Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes

SCIFF is a framework thought to specify and verify interaction in open agent societies. The SCIFF language is equipped with a semantics based on abductive logic programming; SCIFF's operational component is a new abductive logic programming proof procedure, also named SCIFF, for reasoning with expectations in dynamic environments. In this article we present the declarative and operational semantics of the SCIFF language, and the termination, soundness, and completeness results of the SCIFF proof procedure, and we demonstrate SCIFF's possible application in the multiagent domain. (http://lia.deis.unibo.it/research/ socs/), and by the MIUR PRIN 2005 projects 2005-011293 (Specifica e verifica di protocolli di interazione fra agenti) and 2005-015491 (Vincoli e preferenze come formalismo unificante per l'analisi di sistemi informatici e la soluzione di problemi reali).

Service-oriented computing, an emerging paradigm for architecting and implementing business collaborations within and across organizational boundaries, is currently of interest to both software vendors and scientists. While the technologies for implementing and interconnecting basic services are reaching a good level of maturity, modeling service interaction from a global viewpoint, that is, representing service choreographies, is still an open challenge. The main problem is that, although declarativeness has been identified as a key feature, several proposed approaches specify choreographies by focusing on procedural aspects, leading to over-constrained and over-specified models.To overcome these limits, we propose to adopt DecSerFlow, a truly declarative language, to model choreographies. Thanks to its declarative nature, DecSerFlow semantics can be given in terms of logic-based languages. In particular, we present how DecSerFlow can be mapped onto Linear Temporal Logic and onto Abductive Logic Programming. We show how the mappings onto both formalisms can be concretely exploited to address the enactment of DecSerFlow models, to enrich its expressiveness and to perform a variety of different verification tasks. We illustrate the advantages of using a declarative language in conjunction with logic-based semantics by applying our approach to a running example. ACM Reference Format:Montali, M., Pesic, M., van der Aalst, W. M. P., Chesani, F., Mello, P., and Storari, S. 2010. Declarative specification and verification of service choreographies.

Today, large business processes are composed of smaller, autonomous, interconnected subsystems, achieving modularity and robustness. Quite often, these large processes comprise software components as well as human actors, they face highly dynamic environments and their subsystems are updated and evolve independently of each other. Due to their dynamic nature and complexity, it might be difficult, if not impossible, to ensure at design-time that such systems will always exhibit the desired/expected behaviors. This, in turn, triggers the need for runtime verification and monitoring facilities. These are needed to check whether the actual behavior complies with expected business constraints, internal/external regulations and desired best practices. In this work, we present Mobucon EC, a novel monitoring framework that tracks streams of events and continuously determines the state of business constraints. In Mobucon EC, business constraints are defined using the declarative language Declare. For the purpose of this work, Declare has been suitably extended to support quantitative time constraints and non-atomic, durative activities. The logic-based language Event Calculus (EC) has been adopted to provide a formal specification and semantics to Declare constraints, while a light-weight, logic programming-based EC tool supports dynamically reasoning about partial, evolving execution traces. To demonstrate the applicability of our approach, we describe a case study about maritime safety and security and provide a synthetic benchmark to evaluate its scalability.

The paper presents an approach for detecting vehicles in urban traffic scenes by means of rule-based reasoning on visual data. The strength of the approach is its formal separation between the low-level image processing modules (used for extracting visual data under various illumination conditions) and the high-level module, which provides a general-purpose knowledge-based framework for tracking vehicles in the scene. The image-processing modules extract visual data from the scene by spatio-temporal analysis during daytime, and by morphological analysis of headlights at night. The high-level module is designed as a forward chaining production rule system, working on symbolic data, i.e., vehicles and their attributes (area, pattern, direction, and others) and exploiting a set of heuristic rules tuned to urban traffic conditions. The synergy between the artificial intelligence techniques of the high-level and the low-level image analysis techniques provides the system with flexibility and robustness.