Discourse network analysis: policy debates as dynamic networks

Political discourse is the verbal interaction between political actors. Political actors make normative claims about policies conditional on each other. This renders discourse a dynamic network phenomenon. Accordingly, the structure and dynamics of policy debates can be analyzed with a combination of content analysis and dynamic network analysis. After annotating statements of actors in text sources, networks can be created from these structured data, such as congruence or conflict networks at the actor or concept level, affiliation networks of actors and concept stances, and longitudinal versions of these networks. The resulting network data reveal important properties of a debate, such as the structure of advocacy coalitions or discourse coalitions, polarization and consensus formation, and underlying endogenous processes like popularity, reciprocity, or social balance. The added value of discourse network analysis over survey-based policy network research is that policy processes can be analyzed from a longitudinal perspective. Inferential techniques for understanding the micro-level processes governing political discourse are being developed

Architecture for Provenance Systems

This document covers the logical and process architectures of provenance systems. The logical architecture identifies key roles and their interactions, whereas the process architecture discusses distribution and security. A fundamental aspect of our presentation is its technology-independent nature, which makes it reusable: the principles that are exposed in this document may be applied to different technologies

Behavior models for software architecture

Monterey Phoenix (MP) is an approach to formal software system architecture specification based on behavior models. Architecture modeling focuses not only on the activities and interactions within the system, but also on the interactions between the system and its environment, providing an abstraction for interaction specification. The behavior of the system is defined as a set of events (event trace) with two basic relations: precedence and inclusion. The structure of possible event traces is specified using event grammars and other constraints organized into schemas. The separation of the interaction description from the components behavior is an essential MP feature. The schema framework is amenable to stepwise architecture refinement, reuse, composition, visualization, and multiple view extraction. The approach yields a basis for executable architecture specification supporting early testing and verification, systematic use case generation, and performance estimates with automated tools.Consortium for Robotics and Unmanned Systems Education and Research (CRUSER)Consortium for Robotics and Unmanned Systems Education and Research (CRUSER)Approved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

Towards a Generic Context Model for BPM

International audienceThis paper introduces a new context modeling approach for the business process management field. The proposed approach aims at identifying and formalizing the contextual knowledge relevant to business processes in order to be able to adapt business processes according to the context. This approach has the particularity to be generic and extensible; it can be integrated with many business process modeling approaches. It is based on ontologies and has two layers, i.e. generic layer and specific layer. Throughout the paper we compare the proposed approach with the related work in order to clearly demonstrate why we propose this approach

A network theoretic perspective of decision processes in complex construction projects

This paper proposes an approach to modelling and visualising decision processes in large complex construction projects by incorporating a network perspective. Computer modelling and visualisation of decision processes as social and task-entity networks makes possible the identification of key participants, critical tasks, latent networks, vulnerabilities and dynamics that impact upon complex decision situations. New advances in network theory can help reveal the ways in which social, organisational, political and technological relationships shape decision outcomes. By conceiving decision processes as a complex system and modelling this system using network-theoretic principles, it is possible to include a tremendous amount of information that has remained untapped by conventional qualitative, game-theoretic, and statistical approaches. This research contributes to the understanding of the strategic implications of decision processes as complex systems of interacting actors and problem tasks, and provides the technological means for supporting them. The approach has been verified through the development of an experimental network-theoretic system

Supporting adaptiveness of cyber-physical processes through action-based formalisms

Cyber Physical Processes (CPPs) refer to a new generation of business processes enacted in many application environments (e.g., emergency management, smart manufacturing, etc.), in which the presence of Internet-of-Things devices and embedded ICT systems (e.g., smartphones, sensors, actuators) strongly influences the coordination of the real-world entities (e.g., humans, robots, etc.) inhabitating such environments. A Process Management System (PMS) employed for executing CPPs is required to automatically adapt its running processes to anomalous situations and exogenous events by minimising any human intervention. In this paper, we tackle this issue by introducing an approach and an adaptive Cognitive PMS, called SmartPM, which combines process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on three well-established action-based formalisms developed for reasoning about actions in Artificial Intelligence (AI), including the situation calculus, IndiGolog and automated planning. Interestingly, the use of SmartPM does not require any expertise of the internal working of the AI tools involved in the system