Developing provenance-aware query systems: an occurrence-centric approach

被引:1
作者
Dominguez, Eladio [1 ]
Perez, Beatriz [2 ]
Rubio, Angel Luis [2 ]
Zapata, Maria A. [1 ]
Allue, Alberto [3 ]
Lopez, Antonio [3 ]
机构
[1] Univ Zaragoza, Dept Informat & Ingn Sistemas, Zaragoza, Spain
[2] Univ La Rioja, Dept Matemat & Computac, La Rioja, Spain
[3] Infozara Consultoria Informat, Zaragoza, Spain
关键词
Provenance; Monitoring; Information retrieval; Protocol; History; Health; BUSINESS; MODEL;
D O I
10.1007/s10115-016-0950-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In recent years, research on provenance has increased exponentially, and such studies in the field of business process monitoring have been especially remarkable. Business process monitoring deals with recording information about the actual execution of processes to then extract valuable knowledge that can be utilized for business process quality improvement. In prior research, we developed an occurrence-centric approach built on our notion of occurrence that provides a holistic perspective of system dynamics. Based on this concept, more complex structures are defined herein, namely Occurrence Base (OcBase) and Occurrence Management System (OcSystem), which serve as scaffolding to develop business process monitoring systems. This paper focuses primarily on the critical provenance task of extracting valuable knowledge from such systems by proposing an Occurrence Query Framework that includes the definition of an Occurrence Base Metamodel and an Occurrence Query Language based on this metamodel. Our framework provides a way of working for the construction of business process monitoring systems that are provenance aware. As a proof of concept, a tool implementing the various components of the framework is presented. This tool has been tested against a real system in the context of biobanks.
引用
收藏
页码:661 / 688
页数:28
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