Archive:Development/Tutorials/Metadata/Nepomuk/RDFIntroduction (zh CN)

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Development/Tutorials/Metadata/Nepomuk/RDFIntroduction


Nepomuk的RDF和本体
Tutorial Series   [[../|Nepomuk]]
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What's Next   [[../ResourceGenerator|Using the Nepomuk Resource Class Generator]],[[../DataLayout|Nepomuk的数据布局]]
Further Reading   [[../Resources|Resource Handling with Nepomuk]],

[[../AdvancedQueries|Advanced Queries with SPARQL]], Sebastian Trueg的Nepomuk博客

Nepomuk的资源描述框架（RDF）和本体（Ontologies）

这个指南基于 Sebastian Trueg 的博文 Nepomuk Appendix A - RDF for Dummies in a Nutshell。

在这儿讨论的所有本体随同 kdebase-runtime 一起安装，因此这些本体总是存在于 Nepomuk 数据仓库中，另外，他们的资源 URI 可以通过 Soprano::Vocabulary namespace (NIE 除外，它可以简单的使用 Soprano 的 onto2vocabularyclass 建立。)

RDF - 资源描述框架

RDF describes a way of storing data. While "classical" databases are based on tables RDF data consists on triples and only triples. Each triple, called statement consists of 

subject - predicate - object

The subject is a resource, the predicate is a relation, and the object is either another resource or a literal value. A literal can be a string, integer, double, or any other type defined by XML Schema, and it is even possible to define custom literal types. Thus RDF can represent statements such as "Mary - is mother of - Carl", or "Mary - was born on - 1970-02-23". These are statements about things, hence RDF is a good technology for 元数据。

To reduce ambiguity, resources and relations need to be uniquely identified; for example, in statement above, to identify a particular "Mary", and also to distinguish the maternal relationship from "Baghdad - is mother of - all battles". Since RDF was born as a web technology all resources and relations are identified by a URI, Uniform Resource Identifier. (Hence they have a namespace often ending in a # and a name. Typically abbreviation such as foo:bar are used.) Thus, a dataset in RDF is basically a graph where resources are the nodes, predicates the links, and literals act as leaves.

RDF defines one important default property: rdf:type which allows to assign a type to a resource.

RDFS - RDF Schema

RDFS扩展了RDF，定义了一个资源和属性的集合，这个扩展基本上允许定义Ontology（本体）。RDFS不但定义了两个重要的类rdfs:Resource和 rdfs:Class 用来引入实例和类型的区别，而且定义了属性的层次结构：rdfs:subClassof 和 rdfs:subPropertyof ，rdfs:domain 和 rdfs:range 指定属性的细节。

这些扩展允许建立新类和属性，与面向对象编程非常类似，例如： 

@PREFIX foo: <http://foo.bar/types#>

foo:Human rdf:type rdfs:Class . //Human的类型是类
foo:Woman rdf:type rdfs:Class .  //Woman 的类型是类
foo:Woman rdfs:subClassOf foo:Human .  //Woman类是Human类的子类

foo:isMotherOf rdf:type rdf:Property . // isMotherof 的类型是属性
foo:isMotherOf rdfs:domain foo:Woman . // isMotherof 隶属Woman域
foo:isMotherOf rdfs:range foo:Human . // isMotherof 用于Human范围

foo:Mary rdf:type foo:Woman .  // Mary的类型是 Woman
foo:Mary foo:isMotherOf foo:Carl .  //一个Thing的三元语句描述

这是一个如何使用RDFS定义一个本体的简单例子（使用Turtle 语言）。在RDFS中最后两个重要的谓语（关系）是 rdfs:label and rdfs:comment ，为任意资源定义可读性标签和注释。

NRL：Nepomuk 表示语言（Nepomuk Representation Language）

Nepomuk开发NRL是为了扩展RDFS。对于NRL，我不准备详细解释它的一切，但我会就目前KDE而言非常重要的信息进行解释。

NRL最为重要的改变是从三元组描述到四"元组"描述的改变，第四个参数是已定义（存储）的用语句描述的graph（可能为空），这个graph （在Soprano中称为 context） 是这样一种资源，它可以对描述语句进行分组，允许对描述语句组进行追加。NRL定义了一组 graph（context）类型，其中很重要的是：nrl:InstanceBase 和 nrl:Ontology。第一个定义了graph 包含的实例，第二个，你猜对了，它定义了包含类型和谓语的graphs。

为了使之更加清楚，我们用NRL扩展上面的例子： 

@PREFIX foo: <http://foo.bar/types#>

foo:graph1 rdf:type nrl:Ontology .  // 资源foo:graph1的类型是本体
foo:graph2 rdf:type nrl:InstanceBase . // 资源foo:graph2的类型是基础实例

foo:Human rdf:type rdfs:Class foo:graph1. // 资源foo:Human类型是类，是本体 
foo:Woman rdf:type rdfs:Class foo:graph1. // 资源foo:Woman类型是类，是本体
foo:Woman rdfs:subClassOf foo:Human foo:graph1 . //资源foot:Woman是foo:Human的子类，是个本体

foo:isMotherOf rdf:type rdf:Property foo:graph1 . // 资源foo:isMotherOf的类型是属性，是个本体
foo:isMotherOf rdfs:domain foo:Woman foo:graph1 . // 资源foo:isMotherOf的作用域为foo:Woman，是个本体
foo:isMotherOf rdfs:range foo:Human foo:graph1 . // 资源foo:isMotherOf的范围是foo:Human，是个本体

foo:Mary rdf:type foo:Woman foo:graph2 . //资源Mary的类型为foo:Woman,是一个基础实例
foo:Mary foo:isMotherOf foo:Carl foo:graph2 . //资源Mary和资源foo:Carl是foo:isMotherOf的关系，是一个基础实例

但是，上述例子不能展现实体和本体的所有区别

NAO：Nepomuk标签本体（Nepomuk Annotation Ontology）

NAO already defines resource types and properties you already encountered in KDE: nao:Tag or nao:rating. But it also defines nao:created which is a property that assigns an xls:dateTime literal to a resource, in our case a graph. This way we store information about when a piece of information was inserted into the Nepomuk repository. 

foo:graph1 nao:created "2008-02-12T14:43.022Z"^^<http://www.w3.org/2001/XMLSchema#dateTime> .

NIE本体（Nepomuk Information Element）

The NIE ontologies describe desktop resources like files, folders, emails, contacts, IM messages, and so on. It is used by file indexing systems like Strigi or Tracker to describe the extracted metadata.

Xesam - 桌面文件的元数据本体 因NIE而废除

Xesam is an ontology that has been developed in regards to desktop file indexing tools such as Strigi. It tries to define classes/types and properties for most of the metadata that occurs in files on the desktop. Simple examples include id3 tags or image size or even email data such as sender or recipient. File Metadata indexed by Strigi on the KDE desktop is stored in the Nepomuk repository using Xesam classes and properties.

SPARQL - RDF查询语言

SPARQL is what we use to query the RDF repository. Its syntax has been designed close to SQL but since it is quite young it is by far not as powerful yet.

Anyway, this is how a simple query that retrieves the mother of Carl looks like: 

prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix foo: <http://foo.bar/types#>

select ?r where { ?r foo:isMotherOf foo:Carl . }

或者如果我们把NRL算进来： 

prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
prefix foo: <http://foo.bar/types#>
prefix nrl: <http://semanticdesktop.org/ontologies/2007/08/15/nrl#>

select ?r where { graph ?g { ?r foo:isMotherOf foo:Carl . } . ?g rdf:type nrl:InstanceBase . }

A very valuable piece of documentation is the SPARQL quick reference.

其他/定制本体

The ontologies mentioned here form the basis of the data in Nepomuk bu they cannot describe every aspect necessary. If you want to store your own data in Nepomuk and link it with other information it is recommended to follow the following process:

  • Check if existing standard ontologies provide the classes and properties you need (or some of them). Many, including NRL and NAO, reside at http://www.semanticdesktop.org/ontologies/.
  • If not, contact the Oscaf project with what you need to get help with the discussions and development
  • If that does not help either, start your own ontology and if possible propose it as a standard with Oscaf.
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