This paper presents a formalisation and expressivity and complexity analysis of SIGNAL, an industry-scale query language for analysing business process event logs. The formal analysis shows that the core capabilities of SIGNAL, which we refer to as the SIGNAL Conjunctive Core, are more expressive than relational algebra and thus not captured by standard relational databases. We do provide an upper-bound on the expressiveness via a reduction to semi-positive Datalog, which also leads to an upper bound of P-hard for the data complexity of evaluating SIGNAL Conjunctive Core queries. The findings provide first insights into how real-world process query languages are fundamentally different from the more generally prevalent structured query languages for querying relational databases and provide a rigorous foundation for extending the existing capabilities of the industry-scale state-of-the-art of process data querying.

翻译：本文对SIGNAL——一种用于分析业务流程事件日志的工业级查询语言——进行了形式化、表达能力及复杂性分析。形式化分析表明，SIGNAL的核心能力（我们称之为SIGNAL连接核心）在表达能力上超越关系代数，因此无法由标准关系数据库直接实现。我们通过归约到半正定Datalog给出了其表达能力上界，同时得出评估SIGNAL连接核心查询的数据复杂性为P-hard的上界。这些发现首次揭示了实际过程查询语言与查询关系数据库的通用结构化查询语言之间的根本差异，并为扩展现有工业级过程数据查询能力提供了严格的理论基础。