Business process management employs process models and event logs to represent the behavior of the information systems under study. Traditional case-centric notions consider the order of activities and events in isolated process instances. The emerging field of object-centric processes challenges this assumption by putting objects in the center. Object-centric process mining and modeling approaches identify the structure of co-evolving data objects that influence the behavior of an information system to provide a comprehensive view of the system behavior. Object-centricity has been investigated independently in process modeling and in process mining, which resulted in the coexistence of seemingly contradictory assumptions and definitions. As a community effort, this research manifesto relates and aligns existing terminologies, definitions, and perspectives to provide a common ground for current and future research in object-centric business process management. Based on the current state of research, we propose a conceptualization that sets process models and event logs in relation to the information system’s behavior and the execution data it generates. The conceptualization aims at aligning different terminologies and, thus, providing a basis to model and analyze behavioral characteristics. Building on this common ground, we identify open research challenges along the most relevant research areas in object-centric process management. For each research area, its current status is investigated and an outline of the most relevant research challenges is presented.

Background. Autonomous systems, whether AI-enabled or not, are ubiquitous and pervasive in our daily lives. While their adoption and use bring many benefits, they also pose significant ethical challenges. Objective. The objective of this work is to contribute a reference architecture for ethical-aware autonomous systems, focusing on their interaction and collaboration with humans, being them proactive, reactive or passive in the interaction with the systems. Method. To define the architecture, we analyzed scientific papers in the field, guidelines and recommendations, as well as laws and regulations. We then applied this acquired knowledge to build the reference architecture. The results of this work were validated through expert interviews and a scenario-based evaluation. Results. We contribute (i) a definition of ethical-aware autonomous systems, (ii) requirements for ethical-aware autonomous systems, and (iii) a reference architecture for ethical-aware autonomous systems. Our reference architecture is intended to help system and software engineers to design autonomous or intelligent systems that should interact and operate with humans in ethically sensitive contexts such as healthcare, social robotics, and assistive technologies. Conclusion. We believe that this work will assist software architects and engineers in designing and developing autonomous systems that should interact and collaborate with humans while respecting values important to individuals, society, and the environment.