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In which scenario we are going for an Ontology? Can anyone tells some real time applications of Ontology?

While googling I noticed about some semantic web applications are using ontology. But still i didn't got the exact idea about semantic web applications.

From this link i got something about creation of Ontologies, but still I am confusing for what we are going for Ontology by neglecting the traditional databases. And i didn't found any real time applications that using Ontology concept.

Thank you in advance

User
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  • Ontologies do not replace traditional databases, but can be used to augment them (and some more stuff). Primary goal of ontologies is to make computers know, what kind of data they are dealing with. From that there are many applications, e.g., in relation to data integration. – Sirko Jun 03 '14 at 10:02
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    http://protege.stanford.edu/publications/ontology_development/ontology101-noy-mcguinness.html, you can follow the link, there is a great example. – berkay Jun 03 '14 at 10:04
  • Hi berkay, That link i already checked and i mentioned in my question – User Jun 03 '14 at 10:10
  • Hi sirko, So you mean Ontologies provides some artificial intelligence to our applications? – User Jun 03 '14 at 10:11
  • @Rameez Not the ontologies by themselves, but they are helpful in that way. They define some vocabulary for entities and their relations, which AI algorithms can then exploit. Simple example are additional information on websites: If your algorithm knows, that something is a geographical location, it can automatically provide a map for it, for example. In the old days, there would just be some string, which the system knows nothing about. – Sirko Jun 03 '14 at 10:28
  • @Sirko oh ok, thats great. Now I got a little more clarifications. But still i have a concern like, this can be implemented with an algorithm and a well structured database right? And can you please tell me some real time examples which using the Ontology. Some websites or applications? My doubt is whether the Ontology is implemented in anywhere? is it worth am spending time on this? please post it as answer then all can easily saw that. – User Jun 03 '14 at 10:41
  • Hi Sirko, I feel your answers are very relevant to me. Can you please add anything to my [previous question](http://stackoverflow.com/q/23950515/3004836) – User Jun 04 '14 at 04:25

3 Answers3

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Ontologies do not replace databases, but can be used to augment them.

Ontologies provide kind of a common vocabulary for multiple systems, so that data coming from one system can be processed in the other. You could, of course, define one fixed vocabulary (like, e.g., HTML) to describe your data. But in this case you are bound to the defined terms and every new kind of data will lead to a rebuilding of your vocabulary.

Ontologies, on the other hand, are more open. So there are some high level ontologies, that define stuff like "country", "town" or "human being". Based on this you can then create your own ontology and say something like 

An employee is a human being.
A store is a geographic location with ...
Each store has at least one employee.

You can then use so called Reasoners, to deduce additional information from that based on the other semantic information you have access to. So , e.g., the following information might be deduced:

"An employee is a human being." + "Each store has at least one employee."
=> Each store has at least one human being.

This is a simple example, but you get the point.

Besides that reasoning over given information, the semantic annotation can be used in data integration: If the system knows the kind of data it is dealing with, it can make much better suggestions how to integrate it in the current knowledge base. There is plenty of research in that area!

So in the end ontologies serve two purposes:

  1. Augment your data, so others can understand and use it.
  2. Retrieve additional knowledge from your current information by using a Reasoner.

As for real life examples, the following come to mind:

  • schema.org describe your website data in a semantic way and help the search engines find it.
  • Several catalogs of species or substances used in Biology and Pharmacy

Also this question might help:

Community
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Sirko
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Before understanding the real world examples of Ontologies, you should first understand what an Ontology is. According to the Tom Gruber, an AI specialist at Stanford University, the definition of an Ontology is as follows.

An ontology is the specification of conceptualizations, used to help programs and humans share knowledge. An Ontology is a formal and explicit specification of a shared conceptualization.

  • Conceptualization - Breaking the world into concepts in terms of
  • Entities Specification - This is the representation of this
    conceptualization in a concrete form.

In general, an ontology looks like a schema, that describes the entities, their properties and the relationships among these entities, in a specific domain. There can also be constraints in the way that each entity can be combined. Relational databases are simply diagrams that can be used to represent scenarios using UML. But ontologies have formal semantics, so can be machine-interpreted, rather than just being diagrams for human consumption. More on this can be read through this forum.

Why we need Ontologies

Today, people have access to more data from various sources broadening to many different domains and information systems. The amount of data that can be accessed within a single date has increased over time, when compared with the information systems we had decades ago.

For example, if we look at an enterprise, their data sources can be found in many different forms like spreadsheets, databases, presentations, documents, Visio diagrams etc. Since these are all captures in many different formats, it makes it inherently hard to understand the relationship between different data. In a situation like this, it is very hard to understand how policies captured in word documents, relate to business processes captured in models,and how these business processes relate to data captured in the database and so on.

Data needs to be allowed to represent in a format where we can identify all these relationships and stored. Ontologies capture data in a way that allows these relationships to become visible. An ontology is a form of knowledge management. It captures the knowledge within a certain domain (organization/ information system) as a model (data model). This model can then be queried by users, to answer complex questions and display relationships across a domain.

Real World Applications of Ontologies

  1. Artificial Intelligence
  2. Semantic Web
  3. Systems Engineering
  4. Software Engineering
  5. Biomedical Informatics
  6. Library Science
  7. Enterprise Bookmarking
  8. Information Architecture

To understand more about Ontologies, please do read this blog. It contains more than enough information.

GabrielGodefroy
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Keet Sugathadasa
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Ontology enables you to link your data, and reason over it automatically. It is a good question you ask, cause even today, the Semantic community is still seeking what is the "Killer APP" for ontology.

I have developed some simple ontology applications, as shown below:

Lost Silence: http://arxiv.org/abs/1903.05372

SARA -- A Semantic Access Point Resource Allocation Service for Heterogenous Wireless Networks: http://eprints.gla.ac.uk/179727/

NextBus reverse proxy: https://github.com/QianruZhou333/reverseProxy_NextBus.git

Qianru Zhou
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