弥合工业与语义网之间的技术鸿沟：从RDF生成数据库和服务器代码
Bridging the Technology Gap Between Industry and Semantic Web: Generating Databases and Server Code From RDF
摘要：
尽管语义网领域取得了巨大的进步，但工业界很少采用语义网技术及其存储和查询概念。相反，通常部署关系数据库（RDB）来存储通过REST接口访问的业务关键型数据。然而，一些企业将极大地受益于语义Web相关的数据集，这些数据集通常用资源描述框架（RDF）表示。为了弥合这一技术差距，我们提出了一种全自动的方法，可以生成合适的RDB模型，并使用REST API来访问它们。在我们的评估中，从不同的RDF数据集生成的数据库进行检查和比较。我们的研究结果表明，数据库充分反映了他们的同行，而API是能够重现相当简单的SPARQL查询。确定了改进的潜力，例如，减少生成的数据库中的数据冗余。
英文摘要：
Despite great advances in the area of Semantic Web, industry rather seldom adopts Semantic Web technologies and their storage and query concepts. Instead, relational databases (RDB) are often deployed to store business-critical data, which are accessed via REST interfaces. Yet, some enterprises would greatly benefit from Semantic Web related datasets which are usually represented with the Resource Description Framework (RDF). To bridge this technology gap, we propose a fully automatic approach that generates suitable RDB models with REST APIs to access them. In our evaluation, generated databases from different RDF datasets are examined and compared. Our findings show that the databases sufficiently reflect their counterparts while the API is able to reproduce rather simple SPARQL queries. Potentials for improvements are identified, for example, the reduction of data redundancies in generated databases.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
