Merge pull request #233532 from baanders/4-5-ontology

ADT: Clean ontologies content

Author: denrea

articles/digital-twins/concepts-models.md

@@ -57,7 +57,7 @@ The main information about a model is given by its attributes, which are defined
 * *Property* - Properties are data fields that represent the state of an entity (like the properties in many object-oriented programming languages). Properties have backing storage and can be read at any time. For more information, see [Properties and telemetry](#properties-and-telemetry) below.
 * *Telemetry* - Telemetry fields represent measurements or events, and are often used to describe device sensor readings. Unlike properties, telemetry isn't stored on a digital twin; it's a series of time-bound data events that need to be handled as they occur. For more information, see [Properties and telemetry](#properties-and-telemetry) below.
 * *Relationship* - Relationships let you represent how a digital twin can be involved with other digital twins. Relationships can represent different semantic meanings, such as `contains` ("floor contains room"), `cools` ("hvac cools room"), `isBilledTo` ("compressor is billed to user"), and so on. Relationships allow the solution to provide a graph of interrelated entities. Relationships can also have properties of their own. For more information, see [Relationships](#relationships) below.
-* *Component* - Components allow you to build your model interface as an assembly of other interfaces, if you want. An example of a component is a frontCamera interface (and another component interface backCamera) that are used in defining a model for a phone. First define an interface for frontCamera as though it were its own model, and then reference it when defining Phone.
+* *Component* - Components allow you to build your model interface as an assembly of other interfaces, if you want. An example of a component is a frontCamera interface (and another component interface backCamera) that's used in defining a model for a phone. First define an interface for frontCamera as though it were its own model, and then reference it when defining Phone.
 
     Use a component to describe something that is an integral part of your solution but doesn't need a separate identity, and doesn't need to be created, deleted, or rearranged in the twin graph independently. If you want entities to have independent existences in the twin graph, represent them as separate digital twins of different models, connected by relationships.
 
@@ -226,9 +226,11 @@ For a DTDL model to be compatible with Azure Digital Twins, it must also meet th
 
 This section describes additional considerations and recommendations for modeling.
 
-### Use DTDL industry-standard ontologies
+### Use existing industry-standard ontologies
 
-If your solution is for a certain established industry (like smart buildings, smart cities, or energy grids), consider starting with a pre-existing set of models for your industry instead of designing your models from scratch. Microsoft has partnered with domain experts to create DTDL model sets based on industry standards, to help minimize reinvention and encourage consistency and simplicity across industry solutions. You can read more about these ontologies, including how to use them and what ontologies are available now, in [What is an ontology?](concepts-ontologies.md).
+An *ontology* is a set of models that comprehensively describe a given domain, like manufacturing, building structures, IoT systems, smart cities, energy grids, web content, and more.
+
+If your solution is for a certain industry that uses any sort of modeling standard, consider starting with a pre-existing set of models designed for your industry instead of designing your models from scratch. Microsoft has partnered with domain experts to create DTDL model ontologies based on industry standards, to help minimize reinvention and encourage consistency and simplicity across industry solutions. You can read more about these ontologies, including how to use them and what ontologies are available now, in [What is an ontology?](concepts-ontologies.md).
 
 ### Consider query implications
 

articles/digital-twins/concepts-ontologies-adopt.md

@@ -32,6 +32,6 @@ Each ontology is focused on an initial set of models. You can contribute to the
 
 ## Next steps
 
-* Learn more about extending industry-standard ontologies to meet your specifications: [Extending industry ontologies](concepts-ontologies-extend.md).
+Learn about extending existing industry-standard ontologies for your specific solution: [Extending industry ontologies](concepts-ontologies-extend.md).
 
-* Or, continue on the path for developing models based on ontologies: [Using ontology strategies in a model development path](concepts-ontologies.md#full-model-development-path).
+Or, continue on the path for developing models based on ontologies: [Full model development path](concepts-ontologies.md#full-model-development-path).

articles/digital-twins/concepts-ontologies-convert.md

@@ -66,6 +66,4 @@ This converter was used to translate the [Real Estate Core Ontology](https://doc
 
 ## Next steps 
 
-* Learn more about extending industry-standard ontologies to meet your specifications: [Extending industry ontologies](concepts-ontologies-extend.md).
-
-* Or, continue on the path for developing models based on ontologies: [Using ontology strategies in a model development path](concepts-ontologies.md#full-model-development-path).
+Continue on the path for developing models based on ontologies: [Full model development path](concepts-ontologies.md#full-model-development-path).

articles/digital-twins/concepts-ontologies-extend.md

@@ -175,4 +175,4 @@ The DTDL for the extended interfaces, limited to the portion discussed above, wo
 
 ## Next steps
 
-Continue on the path for developing models based on ontologies: [Using ontology strategies in a model development path](concepts-ontologies.md#full-model-development-path).
+Continue on the path for developing models based on ontologies: [Full model development path](concepts-ontologies.md#full-model-development-path).

articles/digital-twins/concepts-ontologies.md

@@ -22,15 +22,24 @@ This article describes the concept of industry ontologies and how they can be us
 
 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 that comprehensively describe a given domain, like manufacturing, building structures, IoT systems, smart cities, energy grids, web content, and more.
 
-When you author a model set from scratch that is complete and describes a domain, you're creating your own ontology. Sometimes, however, when modeling standards for an industry already exist, it can be easier and more effective to lean on that existing ontology instead of creating the ontology from scratch yourself. 
+When you author a model set from scratch that is complete and describes a domain, you're creating your own ontology. Alternatively, sometimes modeling standards for an industry already exist, and it can be more effective to lean on that existing ontology instead of creating the ontology from scratch yourself. 
 
-The articles in this section explain more about using pre-existing industry ontologies for your Azure Digital Twins scenarios, including what ontologies are available today, and the different strategies for turning industry standards into ontologies for use in Azure Digital Twins.
+The articles in this section explain more about creating ontologies and using pre-existing industry ontologies for your Azure Digital Twins scenarios, including what existing ontologies are available today, and the different strategies for turning industry standards into ontologies for use in Azure Digital Twin
 
-## Using existing ontologies for Azure Digital Twins
+## Summary of ontology strategies for Azure Digital Twins
 
-Microsoft has created several [open-source DTDL ontologies](concepts-ontologies-adopt.md) built on widely adopted industry standards. You can use these model sets out-of-the-box in your solutions, or [extend the ontologies](concepts-ontologies-extend.md) with your own additions for a customized solution.
+Here are the main strategies for creating DTDL ontologies to use in Azure Digital Twins. Choose the one that works best for you, depending on how closely the existing materials for your industry already match your solution.
 
-Either way, existing industry ontologies provide a great starting point for digital twin solutions. They encompass a set of domain-specific models and relationships between entities for designing, creating, and parsing a digital twin graph. Industry ontologies enable solution developers to begin a digital twins solution from a proven starting point, and focus on solving business problems. The industry ontologies provided by Microsoft are also designed to be easily extensible, so that you can customize them for your solution. Because models in Azure Digital Twins are represented in [Digital Twins Definition Language (DTDL)](https://github.com/Azure/opendigitaltwins-dtdl/blob/master/DTDL/v2/DTDL.v2.md), ontologies for use with Azure Digital Twins are also written in DTDL.
+| Strategy | Description | Resources |
+| --- | --- | --- |
+| Adopt | You can jump-start your solution by adopting one of Microsoft's open-source DTDL ontologies that has been built on widely accepted industry standards. If the ontologies contain all the models you need, you can take these model sets as they are and use them out-of-the-box. | [Adopting industry standard ontologies](concepts-ontologies-adopt.md) |
+| Extend | If an existing DTDL ontology has most, but not all, of the models you need in your solution, you can extend the ontology with your own additions to create a customized ontology. | [Adopting&nbsp;industry&nbsp;standard ontologies](concepts-ontologies-adopt.md)<br><br>[Extending&nbsp;ontologies](concepts-ontologies-extend.md) |
+| Convert | If you already have existing models represented in another standard industry format, you can convert them to DTDL to use them with Azure Digital Twins. | [Converting&nbsp;ontologies](concepts-ontologies-convert.md) |
+| Author | You can always develop your own custom DTDL ontologies from scratch, using any applicable industry standards as inspiration. | [DTDL models](concepts-models.md) |
+
+## Using existing ontologies
+
+Existing industry ontologies provide a great starting point for digital twin solutions. They encompass a set of domain-specific models and relationships between entities for designing, creating, and parsing a digital twin graph. Industry ontologies enable solution developers to begin a digital twin solution from a proven starting point, and focus on solving business problems. The industry ontologies provided by Microsoft are also designed to be easily extensible, so that you can customize them for your solution. Because models in Azure Digital Twins are represented in [Digital Twins Definition Language (DTDL)](https://github.com/Azure/opendigitaltwins-dtdl/blob/master/DTDL/v2/DTDL.v2.md), ontologies for use with Azure Digital Twins are written in DTDL.
 
 Using these ontologies in your solutions can also set them up for more seamless integration between different partners and vendors, because ontologies can provide a common vocabulary across solutions.
 
@@ -40,37 +49,35 @@ Here are some other benefits to using industry-standard DTDL ontologies as schem
 * Easier data interoperability on a semantic level
 * Best practice reuse, rather than starting from scratch
 
-## Strategies for integrating ontologies
+Microsoft has created several open-source DTDL ontologies built on widely used industry standards. You can [adopt these ontologies](concepts-ontologies-adopt.md) out-of-the-box in your solutions, or [extend the ontologies](concepts-ontologies-extend.md) with your own additions to customize your solutions. Because models in Azure Digital Twins are represented in [Digital Twins Definition Language (DTDL)](https://github.com/Azure/opendigitaltwins-dtdl/blob/master/DTDL/v2/DTDL.v2.md), ontologies designed for Azure Digital Twins are also written in DTDL.
 
-Here are the main strategies for integrating existing industry-standard ontologies with DTDL for use in Azure Digital Twins. Choose the one that works best for you, depending on how closely the existing materials for your industry already match your solution.
+If you have a set of models for your industry that's represented in a different standard industry format, such as RDF or OWL, you can use it as a starting point and [convert the models to DTDL](concepts-ontologies-convert.md) in order to use them in Azure Digital Twins.
 
-| Strategy | Description | Resources |
-| --- | --- | --- |
-| Adopt | You can jump-start your solution by adopting one of Microsoft's open-source DTDL ontologies that has been built on widely accepted industry standards. If the ontologies contain all the models you need, you can take these model sets as they are and use them out-of-the-box. | [Adopting&nbsp;industry&nbsp;standard ontologies](concepts-ontologies-adopt.md) |
-| Extend | If an existing DTDL ontology has most, but not all, of the models you need in your solution, you can extend the ontology with your own additions to create a customized ontology. | [Adopting&nbsp;industry&nbsp;standard ontologies](concepts-ontologies-adopt.md)<br><br>[Extending&nbsp;ontologies](concepts-ontologies-extend.md) |
-| Convert | If you already have existing models represented in another standard industry format, you can convert them to DTDL to use them with Azure Digital Twins. | [Converting&nbsp;ontologies](concepts-ontologies-convert.md) |
-| Author | You can always develop your own custom DTDL ontologies from scratch, using any applicable industry standards as inspiration. | [DTDL models](concepts-models.md) |
+## Authoring your own ontologies
+
+If there's no existing industry ontology that meets your needs, you can always develop your own custom DTDL ontologies from scratch. These can be inspired by applicable industry standards, or any other information that's relevant to your business.
 
-### Full model development path
+For information about designing individual models, including all the fields they contain and how to author them in DTDL, see [DTDL models](concepts-models.md).
 
-No matter which strategy you choose for integrating an ontology into Azure Digital Twins, you can follow the complete path below to guide you through creating and uploading your ontology as DTDL models.
+## Full model development path
 
-1. Start by reviewing and understand [DTDL modeling in Azure Digital Twins](concepts-models.md).
-1. Continue with your chosen ontology integration strategy from above: [Adopt](concepts-ontologies-adopt.md), [Convert](concepts-ontologies-convert.md), or [Author](concepts-models.md) your models based on your ontology.
-    1. If necessary, [extend](concepts-ontologies-extend.md) your ontology to customize it to your needs.
+No matter which strategy you choose for designing or integrating an ontology into Azure Digital Twins, you can follow the complete path below to guide you through creating and uploading your ontology as DTDL models.
+
+1. Start by reviewing and understanding [DTDL modeling in Azure Digital Twins](concepts-models.md).
+1. Proceed with your chosen ontology strategy: [adopt](concepts-ontologies-adopt.md), [convert](concepts-ontologies-convert.md), [extend](concepts-ontologies-extend.md), or [author](concepts-models.md) your models based on the needs of your solution and industry.
 1. [Validate](how-to-parse-models.md) your models to verify they're working DTDL documents.
 1. Upload your finished models to Azure Digital Twins, using the [APIs](how-to-manage-model.md#upload-models) or a sample like the [Azure Digital Twins model uploader](https://github.com/Azure/opendigitaltwins-tools/tree/master/ADTTools#uploadmodels).
 
-Reading this series of articles will guide you in how to use your models in your Azure Digital Twins instance. 
-
->[!TIP]
-> You can visualize the models in your ontology using the [model graph](how-to-use-azure-digital-twins-explorer.md#explore-models-and-the-model-graph) in Azure Digital Twins Explorer.
+Once your models have been uploaded to the service, you can...
+* Visualize the models in your ontology using the [model graph](how-to-use-azure-digital-twins-explorer.md#explore-models-and-the-model-graph) in Azure Digital Twins Explorer.
+* Manage them on an ongoing basis, including retrieving models in code, updating models, and deleting models, using the instructions in [Manage DTDL models](how-to-manage-model.md).
+* Use the models to create [digital twins and a twin graph](concepts-twins-graph.md).
 
 ## Next steps
 
-Read more about the strategies of adopting, converting, and authoring ontologies:
+Read more about the strategies of adopting, extending, and converting existing ontologies:
 * [Adopting DTDL-based industry ontologies](concepts-ontologies-adopt.md)
+* [Extending ontologies](concepts-ontologies-extend.md)
 * [Converting ontologies](concepts-ontologies-convert.md)
-* [Manage DTDL models](how-to-manage-model.md)
 
 Or, learn about how models are used to create digital twins: [Digital twins and the twin graph](concepts-twins-graph.md).