• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

About the Laboratory

Processes are everywhere and without information systems supporting these processes society would come to a grinding halt. When you rent a car, book a flight, buy a book, file a tax declaration, or transfer money there are process-aware information systems making this possible. A Process-Aware Information System (PAIS) is a software system that manages and executes operational processes involving people, applications, and/or information sources on the basis of process models. Example PAISs are Business Process Management (BPM) systems, Workflow Management (WFM) systems, Enterprise Resource Planning (ERP) systems, and case handling systems. Given the importance of such systems and related analysis techniques the National Research University Higher School of Economics (HSE) created the International Laboratory of Process-Aware Information Systems.

The laboratory was established in January 2013 and is supervised by professor Wil van der Aalst, one of the leading computer scientists in the world and the most influential researcher in areas such as business process management and process mining.

The notion of a process model is foundational for PAISs. A process model aims to capture the different ways in which a case (i.e., process instance) can be handled. A plethora of notations exists to model operational business processes (e.g., Petri nets, BPMN, UML, and EPCs). These notations have in common that processes are described in terms of activities (and possibly subprocesses). The ordering of these activities is modeled by describing causal dependencies. Moreover, the process model may also describe temporal properties, specify the creation and use of data, e.g., to model decisions, and stipulate the way that resources interact with the process (e.g., roles, allocation rules, and priorities).

Process mining techniques play a central role in the lab because of the incredible growth of event data. Process mining techniques can be used to extract knowledge from event data, discover models, align logs and models, measure conformance, diagnose bottlenecks, and predict future events. Today's processes leave many trails in data bases, audit trails, message logs, transaction logs, etc. Therefore, it makes sense to relate these event data to process models independent of their particular notation. Process models discovered based on the actual behavior tend to be very different from the process models made by humans. Moreover, conformance checking techniques often reveal important deviations between models and reality.

Traditionally, process models and system specifications tend to be static and disconnected from the real processes and system. Process mining techniques provide a means to establish a direct connection between processes, models, and systems. Moreover, event data can be used to breathe life into process models and unite domain experts, IT experts, managers and users of PAISs.

HSE’s International Laboratory of Process-Aware Information Systems aims to address urgent challenges related to business process management, process mining, and information systems development. The laboratory uses a mixture of formal methods (e.g., Petri nets and other models for concurrency), data-driven analysis (data/process mining), and systems engineering.





 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!