简而言之:

RDF定义了如何写东西 OWL定义了要写什么

正如前面的帖子所写的，RDF是一种规范，它告诉您如何定义三元组。

问题是RDF允许你定义任何东西，所以你可以像这样组成一个声明:

| subject | predicate | object |
|---------|-----------|--------|
| Alex    | Eats      | Apples |
| Apples  | Eats      | Apples |
| Apples  | Apples    | Apples |

这些三元组形成有效的RDF文档。

但是，从语义上讲，您知道这些语句是不正确的，RDF不能帮助您验证所编写的内容。

这不是一个有效的本体。

OWL规范准确地定义了您可以用RDF编写什么以获得有效的本体。

本体可以有几个属性。

这就是为什么OWL(版本1)定义了几个版本，如OWL DL, OWL Lite, OWL Full。

RDF、RDFS和OWL是表示日益复杂的信息或知识的方法。它们都可以用RDF/XML语法(或任何其他RDF序列化语法，例如Turtle或N3)序列化。

这些技术是相关的，应该是可互操作的，但它们有不同的起源，这可能就是为什么它们之间的关系很难掌握的原因。选择一种还是另一种取决于建模所需要的情况有多复杂。

表达能力的总结

RDF:简单的表示，主要关注实例及其类型的映射(RDF: type)。可以定义自定义属性来链接数据和创建三元组。使用SPARQL查询RDF数据。 在Turtle中序列化RDF的例子:

@prefix : <http://www.example.org/> .
:john    rdf:type           :Man .
:john    :livesIn  "New-York" .
:livesIn    rdf:type    rdf:Property .

RDFS: Some situations are not easily modelled by RDF alone, it is sometimes interesting to represent more complex relations like subclasses (the type of a type) for example. RDFS provides special means to represent such cases, with constructs like rdfs:subClassOf, rdfs:range or rdfs:domain. Ideally, a reasoner can understand the RDFS semantics and expand the number of triples based on the relations: For instance if you have the triples John a Man and Man rdfs:subClassOf Human then you should generate as well the triple John a Human. Note that this is not possible to do with RDF alone. RDFS data are queried using SPARQL. Example of RDFS serialised in Turtle:

@prefix : <http://www.example.org/> .
:john    rdf:type           :Man .
:Man    rdfs:subClassOf    :Human .
:john    :livesIn  "New-York" .
:livesIn    rdf:type    rdf:Property .
# After reasoning
:john    rdf:type    :Human .

OWL: The highest level of expressivity. Relation between classes can be formally modelled based on description logics (mathematical theory). OWL relies heavily on the reasoner, it is possible to express complex constructs such as chained properties for instance or restriction between classes. OWL serves to build ontologies or schema on the top of RDF datasets. As OWL can be serialised as RDF/XML, it is theoretically possible to query it via SPARQL, yet it is much more intuitive to query an OWL ontology with a DL query (which is usually a standard OWL class expression). Example of OWL constructs serialised in Turtle.

@prefix : <http://www.example.org/> .
:livesIn    rdf:type    owl:DatatypeProperty .
:Human    rdf:type    owl:Class .
:Man   rdf:type    owl:Class .
:Man    rdfs:subClassOf    :Human .
:John    rdf:type    :Man . 
:John    rdf:type    owl:NamedIndividual .

当您使用术语RDF时，您必须区分两件事:

You can refer to RDF as a concept: A way of describing things/logic/anything using collections of triples. Example: "Anna has apples." "Apples are healthy." Above you have two triples that describe two resources "Anna" and "apples". The concept of RDF (Resource Description Framework) is that you can describe resources (anything) with sets of only 3 words (terms). At this level you don't care about how you are storing information, whether you have a string of 3 words, or a painting on a wall, or a table with 3 columns etc. At this conceptual level the only thing that is important is that you can represent anything that you want using triple statements. You can refer to RDF as a vocabulary A vocabulary is just a collection of term definitions stored in a file or somewhere. These defined terms have the purpose of being generally reused in other descriptions so people can describe data (resources) more easily and in a standard manner. On the web you can find some standard vocabularies like: RDF (https://www.w3.org/1999/02/22-rdf-syntax-ns) RDFS (https://www.w3.org/2000/01/rdf-schema#) OWL (https://www.w3.org/2002/07/owl) The RDF vocubalary defines terms that help you to describe (at the most basic level as possible) individuals/instances of classes. Example: rdf:type, rdf:Property. With rdf:type you can describe that some resource is an instance of a class: <http://foo.com/anna> rdf:type <http://foo.com/teacher> So the RDF vocabulary has terms that are targeting basic descriptions of class instances and some other descriptions (like the triple statement definition, or the predicate definition... in general things that are realted to the RDF concept). The RDFS vocabulary has term definitions that help you describe classes and relationships between them. RDFS vocabulary doesn't care about instances of classes (individuals) like the RDF vocabulary. Example: the rdfs:subClassOf property which you can use to describe that a class A is subclass of class B. The RDF and the RDFS vocabularies are dependent to one another. RDF defines it's terms using RDFS, and RDFS uses RDF for defining it's own terms. The RDF/RDFS vocabularies provide terms that can be used to create very basic descriptions of resources. If you want to have more complex and accurate descriptions you have to use the OWL vocabulary.

OWL词汇表附带了一组针对更详细描述的新术语。这些术语是使用RDF/RDFS词汇表中的术语定义的。

owl:ObjectProperty a rdfs:Class ;
                   rdfs:label "ObjectProperty" ;
                   rdfs:comment "The class of object properties." ;
                   rdfs:isDefinedBy <http://www.w3.org/2002/07/owl#> ;
                   rdfs:subClassOf rdf:Property .

owl:DatatypeProperty a rdfs:Class ;
                     rdfs:label "DatatypeProperty" ;
                     rdfs:comment "The class of data properties." ;
                     rdfs:isDefinedBy <http://www.w3.org/2002/07/owl#> ;
                     rdfs:subClassOf rdf:Property .

 owl:TransitiveProperty a rdfs:Class ;
                        rdfs:label "TransitiveProperty" ;
                        rdfs:comment "The class of transitive properties." ;
                        rdfs:isDefinedBy <http://www.w3.org/2002/07/owl#> ;
                        rdfs:subClassOf owl:ObjectProperty .

正如您在上面所看到的，OWL词汇表通过创建新的属性类型来扩展rdf:Property的概念，这些类型不那么抽象，可以提供更准确的资源描述。

结论:

RDF is a concept or a way of describing resources using sets of triples. RDF triples can be stored in different formats (XML/RDF, Turtle etc.) The concept of RDF is the base model of all semantic web technologies and structures (like vocabularies). RDF is also a vocabulary that along with the RDFS vocabulary provides a set of terms that can be used for creating general/abstract descriptions of resources. OWL is a vocabulary built with RDF and RDFS vocabularies that provide new terms for creating more detailed descriptions of resources. All semantic web vocabularies (RDF, RDFS, OWL etc) are built by respecting the RDF concept. And of course the OWL vocabulary has behind the scenes all kind of complex logic and concepts which define the Web Ontology Language. The OWL vocabulary is just a way of using all that logic in practice.

基本的语义web堆栈已经在这篇文章中解释了很多。我想把重点放在最初的问题上，并比较RDF和OWL。

OWL是RDF和RDF- s的超级集(在上面) OWL允许有效地使用RDF和RDF- s OWL有一些扩展的词汇表 类和个人(“实例”) 属性和数据类型(“谓词”) OWL是正确的推理和推断所必需的 OWL有三种方言，精简，描述逻辑和完整

使用OWL是通过了解一些事实来获得更多意义(推理和推断)的必要条件。这种“动态创建”的信息可以进一步用于像SPARQL中那样的一致查询。

一些例子将显示这实际上与OWL一起工作——这些都是从我2015年在西班牙马略卡的TYPO3camp上关于语义网基础知识的演讲中摘录出来的。

规则等价

Spaniard: Person and (inhabitantOf some SpanishCity)

这意味着西班牙人必须是一个人(因此继承了推理部分中的所有财产)，并且必须至少居住在一个(或多个)西班牙城市。

属性的含义

<Palma isPartOf Mallorca>
<Mallorca contains Palma>

该示例显示了对属性isPartOf和contains应用inverseOf的结果。

逆 对称的 传递 不相交的 .．.

属性的基数

<:hasParent owl:cardinality “2“^^xsd:integer>

这定义了每个事物(在这个场景中很可能是人)都有两个父元素——基数被分配给hasParent属性。

最低 最大 确切的

The Resource Description Framework (RDF) is a powerful formal knowledge representation language and a fundamental standard of the Semantic Web. It has its own vocabulary that defines core concepts and relations (e.g., rdf:type corresponds to the isA relationship), and a data model that enables machine-interpretable statements in the form of subject-predicate-object (resource-property-value) triples, called RDF triples, such as picture-depicts-book. The extension of the RDF vocabulary with concepts required to create controlled vocabularies and basic ontologies is called RDF Schema or RDF Vocabulary Description Language (RDFS). RDFS makes it possible to write statements about classes and resources, and express taxonomical structures, such as via superclass-subclass relationships.

Complex knowledge domains require more capabilities than what is available in RDFS, which led to the introduction of OWL. OWL supports relationships between classes (union, intersection, disjointness, equivalence), property cardinality constraints (minimum, maximum, exact number, e.g., every person has exactly one father), rich typing of properties, characteristics of properties and special properties (transitive, symmetric, functional, inverse functional, e.g., A ex:hasAncestor B and B ex:hasAncestor C implies that A ex:hasAncestor C), specifying that a given property is a unique key for instances of a particular class, and domain and range restrictions for properties.

我试图掌握语义网的概念。我发现这很难 来理解RDF和OWL之间的确切区别。是 OWL是RDF的扩展或者这两者是完全不同的 技术吗?

简而言之，是的，您可以说OWL是RDF的扩展。

In more detail, with RDF you can describe a directed graph by defining subject-predicate-object triples. The subject and the object are the nodes, the predicate is the edge, or by other words, the predicate describes the relation between the subject and the object. For example :Tolkien :wrote :LordOfTheRings or :LordOfTheRings :author :Tolkien, etc... Linked data systems use these triples to describe knowledge graphs, and they provide ways to store them, query them. Now these are huge systems, but you can use RDF by smaller projects. Every application has a domain specific language (or by DDD terms ubiquitous language). You can describe that language in your ontology/vocabulary, so you can describe the domain model of your application with a graph, which you can visualize show it to business ppl, talk about business decisions based on the model, and build the application on top of that. You can bind the vocab of your application to the data it returns and to a vocabulary known by the search engines, like microdata (for example you can use HTML with RDFA to do this), and so search engines can find your applications easily, because the knowledge about what it does will be machine processable. This is how semantic web works. (At least this is how I imagine it.)

Now to describe object oriented applications you need types, classes, properties, instances, etc... With RDF you can describe only objects. RDFS (RDF schema) helps you to describe classes, inheritance (based on objects ofc.), but it is too broad. To define constraints (for example one kid per chinese family) you need another vocab. OWL (web ontology language) does this job. OWL is an ontology which you can use to describe web applications. It integrates the XSD simpleTypes. So RDF -> RDFS -> OWL -> MyWebApp is the order to describe your web application in a more and more specific way.