Merge pull request #189761 from baanders/2-25-ont

ADT: Small edits ontology text

Author: Court72

articles/digital-twins/concepts-ontologies.md

@@ -19,17 +19,9 @@ ms.service: digital-twins
 
 This article describes the concept of industry ontologies and how they can be used within the context of Azure Digital Twins.
 
-The vocabulary of an Azure Digital Twins solution is defined using [models](concepts-models.md), which describe the types of entities that exist in your environment.
+The vocabulary of an Azure Digital Twins solution is defined using [models](concepts-models.md), which describe the types of entities that exist in your environment. An *ontology* is a set of models for a given domain, like building structures, IoT systems, smart cities, energy grids, web content, and more.
 
-Sometimes, when your solution is tied to a particular industry, it can be easier and more effective to start with a set of models for that industry that already exist, instead of authoring your own model set from scratch. These pre-existing model sets are called **ontologies**.
-
-In general, an ontology is a set of models for a given domain—like a building structure, IoT system, smart city, the energy grid, web content, and so on. Ontologies are often used as schemas for twin graphs, as they can enable:
-* Harmonization of software components, documentation, query libraries, and so on.
-* Reduced investment in conceptual modeling and system development
-* Easier data interoperability on a semantic level
-* Best practice reuse, rather than starting from scratch or "reinventing the wheel"
-
-This article explains why to use ontologies for your Azure Digital Twins models and how to do so. It also explains what ontologies and tools for them are available today.
+Sometimes, when your solution is tied to a particular industry, it can be easier and more effective to start with a set of models for that industry that already exist, instead of authoring your own model set from scratch. This article explains more about using pre-existing industry ontologies for your Azure Digital Twins scenarios, including strategies for using the ontologies that are available today.
 
 ## Using ontologies for Azure Digital Twins
 
@@ -39,6 +31,12 @@ Also, using these ontologies in your solutions can set them up for more seamless
 
 Because models in Azure Digital Twins are represented in [Digital Twins Definition Language (DTDL)](https://github.com/Azure/opendigitaltwins-dtdl/blob/master/DTDL/v2/dtdlv2.md), ontologies for use with Azure Digital Twins are also written in DTDL. 
 
+Here are some other benefits to using industry-standard DTDL ontologies as schemas for your twin graphs:
+* Harmonization of software components, documentation, query libraries, and more
+* Reduced investment in conceptual modeling and system development
+* Easier data interoperability on a semantic level
+* Best practice reuse, rather than starting from scratch
+
 ## Strategies for integrating ontologies
 
 There are three possible strategies for integrating industry-standard ontologies with DTDL. You can pick the one that works best for you depending on your needs: