What is an ontology? In simple terms, an ontology is a representational system which defines the concepts, topics, subjects and the relationships within a subject domain. Models such as taxonomies, ontologies, controlled vocabularies and thesauri allow organizations to identify and create a consistent language, which users understand and describes the organization, processes and customers so they can:
- Consistently apply context and meaning to information throughout the enterprise in order to realize its value.
- Find the information they need and act on it to drive successful results.
- Apply text analytics to identify the meaningful information within enterprise information using machines and algorithms.
- Apply a series of tags also known as metadata, which identify the core concepts found within information.
- Identify important information found within information assets, which is not part of your model, but improves classification results such as, people, places, dates, measurements, nouns, zones of text, etc. using extraction.
- Harmonize disparate information sources against a canonical model to unify information and drive key decisions.
Seems like having a model is good thing to have, so why doesn’t every organization have one? They take time to build, the language throughout the enterprise is not always consistent and not everyone understands the value – so they are reluctant to provide the time and resources it takes.
A good way to approach model development is to use tools, technology and processes that support the process. You’ll want a feature rich platform that incorporates Semantic Web standards so you can you drive information exchange, leverage open linked data and increase interoperability in the ontology building process.
Using an model management tool that’s easy to use and collaborative can streamline the model building process. And those painful conversations to gain consensus for each concept and term can be eliminated if the tool supports contextual synonyms and relationships that address the differences in term definitions across the enterprise so that all users are satisfied.
The Semantic Web provides a common standards based framework that allow data to be shared and reused across department, enterprise and community boundaries. These standards promote common data formats and exchange protocols so that organizations can share information and incorporate internal as well as external models into their organization.
Incorporating these standard models lets you jump-start the ontology development process. You can begin with a public ontology and customize it to reflect the unique concepts and terms associated with your organization and business domain. By linking to public domain models you can include the information you need and at the same time data remains independent, individual taxonomies live where they’re developed and model integrity remains intact.
And let’s face it you don’t have to model the whole organization at once – you can use an agile process starting with one part and build sideways. Once you’ve identified a problem, you model the problem domain; if your problem is adverse event reporting in Pharma, you look at drugs, side effects and dosages. Once you’ve solved one business problem you’re ready to tackle another and when you’re done you can link them together if appropriate.
Smartlogic’s Intelligent Information platform addresses these issues. Semaphore Ontology Editor supports:
- A web-based, easy-to-use model management platform that supports user collaboration. Multiple models can be worked on at the same time and what-if modeling can be performed before updating production models.
- Ontology mapping and linked open data that leverages internal as well as public domain models.
- Native Semantic Web support.
- Task centric model development to drive workflow & life-cycle management to support best practices and mimic the way teams work.
With these features you can quickly build your model and put it to work immediately by extracting critical entities and facts, enriching all information with precise and complete metadata and harmonizing all information across the enterprise to drive workflows, manage regulatory compliance, improve search and discovery, and archive, migrate and monetize your information.
Building an ontology doesn’t have to be painful, using Semaphore tools and processes can help you jump-start the ontology building process and realize the value in your information immediately.
