great time to get involved.
Tim Berners-Lee, computer scientist and the inventor of the World Wide Web, once said:
I have a dream for the Web in which computers become capable of analyzing all the data on the web – the contents, links, and transactions between people and computers. A “Semantic Web”, which makes this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy in our daily lives will be handled by machines talking to machines. The “intelligent agents” people have touted for ages will finally materialize.
For a more complex and detailed explanation of the Semantic Web, I strongly suggest reading this article by Ontotext.
In summary, the Semantic Web is an extension of the current web that provides a standardized way to express the relationships between web pages, allowing computers to understand and respond to complex human requests based on their meaning. It was envisioned by Tim Berners-Lee, one of the inventors of the World Wide Web. In this new Web, information is well-defined to enable better cooperation between computers and people. It's structured and tagged in such a way that it can be read directly by computers and AI, helping them to perform more of the tedious work involved in finding, sharing, and combining information on the web. The ultimate goal of the Semantic Web is to make the Internet more intelligible to computers and useful to humans by setting up a universal framework that allows data to be shared and reused across applications, enterprises, and communities.
Here are some key components of the Semantic Web:
  1. 1.
    Resources and URIs: Everything in the Semantic Web is considered a resource, which can be a web page, a part of a web page, or a piece of data. Each resource is identified by a Uniform Resource Identifier (URI).
  2. 2.
    RDF (Resource Description Framework): RDF is a standard model for data interchange on the web. It has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed.
  3. 3.
    Ontologies: Ontologies define the concepts and relationships used to describe and represent an area of knowledge. Ontologies are used by people, databases, and applications that need to share domain information.
  4. 4.
    SPARQL: SPARQL is a query language for RDF. It's used to retrieve and manipulate data stored in Resource Description Framework format.
  5. 5.
    Linked Data: Linked Data is a method of publishing structured data so that it can be interlinked and become more useful through semantic queries. A great example is OriginTrail's Decentralized Knowledge Graph, where data is not only linked but also distributed and decentralized, promoting a more open and collaborative web. More details below.

OriginTrail and Web3

The Semantic Web offers an exciting opportunity to expand the way users interact with assets. Both assets, those anchored in the real world (cars, building, rare items such as an expensive bottle of whiskey, educational or vocational credentials, etc.) and those digitally native (NFTs representing digital art, gaming avatars or fungible tokens used for trading) are poised to change the way we manage, protect and increase the value of our wealth. Things we own are now converging towards becoming Web3-grade assets – assets made discoverable, verifiable and valuable using the Internet technology comprising both a semantic layer – knowledge graphs and trust layer – blockchain.
Leveraging both the groundbreaking knowledge graph and blockchain technology, OriginTrail is a neutral, inclusive ecosystem striving to deliver useful and foundational Internet technologies. The open source codebase and permissionless nature of the established OriginTrail network layers drive transparency and laissez-faire type of a market incentives that underpin security, transparency and antifragility of the system. OriginTrail is thus becoming a core component of Web3 infrastructure, also ensuring user asset sovereignty as data representing assets can only be managed by asset owners. (source)
In a recent interview with Dr. Bob Metcalfe, the Father of Ethernet, at the Knowledge Graph Conference 2022, he was asked to rate OriginTrail’s chances of success
“The weakness of it is that it’s too complicated to explain” to ordinary mortals, said Metcalfe of the technology. The OriginTrail technology appears a bit like middleware, which is a category that only tends to excite a handful of people. “Yes, and I’m one of them,” said Dr. Metcalfe.
Despite the complexity of the tech, “What they are doing is right in line with where things are going.” More importantly, he took on the advisor role because he’s learning from what OriginTrail is doing, educating himself on what new forms of value there will be in the connectivity of Web3 assets.
At this timestamp during Branimir’s presentation, the link between the Semantic Web3 and the DKG is thoroughly explained.
If you do not wish to watch the segment, here’s a summary of what Branimir said:
OriginTrail is the world’s first Decentralized Knowledge Graph, where the idea is that everybody can share this set of technologies. We can expand connectivity to wider spaces than just siloed platforms like Google and Facebook. Anybody can participate with any device, and therefore generate value for everyone. OriginTrail is a global semantic network of data that organizes humanity’s most important assets, making them discoverable, verifiable and valuable. The value exchange pays for all network effects. In a way, the original structure of the Semantic Web 3.0 envisonned by Berners-Lee comes to this synergy of knowledge graphs, and blockchains, as we have them today. If we show a very simplified architecture here, sitting on top of blockchains is the Decentralized Knowledge Graph, which enables these Web 3.0 applications. These layers of blockchains and Decentralized Knowledge Graph on the new Semantic Web 3.0 have basically covered the architecture that Tim Berners-Lee envisioned originally on the Semantic Web in a trusted sense.
The Decentralized Knowledge Graph drives network effects. We start from the notion that information is inherently valuable. For instance, all big tech companies in the world benefit a lot from the information that gets exchanged through them. A simple Google search term enriches the knowledge graph of Google and generates more value. Next time when Google is being searched for the same term, they will actually use the learnings from what you’ve done previously. The same concept of enriching a knowledge graph can be done in a decentralized manner. Taking this information, which is inherently valuable, we actually unlock the Metcalfe’s Law network effects for humanity’s most important assets.
We do that in three ways. First, we make all of these assets discoverable. We use the word asset in the widest context, so that means both physical assets, which OriginTrail has already been using in the tracking of physical assets in real world today, and digital assets, such as assets on a blockchain (NFTs for instance) or just generally data assets. Second, making assets discoverable is a very important aspect of enabling this data connectivity to happen, because without discoverability, we’re not able to make these connections. Discoverability means that all this knowledge that gets accumulated is able to connect to some other knowledge or is able to be used in some upper layer, application layer, like Professor Metcalfe beautifully put it – connectivity also permeates through all layers. Discoverability is also important in terms of bridging data silos. When we have situations where we have companies that have maintained their own data systems, like Facebook and Google, but also the traditional supply chain companies, or generally any data system, in order to bridge those, you need to have the property of discoverability. To make this bridge happen, verifiability in another important aspect. In the context of blockchains, verifiability is associated to transactions, but the meaning can be expanded to anything. The decentralized Knowledge Graph is actually a set of verifiable assertions – think of that as immutable data sets that have all been signed, and have a cryptographic fingerprint associated with them on a particular blockchain. Why is it a blockchain? Because you can always take that data set, crunch it back to its hash and compare it to the one that has been time stamped on the blockchain, and see if it has been changed. If it hasn’t, then you can you verify the integrity of this information, or that it has been immutable, but also confirm or verify the signature of whoever issued this verifiable assertion or data set. Finally, you can use it directly on the blockchain, because you can verify that whatever data comes from the DKG has a corresponding set of fingerprints on the chain that can verify that at certain point in time, it really had that shape. Therefore, verifiability comes in various forms. But why does it matter? It matters in the sense which Professor Metcalfe mentioned – the problem of fake news, which really is a problem of verifiability. Can you verify the source? Can you be sure that the information that has been shared is truthful. Obviously there is no algorithm in the world that you put some information in, and a true or false statement comes out and says this is the truth or not. But what we can do on a protocol level today is we can verify several things, that something hasn’t been changed along the way, some statement made by some organization is as it is, but also, we can verify that indeed, it comes from that organization.
Now, if we think about these assertions not as separate things, but rather interconnected things, you’re able to query them, and you’re able to formulate all kinds of answers and analytics based on verifiable data – that is the semantic, and that is what we can base our decisions on. All of this makes data valuable. Going back to Google, one of the biggest thing associated with Google searches is the SEO (Search Engine Operation) friendliness. You know how high your website ranks or shows up on the list for Google search – all this basically determines the website value. Therefore, if you are really easily discoverable through some search term, it means that your website is being clicked on a lot and it has a lot of links pointing to it. Google gives it much higher value, and it actually sorts the list according to the value. This value is calculated, among others, with also this Google PageRank algorithm. This algorithm essentially harnesses the power of network effects. So again, the Decentralized Knowledge Graph is designed to make data discoverable, verifiable and valuable. It conforms to the Metcalfe’s Law, which is basically that the value is proportional to the square of the number of entities in this interconnected network. Robert Noyce, one of the co-founders of Intel, once said that knowledge is power. When you share that knowledge, knowledge sharing is power multiplied.
With OriginTrail, you can do several things such as building high quality variable data, you can build applications on top, you can publish verifiable assertions from any system, integrate all of this data across the semantic Web 3.0 pretty seamlessly, and easily build privacy first Metaverse right outside. OriginTrail is completely open source, and it is designed to enable anybody to own their own data. Anybody can run an OriginTrail node and network, anybody can connect and publish with it, with the possibility of containing some permission information in their own subgraph and keep data private. Publishing public information is, of course there for this kind of discoverability and verifiability. What you can also do is you can discover and crowdsource high quality data sets. This is something very interesting for the field of data science, machine learning AI, because for all these great algorithms we really need lots of and very high-quality data. Finally, you can tokenize your dynamic assets. Today, the physical or digital OriginTrail DKG is already actually working on that, and there’s quite a few global leaders using it. The British Standards Institution has several applications built on top of OriginTrail, the Swiss railway companies are working on also several implementations for the last couple of years in production that are tracking supply chain parts, and with multiple partners in the European rail space. Another interesting example is the trusted factory example with SCAN Association, which is actually an association of companies such as Walmart, Home Depot, Costco, and many others for factory audits. There are also other use cases in fashion, food traceability, and others that OriginTrail is already been used for. Walmart have awarded us, and Oracle, as one of our partners, has also been traditionally in the data space as one of the original databases very interested in the semantic web and blockchain, and therefore, working together with OriginTrail. Finally, the World Economic Forum with whom we’ve been involved in a project of actually mapping and crowdsourcing very useful information on personal protective equipment, which is highly critical in this situation of pandemic. So that will be it.”

Dr. Bob Metcalfe and John G. Keogh

Dr. Bob Metcalfe, The Grandfather of network effects, joined Trace Labs’ advisory board. In the event below, they talked about knowledge graphs and the switch from Web 2.0 to the semantic Web 3.0 extensively.
Here is a great exchange between Branimir and Dr. Bob Metcalfe in the video above.
Branimir: “There’s quite a lot of algorithms that are actually built to harness the connectivity of the knowledge graph. The most famous one is the Google PageRank. If you have a link or a set of links on the web, then it’s not only used for websites – it can be used on large maps as well in several different ways but essentially what it does is it creates a notion of value based on how many links points to something but not just in terms of numbers but also in terms of ‘power’. If a major website like CNN points to some other website, since they have more ‘power’, they actually transfer part of their power or value to that website.”
Dr. Metcalfe: “This is wonderful. This beautifully makes a point that connectivity occurs in layers and you’re describing the connectivity of the knowledge graph. Above that, there are buyers and sellers who use Google to find things and so that’s a graph and it has value associated with it. This connectivity at pagerank level is yielding value at buyer and seller level so the layers of the Internet also give us a hint that there are layers of connectivity.
Branimir: “That resonates so much with me professor because when you look at OriginTrail, it is a decentralized network so we have the concept of connectivity on the network level, or physical level, and there’s the concept of connectivity on the data level, and finally on the application level as you mentioned because there’s somebody consuming and publishing all of this information and then discovering it or utilizing it.”
Dr. Metcalfe: “I’d like to reiterate the importance of what you’re doing. Metcalfe’s Law talked about the connection of machines and how valuable these PCs would be if they were connected. Then, Facebook made it all about connecting people together. What you’re working on is the connectivity of data and the value that can be derived from that.”or details on each stage, visit the link below