How to Develop an Ontology in Your Organization

We have already discussed Data Ontology in my earlier post and if you have directly stumbled upon this post then I will recommend to first read that one here–

In today’s fast-paced world of data, it’s tough for organizations to make the most out of all their information. With data coming in quickly and frequently from various sources, it’s a challenge for analysts and data experts to know and use data from different parts of the organization. If we can’t find and use the data properly, it leads to extra work, time wasted, and missed chances to discover valuable insights from the data. Data Ontology can help organizations address this challenge.

Components of Data Ontology

Ontologies are like building blocks that need data to be created. Think of this data as a business glossary, which is just a list of business terms and what they mean just how we see a special section in a book where all the confusing terminologies are defined so that we understand the context of using them in that particular book. So, the first thing you do when creating an ontology is to make a business glossary. Once you have that, it becomes the base for your ontology. Below are the possible components-

• Concepts Glossary – These are the basic entities or concepts within the domain.
• Hierarchy – Concepts can be further categorized in sub-concepts and instances related to each concept.
• Attributes – Properties which are associated with each concept, establishing relationships with specific instances.
• Relationships – These depict how all the concepts are linked or associated with other concepts.
• Constraints – The constraints which are applicable on relationships among concepts.

Data ontology for an Enterprise

Let’s understand the development process using an example. The image below represents an enterprise structure, and the concept is “Organization,” which encompasses various domains, teams, and employees. Within the “Domains” category, there are specific teams and employees associated. This hierarchical arrangement can also be added where teams and employees exist within distinct domains, creating a network of relationships.

First step can be to decide the scope or domain, which we chose as an ‘Organization’ on a broad level and how would you decide that? It’s simple! Scope should be in such a way that you should be able to understand and answer the questions out of the diagram. For example- “Steve is an employee and by looking at the diagram you should be able to understand that what is his designation, which team he is part of?”

Second step would be to decide the concepts and the glossary. An organization can have different domains, teams and employees. Prepare a mini dictionary explaining the meaning of all
the terms, as every enterprise might not have the same meaning for domain.

Next step would be to build out the hierarchy using concepts and sub-concepts. You can use top-down or bottom-up approach as per your convenience. I find top-down a bit easier to develop. For ex- you can start with Organization, then domain, then teams and then employees.

Fourth step is to add the properties. An example of this can be the responsibility or main functioning of a domain/department. So, that way each instance of domain will have different functioning. In the same manner, you can add properties/attributes of all the concepts in the hierarchy.

Next step would be to add the relationships of the concepts with each other as how they are linked. In Organization, domain has some functioning and teams under those domains work towards achieving common goals. Some employees might be part of a Team but they also contribute to a community which is again a subconcept.

Next thing you can define the constraints. For example- an employee can only belong to a single team.

The final step in building an ontology involves generating specific instances for the concepts within the hierarchy. This you can achieve by selecting a concept and then creating individual instances based on that chosen concept. In our example- instances of domain can be various Departments like ‘IT Support and HelpDesk’ or ‘IT Department’ etc.

Conclusion

Though I have provided you with all the steps that you will require to create a Data Ontology for your domain but It’s important to remember that there’s no one-size-fits-all approach to create an ontology. The key is to recognize that ontology development is a dynamic process, and its effectiveness can truly be evaluated when applied in practical applications.
Happy Learning!