Linked Data (LD) as a web--based technology enables in principle the seamless, machine--supported integration, interplay and augmentation of all kinds of knowledge, into what has been labeled a huge knowledge graph. Despite decades of web technology and, more recently, the LD approach, the task to fully exploit these new technologies in the public domain is only commencing. One specific challenge is to transfer techniques developed preweb to order our knowledge into the realm of Linked Open Data (LOD) This paper illustrates two different models in which a general analytico--synthetic classification can be published and made available as LD. In both cases, an LD solution deals with the intricacies of a pre--coordinated indexing language.
翻译:链接数据(LD)是一种基于网络的技术,它原则上能够将各种知识的无缝、机器支持的整合、互动和扩展纳入一个被贴上标签的巨大知识图中。尽管有数十年的网络技术,而且最近还采用了LD方法,但在公共领域充分利用这些新技术的任务才刚刚开始。一个具体的挑战是如何将开发的预选技术转让到链接开放数据(LOD)领域。本文说明了两种不同的模式,在这两种模式中,一般的分析性合成分类可以作为LD公布和提供。在这两种情况下,LD解决方案都涉及事先协调的索引语言的复杂性。