A growing number of Linked Open Data sources (from diverse provenances and about different domains) that can be freely browsed and searched to find and extract useful information have been made available. However, access to them is difficult for different reasons. This study addresses access issues concerning heterogeneity. It is common for datasets to describe the same or overlapping domains while using different vocabularies. Our study presents a transducer that transforms a SPARQL query suitably expressed in terms of the vocabularies used in a source dataset into another SPARQL query suitably expressed for a target dataset involving different vocabularies. The transformation is based on existing alignments between terms in different datasets. Whenever the transducer is unable to produce a semantically equivalent query because of the scarcity of term alignments, the transducer produces a semantic approximation of the query to avoid returning the empty answer to the user. Transformation across datasets is achieved through the management of a wide range of transformation rules. The feasibility of our proposal has been validated with a prototype implementation that processes queries that appear in well-known benchmarks and SPARQL endpoint logs. Results of the experiments show that the system is quite effective in achieving adequate transformations.

中文翻译：

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用于查询不完全对齐数据集的基于规则的传感器

越来越多的链接开放数据源（来自不同来源和不同领域）可以自由浏览和搜索以查找和提取有用信息。但是，由于不同的原因，很难访问它们。本研究解决了有关异质性的访问问题。数据集在使用不同的词汇表时描述相同或重叠的域是很常见的。我们的研究提出了一种转换器，它可以将根据源数据集中使用的词汇表适当表达的 SPARQL 查询转换为另一个针对涉及不同词汇表的目标数据集适当表达的 SPARQL 查询。转换基于不同数据集中的术语之间的现有对齐方式。每当转换器由于术语对齐的稀缺而无法产生语义等效的查询时，转换器就会产生查询的语义近似以避免将空答案返回给用户。跨数据集的转换是通过管理各种转换规则来实现的。我们提议的可行性已经通过原型实现得到验证，该原型实现处理出现在众所周知的基准和 SPARQL 端点日志中的查询。实验结果表明，该系统在实现足够的转换方面非常有效。我们提议的可行性已经通过原型实现得到验证，该原型实现处理出现在众所周知的基准和 SPARQL 端点日志中的查询。实验结果表明，该系统在实现足够的转换方面非常有效。我们提议的可行性已经通过原型实现得到验证，该原型实现处理出现在众所周知的基准和 SPARQL 端点日志中的查询。实验结果表明，该系统在实现足够的转换方面非常有效。