John Graybeal

Registering and Accessing Your Ontology

Once you have your ontology in hand, you need to tell the world about it. You also need a way for the world to easily access your information.

Creating Ontologies Using Vocabularies

For flat or hierarchical vocabularies, it is often straightforward to create a corresponding ontology. The development of an ontology will involve ensuring the following: format, classes/subclasses, instances, and relationships. Here are a few key things to understand before you begin creating the ontology.

Creating a Domain Ontology

If you want to create a sophisticated ontology describing a domain of interest, there are a few basic steps to get started. Below is a brief outline of the process; the related resources at the end of the guide provide a more thorough treatment.

Community or Solo?

Given your particular goals and knowledge, you will need to decide whether to make the ontology development a community effort. Reasons to do so include greater buy-in (acceptance) and use of the ontology, greater awareness of the work, and access to a larger pool of knowledge.

Who Serves Your Ontology?

When you have an ontology, you have to choose whether to present it yourself, or via one or more third-party repositories. There are good reasons to do it either way, as described below. Additional considerations are described in the section on Registering and Accessing Ontologies.

Creating and Serving Ontologies

If you are thinking about creating your own ontology, you must first do several things to build it, and then a few more tasks to make it useful.

Building An Ontology

The steps to build an ontology depend on what kind of information you want to represent.

Many ontologies are created to capture understanding of a domain. These ontologies relate the different concepts in the domain to each other. A typical resource in such an ontology may say something like:

atmospheric_winds Create sea_surface_waves

What is an Ontology?

An ontology is a representation of knowledge, generally of a particular subject (domain), written with a standardized, structured syntax. An ontology contains concepts (resources), which serve to characterize the domain.

Mapping Among Controlled Vocabularies

Reasons for Mapping Controlled Vocabularies

Mapping provides long-term advantages that help improve the utility and longevity of a project’s data.

Understanding the motivations behind mapping and the tools that are available to associate the metadata elements in one project with the terms in another vocabulary will assist a metadata manager in making good decisions for a project. Motivations for mapping may include the following and are described below:

Overview to Choosing and Implementing Established Controlled Vocabularies

There are two ways to obtain a controlled vocabulary: start with an existing vocabulary or build your own. We strongly recommend the first approach for most situations. There are four steps in creating a system with integrated controlled vocabularies. (If you have implemented your own vocabulary, you can apply steps three and four after your new controlled vocabulary is established.)

Achieving Semantic Interoperability


Semantic interoperability exists when different systems can make effective use of the terms that are used in an interaction. For example, a meteorology model may use the general term “temperature” for air temperature and provide a more specific term for water temperature. This may work fine with another meteorological system, but it will cause confusion when interacting with an ocean model where the more generic “temperature” means water temperature and “air temperature” is more specifically named.

Choosing a Controlled Vocabulary

This guide is written for data managers and managing scientists who must implement a data system for their project. The adoption of vocabularies for a metadata project requires understanding of the characteristics of the project and the data system in which the vocabularies will be applied.

Finding and selecting an appropriate vocabulary takes some research. Defining your own vocabulary may seem like an easier alternative, but ultimately this approach decreases your project’s ability to interoperate with other data sources.


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