论文标题
Jekyll RDF：基于模板的链接数据发布，并最大程度地扩展性
Jekyll RDF: Template-Based Linked Data Publication with Minimized Effort and Maximum Scalability
论文作者
论文摘要
在过去的几十年中，网络已经从人类人类通信网络演变为复杂的人机相互作用网络。越来越多的数据可作为链接的数据可用，该数据允许机器“理解”数据，但是RDF并不是人类理解的。使用Jekyll RDF，我们提出了一种方法，可以通过将RDF数据集作为可自定义的静态HTML站点发布来缩小结构化数据和人类访问探索接口之间的差距。它由一个RDF资源映射系统组成，该系统可在其各自的IRI下提供资源，基于模式类的模板映射以及一个标记语言来定义模板以渲染自定义的资源页面。使用模板系统，可以为链接数据资源旁边的RDF数据创建特定域的浏览接口。这使内容管理和知识管理系统能够以高度可定制，低的努力和可扩展的方式为数据集提供，以被机器和人类消费。
Over the last decades the Web has evolved from a human-human communication network to a network of complex human-machine interactions. An increasing amount of data is available as Linked Data which allows machines to "understand" the data, but RDF is not meant to be understood by humans. With Jekyll RDF we present a method to close the gap between structured data and human accessible exploration interfaces by publishing RDF datasets as customizable static HTML sites. It consists of an RDF resource mapping system to serve the resources under their respective IRI, a template mapping based on schema classes, and a markup language to define templates to render customized resource pages. Using the template system, it is possible to create domain specific browsing interfaces for RDF data next to the Linked Data resources. This enables content management and knowledge management systems to serve datasets in a highly customizable, low effort, and scalable way to be consumed by machines as well as humans.
