Although the amount of RDF data has been steadily increasing over the years, the majority of information on the Web is still residing in other formats, and is often not accessible to Semantic Web services. A lot of this data is available through APIs serving JSON documents. In this work we propose a way of extending SPARQL with the option to consume JSON APIs and integrate this information into SPARQL query answers, obtaining a language that combines data from the “traditional” Web to the Semantic Web. Our proposal is based on an extension of the SERVICE operator with the ability to connect to JSON APIs. With the aim of evaluating these queries as efficiently as possible, we show that the main bottleneck is the amount of API requests, and present an algorithm that produces “worst-case optimal” query plans that reduce the number of requests as much as possible. We note that the analysis of this algorithm is by a reduction to an algorithm for evaluating relational queries with access methods with the minimal number of access queries, which is of independent interest. We show the superiority of the worst-case optimal approach in a series of experiments that take existing SPARQL benchmarks, and augment them with the ability to connect to JSON APIs in order to obtain additional information.

尽管这些年来RDF数据量一直在稳定增长，但是Web上的大多数信息仍以其他格式存在，并且语义Web服务通常无法访问。可以通过提供JSON文档的API获得大量此类数据。在这项工作中，我们提出了一种扩展SPARQL的方法，可以使用JSON API，并将此信息集成到SPARQL查询答案中，从而获得一种将数据从“传统” Web到语义Web进行组合的语言。我们的建议基于SERVICE运算符的扩展，具有连接到JSON API的能力。为了尽可能有效地评估这些查询，我们显示了主要瓶颈是API请求的数量，并提出了一种算法，该算法可生成“最坏情况下最佳”的查询计划，从而尽可能减少请求的数量。我们注意到，对该算法的分析是通过简化为一种用于评估关系查询的算法，该算法使用最少访问次数的访问方法来评估关系查询，这是个人关注的问题。我们在采用现有SPARQL基准的一系列实验中展示了最坏情况最优方法的优越性，并通过连接到JSON API的能力增强了基准以获取更多信息。