Discovery querying in linked open data
Discovery querying in linked open data
复制标题
链接开放数据中的发现查询
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
K. Sattler
中科院分区：
文献类型：
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作者：
Stefan Hagedorn;K. Sattler
机器无法解释和处理网页上发布的信息的问题导致了数据网的发展，仅次于文件网。这个想法被称为语义网，在语义网中，信息之间的链接以机器可以理解和解释的方式建立起来。随着它的发展，引入了新的应用程序来查询和处理这些关联数据。此外，还启动了开放数据计划，目标是在网络上免费发布政府、科学和文化数据。通常，这些开放数据以半结构化的形式提供，如CSV文件，但也可以转换为链接数据格式。有了这些链接的开放数据，就可以创建有效处理查询和查找信息的程序。
The problem of the inability of machines to interpret and process information published on web pages caused the development of a web of data, next to the web of documents. The idea is known as the Semantic Web, where links between information are established in a way that machines can understand and interpret. With its development, new applications were introduced to query and process this linked data. Additionally the open data initiative was launched with the goal to publish governmental, scientific, and cultural data freely accessible on the web. Often, this open data is offered in a semi-structured form, like CSV files, but can also be transformed into linked data format. With this linked open data, programs can be created that efficiently process queries and find information.
This work is supposed to integrate the support for discovery queries into an existing LOD cache engine. The goal is to develop a new approach that processes SPARQL queries and augments the result with discovered information from different (online) sources. Thus, the approach can help users to explore new information and knowledge more easily. Users should not worry about what particular data is stored locally and which identifiers are used. To do so, we plan to extend the rewriting process during logical optimization of SPARQL queries.