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Ontology Management

Make meaning with data connections

While creating and maintaining a taxonomy is the first step in achieving clean, organized data, ontology management allows for rich data understanding. An ontology that successfully leverages its close relationship to the taxonomy is able to produce meaning that could not be found otherwise.

In short, an ontology gives you the ability to express the precise meaning of entities and their relationships to each other. Using standards-based ontologies, machines can more accurately process the meaning of data based on complex business rules in an automated way and detect data inconsistencies on their own.

The biggest challenges for organizations who haven’t adopted ontologies.


Data silos

Ontologies open the door, so to speak, to the big wide world of data. The data becomes interoperable, be it within company boundaries, or even to other data sources from e.g. suppliers or government agencies. Without the expressive layer of ontologies, company data remains “locked” in disparate silos.


Rigid data

Relational data models are rigid and there is a good reason for this, as they were developed for exactly one application. Data described on the basis of ontologies can be flexibly linked via mechanisms such as ontology-based data access (OBDA) and reused by a wide variety of applications.

Useful Resources

Tutorial: From taxonomies to ontologies.

White Paper: Healthcare Information System to Australian Citizens using PoolParty Semantic Suite 

PoolParty Application Gallery: Get ideas and insights on how to use semantic technology.

The biggest changes organizations can leverage with PoolParty’s ontology management.

Simply put, a dataset that doesn’t use an ontology does not provide the same rich dimensionality as it would with one. Whereas a taxonomy is good for classification and definition of concepts, terms, and labels, the ontology adds an expressive layer to the data by introducing the semantic relationships between business objects. Without an ontology, the computer fails to match the natural links of business objects that human logic is already adept at. 

A manufacturer might favor an ontology for its ability to map links between products, suppliers, and stores that the products are being sold in. This gives them an overview of their organization and allows for insights pertaining to inventory and their supplier network that they would struggle to pull without an ontology.

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Experience the major benefits of ontology management with PoolParty Semantic Suite today.

Easy integration

PoolParty lets you design knowledge graphs at your own pace and with speed. Create your own ontologies and custom schemes by reusing already existing ontologies such as FOAF, FIBO, and CHEBI, among others. Apply them to your existing taxonomies with ease.



While PoolParty operates primarily with semantic web SKOS and OWL standards, it also supports the use of custom schemes that are non-SKOS. You can start with simple knowledge models based on SKOS and extend to OWL ontologies. SCHACL language can be used to further validate the data and act as an endpoint for complex queries.



PoolParty’s adaptable platform allows you to scale your data model as you go. Any updates to your ontology can be done quickly and efficiently. These ontologies serve as a prerequisite to enterprise knowledge graphs, which enable you to have a comprehensive, enriched overview of your business.

Download the success story with our customer JobTeaser to learn how they use ontologies to power their job recruiting platform