Nowadays, Process-Aware Information Systems (PAISs) are widely used in all human activities, from classical ones (management of supply chain, postal tracking delivery, etc.) to very dynamic ones (health-care, emergency management, home automation, etc.). Every aspect of a business process involves a certain amount of knowledge, depending on several factors that range from the complexity of the domain of interest to the background and expertise of process participants.

Typically, knowledge-intensive processes are often only slightly structured and may not be completely captured by common business process models. Variations or divergence from structured, pre-defined reference models are common, due to autonomous user decisions and to unpredictable, emergent events and contextual changes that make the structure of the process significantly less rigid. The explicit flow of control may be driven and implicitly determined by the user's decision making or by contextual conditions, and it may be coupled with undesigned and unforeseen alternative activities and process fragments, dynamically determined at run-time. In the worst case, there is no pre-defined view of the knowledge-intensive process, and tasks are mainly discovered as the process unfolds.

In recent years, the increasing demand in effective solutions for knowledge-intensive processes has been reflected in the arising of various approaches (such as declarative and object-centric processes, artifact-centric systems, and adaptive case management) that emphasize how the integration of rules, data, control flow and user decisions may support the specification, analysis and enactment of flexible, knowledge-intensive business processes. From the foundational and practical viewpoint, the purpose of integrating such aspects with traditional business process management is a challenging, still largely open issue, which requires to reconsider the role of each process component together with the ways it interacts with the other components, and ultimately to reshape the entire process life-cycle.

The main focus of this workshop is to discuss novel and ongoing approaches, techniques and tools whose distinctive feature relies in the interplay between data, users and control flow aspects, to the aim of defining and understanding the knowledge dimension for business processes. We invite researchers from the fields of service-oriented computing, business process management, data management, artificial intelligence, knowledge representation and management to submit papers on the following aspects (not exclusive):

Modeling languages, notations and methods for knowledge representation and management in business processes and services
Variability and adaptability of business process models for knowledge-intensive tasks through automatic techniques
Resource management for knowledge-intensive business process modeling and support
User-oriented aspects of knowledge-intensive business processes and services
Declarative approaches for knowledge-intensive business processes
Verification, analysis and validation of knowledge-intensive business processes and services
Dynamic configuration; modeling by knowledge reuse
Run-time verification and monitoring
Knowledge-intensive business process/service support architectures and platforms
Machine learning for business process mining and monitoring
Artifact-centric business processes
Adaptive Case Management
Object-aware approaches for business process management
Case studies, empirical evaluations and experimentations