Ontology vs taxonomy – this is one of the most common comparisons made when people learn about semantic search and the world of semantic technology. Now, the question that arises is that does the two indeed have much of a difference and whether they play different roles in the semantic world. To understand this, one must get a clear understanding of the role of the semantic technology and why it’s one of the key technologies driving enterprise search today. Why semantic search? Well, the simple answer to this is that this is what enterprises need in order to unravel all that’s hidden within the unsurmountable volumes of enterprise data. 3RDi Search is one such enterprise search tool that is powered by semantic technology. Commvault is another such tool. But why need an entirely new technology to analyze this data, instead of going for the traditional search technology? It’s because the enterprise data is mostly unstructured and raw, and the keyword based approach is not well-equipped to analyze it. How Semantic Search Works Semantic search works differently from the conventional keyword based approach, because while the latter only focuses on finding results that match with the set of keywords provided in the query by the user, the latter involves a detailed analysis of the query in order to find the most relevant results to a query, including the results that include synonyms of the terms in the query. This can be beneficial in increasing the scope of search and also the relevancy. Ontology vs Taxonomy Here’s what ontology and taxonomy means and their difference: Ontology In the semantic web, ontology refers to the set of terms that are used to represent a domain. These are a common set of terms that are specific to a certain domain and it is used to describe the concepts in the domain. In other words, an ontology is used to describe an area of information. For example, the ontology for education and learning domain will be different from the ontology for say, the medicine domain. Today’s enterprise search software are powered by domain-specific vocabulary, which helps in providing the software the needed ontology to find relationships between terms it encounters, and identifying the context of the term. Ontology also defines the relationship between the different terms in the set. In other words, ontology is what helps define the terms associated to a domain, as well as the relationships between them. Not just that, it is the ontology that encodes the knowledge of the domain such that it becomes easier for the machines to understand. Taxonomy Taxonomy is the term used to refer to the science of classification. What began as a science of classification of living organisms, is used as a term to denote classification of concepts, things, as well as schemes that underly a classification. Taxonomy also involves hierarchical relationships embedded in its classifications. Taxonomy is important to the concept of semantics, as it can help classify the terms in the query and also establish relationships between them. This can help a semantic search tool to identify the context of the unstructured data that it’s analyzing. So, that was about ontology vs taxonomy and their role in the semantic technology. Today we have highly advanced software to analyze unstructured data, and all of them have semantics at its core.