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——进行了形式化描述、表达能力及复杂性分析。形式化分析表明，SIGNAL的核心能力（称为SIGNAL合取核心）比关系代数更具表达能力，因此无法由标准关系数据库完全捕捉。我们通过归约至半正定Datalog给出了其表达能力的上界，这也导致了评估SIGNAL合取核心查询的数据复杂性的P难题上界。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更普遍结构化查询语言之间的根本差异，并为扩展工业级最新过程数据查询能力的现有基础提供了严谨的理论支持。