Why Semantic web is important to business?

The “semantic Web” is hugely important to tomorrow’s business.

But what is it? And what does it mean for your business?
“Semantic” is the latest buzzword to hit the online world. It’s come to mean everything and nothing.

From semantic search to the semantic Web; and from semantic marketing to semantic technologies, it seems like everyone wants to ride the semantic train.

So What?

It marks the transition into a new phase of the Web, where we stop searching and start finding.

In other words, we discover not just the information that matches the keywords we search for, but the information that we really wanted to find. Information directly related in context, not just in keywords.

This is exactly what is happening with Google GOOG -0.46%’s semantic search, which finds content in direct response to the intent of our search query. It uses contextual signals to understand what we really mean when we type into Google’s search box, or talk to a virtual assistant, such as Siri.

New Products; New Services
The semantic Web is far more open, transparent and personalized. It’s being transformed into a place where the same content means different things to different people.

A search for “pizza” from my desktop at 9am will generate informational links and pizza recipes, yet the same search carried out on my smartphone at 8pm will pop up ads for pizza restaurants near my location.

Google looks not just at the content in its search index, but also at who is asking the question, where, and when. In a sense, it matches detailed knowledge of the searcher’s profile with an understanding of the search, in order to deliver the best possible answer.

Tomorrow’s businesses need to take advantage of semantic search.
The Age Of Checkbox Marketing Is Over
The semantic Web requires an entirely different type of thinking about online marketing content. Information placed online needs to be capable of generating some kind of interaction with the online population, which means “marketing deliverables” have to contain real value, not just keywords.

In the semantic Web, there’s no such thing as inert data: Information always means something. It becomes a signal that acquires relevance—in the right context. (I’ll explain how and why, in the next two sections.)

Similarly, products and services can no longer take the convenient approach of “one size fits all.” An online population that’s becoming accustomed to total personalization won’t take kindly to a company that treats customers as faceless numbers in a crowd.

Semantic Search Is All About Big Data
As the Web grows in size and the amount of data on it increases, the only way to make use of it is to contextualize it.

That means it can be used in a more personalized, relevant way. The moment you have masses of anything, you can find patterns emerging, which often release new insights.

The entire Big Data movement is based on this. Semantic search is no exception to the rule. The only difference is that, instead of a business analyzing data from operations, we have Google search being transformed into the world’s biggest database, categorizing the Web itself.

So how’s it achieved? How does the Web acquire greater meaning than just what’s contained in the information on it?
The Answer Lies In Hyperconnectivity
For example, if we could somehow acquire all of the world’s knowledge, it wouldn’t make us smarter. It would just make us more knowledgeable. That’s exactly how search worked before semantics came along.

In order for us to become smarter, we somehow need to understand the meaning of information. To do that we need to be able to forge connections in all this data, to see how each piece of knowledge relates to every other.

In the semantic Web, we users provide the connections, through our social media activity. The patterns that emerge, the sentiment in the interactions—comments, shares, tweets, Likes, etc.—allow a very precise, detailed picture to emerge.

That’s why the success of Google Plus is critical to Google’s move to semantic search.

The Bottom Line
The semantic Web is accelerating change across the board, challenging companies that move too slowly to adapt. Embrace it, or risk extinction.

The old rules no longer apply. If you want to be found, social is no longer an option.

Practical application of Semantic Web and build applications in your organisation

Semantic technologies allows your to provide meaning to data that is machine understandable. Semantic Web is very well suited for data integration tasks, and building smart data, which is an issue that a lot of big organizations face these days.

They can help you separate your business logic from your codebase by encoding it into an RDF graph; which can help non-programmers perform complex information processing tasks with the help of the computer, which can understand the semantics.

But, like anything else, Semantic technologies are not a silver bullet which will fix all your problems.

You might want to check out the W3C’s official use cases for semantic technologies. There are several good descriptions of projects there which should give you an idea of what other folks are doing with semantic technologies.
Generally, the “semantic web” is a buzzword and therefore is quite unspecific. The basic idea is, to not only connect documents (like you connect websites by using hyperlinks) but to connect semantic concepts. And not only to connect them, but to specify the kind of connections in a more specific way.

And how you do that is totally up to you. There are some technologies that are closely connected to the term “semantic web” like RDF and OWL. You also might to look for the freeware “Protege” which provides some tutorials (Pizza Tutorial). After you have done that, you will have a clearer impression of what you can do with it.

To get another impression what you can do with it, you might want to look at: http://wiki.dbpedia.org/Applications

But to be honest: What you can actually do with it is still beeing researched. There are quite some interesting projects out there, but you are welcome to think of new applications.

There are several parts of the “Semantic Web” that are useful to distinguish:

  • RDF, RDF/S and related technologies
  • OWL and related technologies
  • Linked Data

RDF and RDF/S represent the core of the Semantic Web. It is relatively easy to understand and easy to use. RDF and RDF/S provide you with minimal semantics that you can use to describe concepts used by your organization. Perhaps about the only practical reason you would use it instead of traditional RDBMS is that you need to represent concepts that frequently change and/or evolve. That is, a RDBMS schema would be too rigid and constraining for your purposes; you need something more flexible but still with a schema (i.e. not a schema-less document store for example). For example, a bank where everything is standardized and all schemas are set in stone wouldn’t use RDF/S (or OWL). On the other hand, RDF/S is ideal for knowledge graphs such as DbPedia where the schema constantly evolves.

OWL is a different beast. It provides you with richer concept modelling facilities than RDF/S. It can be useful if you need to define a precise structure of concepts (an ontology) and if you need to verify that the structure is without contradictions. OWL is not so easy to use, and it’s not so easy to understand even for people relatively knowledgeable about the Semantic Web (RDF/S has it’s quirks too but not as much) – the problem is often that of your intended meaning vs. the actual meaning of the OWL expression you use. Also, Some people would say that using OWL is a bit like using blank shells in a gun because you cannot trust your gun to not to shoot yourself in the foot: OWL puts restrictions on what concepts you can express so that reasoners (guns) can deal with it reasonably (not to shoot you for example by never finishing computation). That may be a good thing but it hinders the ease of expression.

Linked Data could be characterized as a movement within the Semantic Web community to make the Semantic Web more practically useful. It shifts focus from knowledge representation (theoretical RDF, RDF/S, OWL) more to their actual applicability on the Web. It stresses the need for using dereferenceable URLs, links between different data sets, correct publishing.

All in all, if you model your data and publish it as Linked Data then thanks to RDF/S and OWL you have the opportunity to create clever applications that were not designed directly for the schema of your dataset but still are capable of using it usefully. A good example how this could be achieved is the Freebase Metaschema: for example your dataset could use properties such as (an actor) “actedIn” (a movie), (an author) “wrote” (a book) and both “actedIn” and “wrote” would be “marked” as some kind of specialization of the property “contributedTo”. So if your application knows how to handle “contributedTo” properties then it will be able to handle even newer datasets to which you add a new property such as “directorOf” and also “map it” to “contributedTo”. The whole Semantic Web machinery is basically aimed at making this possible and at making it general, expressive, and useful.

RDF 1.1 is a W3C Recommendation

World Wide Web Consortium (W3C) has announced that RDF 1.1 has become a “Recommendation.” RDF 1.0 was published in 2004.Over the years, the RDF Working Group has published a set of eight Resource Description Framework (RDF) Recommendations and four Working Group Notes.

Whats new in 1.1?

identifiers are now IRIs (“Internationalized Resource Identifieers” — they were “RDF URI references” before).
language-tagged literals now always have the rdf:langString datatype
simple literals, i.e., literals without datatype do not exist anymore
introduction of datasets (difference to SPARQL is that graph name can also be a blank node)
a couple of new XSD datatypes are now compatible with RDF, namely xsd:duration, xsd:dayTimeDuration, xsd:yearMonthDuration, xsd:dateTimeStamp
new rdf:HTML datatype.
semantics uses the notion of “recognized datatypes” instead of a “datatype map”.