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


Tutorial Series   [[../|Nepomuk]]
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


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:Resourcerdfs: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:subClassofrdfs:subPropertyofrdfs:domainrdfs:range 指定属性的细节。


@PREFIX foo: <>

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)


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:InstanceBasenrl: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。


@PREFIX foo: <>

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


NAO:Nepomuk 标注本体(Nepomuk Annotation Ontology)

你在KDE已经遇到过的由NAO定义的资源类型和属性是:nao:Tagnao:rating 。其实NAO也定义了 nao:created 属性,它为资源 (在下面的例子里是一个graph)分配一个 xls:dateTime 类型数据。 当一些信息被加入到Nepomuk库时,我们用这个方法存储相关信息。

foo:graph1 nao:created "2008-02-12T14:43.022Z"^^<> .

NIE — Nepomuk 信息元素本体(Nepomuk Information Element)

NIE 本体描述桌面资源文件像文件,文件夹,电子邮件,联系人,即时消息等等,它在文件索引系统诸如 Strigi 或者 tracker中用于描述提取的元数据。

Xesam - 桌面文件的元数据本体 因采用NIE而过时

Xesam是一个应用于strigi 索引桌面文件而开发出来的本体,它试图对桌面应用的大多数文件类型元数据定义类/类型和属性。简单的例子如id3标签或图像大小,或如发信人和收信任等电子邮件数据,在KDE桌面系统上strigi对文件元数据的检索结果使用Xesam定义的类和属性等数据保存在Nepomuk数据仓库内。


我们用SPARQL 查询RDF 数据库,它的语句格式被设计成近似SQL,但因为它迄今为止十分年轻,所以还不是很强大。

尽管这样,搜索“the mother of carl”这样简单的查询大致如下:

prefix rdf: <>
prefix foo: <>

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

或者如果采用NRL :

prefix rdf: <>
prefix foo: <>
prefix nrl: <>

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

SPARQL quick reference是一份非常有价值的文档。


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
  • 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.

This page was last edited on 23 June 2013, at 13:35. Content is available under Creative Commons License SA 4.0 unless otherwise noted.