Event logs play a fundamental role in enabling data-driven business process analysis. Traditionally, these logs track events related to a single object, known as the case, limiting the scope of analysis. Recent advancements, such as Object-Centric Event Logs (OCEL) and Event Knowledge Graphs (EKG), capture better how events relate to multiple objects. However, attributes of objects can change over time, which was not initially considered in OCEL or EKG. While OCEL 2.0 has addressed some of these limitations, there remains a research gap concerning how attribute changes should be accommodated in EKG and how OCEL 2.0 logs can be transformed into EKG. This paper fills this gap by introducing Temporal Event Knowledge Graphs (tEKG) and defining an algorithm to convert an OCEL 2.0 log to a tEKG.
Detecting Dynamic Relationships in Object-Centric Event Logs
INESC-ID/Instituto Superior Técnico, Universidade de Lisboa（里斯本大学高等技术学院）；Free University of Bozen-Bolzano（博尔扎诺自由大学）；Hasso Plattner Institute, University of Potsdam（波茨坦大学哈索·普拉特纳研究所）
How Many and What Types of SPARQL Queries can be Answered through Zero-Knowledge Link Traversal?
当前查询Web of Data的实际方法是通过SPARQL协议，其中客户端通过SPARQL端点向服务器发送查询。与HTTP服务器相反，提供和维护一个健壮和可靠的端点需要大量的工作，而不是所有的发布者都愿意或能够做到。另一种查询评估方法是通过链接遍历，其中通过实时的解引用在线Web资源（URI）来回答查询。虽然已经提出了用于这种基于查找的查询评估方法的几种方法，但是不存在对可以在实况Web上直接回答的查询的类型（模式）的分析，而不访问本地或远程端点，并且没有可用数据源的先验知识。在本文中，我们首先提供了一种方法来检查是否可以通过零知识链接遍历（而不访问端点）回答SPARQL查询（SPARQL端点上进行评估），并分析了一个大语料库的真实SPARQL查询日志的频率和分布的可回答和不可回答的查询模式。随后，我们提供了一个算法，用于将应答查询转换为绕过端点的SPARQL-LD查询。我们报告的转换查询的效率的实验结果，并讨论了这种查询评估方法的优点和局限性。
