Gartner has positioned taxonomy and ontology management on the 2016 Emerging Technologies Hype Cycle

Source: Gartner 2016

Recently one of our Twitter followers asked if we agreed with the way Gartner has positioned taxonomy and ontology management on the 2016 Emerging Technologies Hype Cycle. The technology profile (or “dot” as they are fondly called) is halfway between the Peak of Inflated Expectations and the Trough of Disillusionment with an estimated maturity date of more than 10 years.

Before we answer the question, there are a couple of things that are probably worth mentioning:

• Hype cycles are meant to represent immature technologies, giving organizations the ability to predict the potential impact and disruption that a particular technology may have in their enterprise. A technology typically matures off the curve when it achieves an adoption rate of about 30%.
• The placement of the dot is not relative to a particular hype cycle. The technology profiles are developed independently by subject matter experts who estimate the placement of a particular dot, then hype cycle authors assemble the collection of dots that most closely represent the topic area. The first iteration of a hype cycle diagram is a nightmare – typically the dots are all on top of one another and it takes significant graphic skill to make the diagrams as readable as they are when published. The point is that the Taxonomy and Ontology Management dot is in exactly the same place on all the hype cycles in which it appears; these include Information Infrastructure, Information Governance and MDM, Content Management and others
• The Priority Matrix, which is included in the Hype Cycle document, is a very important diagram and is often overlooked. The Priority Matrix is designed to help companies identify the high impact technologies that may transform their organization or disrupt their industry in the short, medium and long term. The Taxonomy and Ontology Management dot is judged to be of medium impact and is very long term (more than 10 years) – the implicit advice to organizations is that this is technology worth ignoring.

So do we agree with Gartner? The answer is complex – we kinda do and kinda don’t.

We do agree with Gartner that Taxonomy and Ontology Management, by itself, is not a high impact technology. When you build an ontology, you are in essence constructing a model of a problem domain. Models are great in clarifying your thinking around a particular topic, but beyond that, they have very little intrinsic value. They’re just a picture. They don’t do anything. Unless the model is put to work in some way that creates a positive business impact on the enterprise, it’s just a model. We also believe, based on our experience with clients, that getting out of the relational, object/attribute mindset when modeling is a difficult thing to do. Semantic modeling is about concepts and relationships – not the way most organizations are conditioned to think. So yes, Taxonomy and Ontology Management is not high impact and the time to maturity is going to be quite long unless you have expert help to teach you how to model semantically instead of relationally.

HOWEVER

We also disagree with Gartner, because we think they are missing something. We were very surprised to find a dot for Taxonomy and Ontology Management, but no companion dot for the technologies that put the model to work. Smartlogic Semaphore is a model-driven, rules-based platform for the generation of metadata. That is, we build the model, use the model to derive the classification rules and then use sophisticated NLP techniques to analyze the information assets and generate metadata for them in the context of the model. Our clients are using Taxonomy and Ontology Management in conjunction with rules-based metadata generation to achieve significant business outcomes every day.

So with respect to Taxonomy and Ontology Management, Gartner may be right. But they are only telling part of the story. Organizations SHOULD NOT ignore Taxonomy and Ontology Management, because when taken in conjunction with technologies that make the model useful, it can deliver real results today.