Marco Montali

Process Mining Manifesto

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.

Declarative specification and verification of service choreographiess

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.

Monitoring business constraints with linear temporal logic: an approach based on colored automata

Todays information systems record real-time information about business processes. This enables the monitoring of business constraints at runtime. In this paper, we present a novel runtime verification framework based on linear temporal logic and colored automata. The framework continuously verifies compliance with respect to a predefined constraint model. Our approach is able to provide meaningful diagnostics even after a constraint is violated. This is important as in reality people and organizations will deviate and in many situations it is not desirable or even impossible to circumvent constraint violations. As demonstrated in this paper, there are several approaches to recover after the first constraint violation. Traditional approaches that simply check constraints are unable to recover after the first violation and still foresee (inevitable) future violations. The framework has been implemented in the process mining tool ProM.

Monitoring business constraints with the event calculus

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.

Specification and Verification of Declarative Open Interaction Models - A Logic-Based Approach

The advent of distributed and heterogeneous systems has laid the foundation for the birth of new architectural paradigms, in which many separated and autonomous entities collaborate and interact to the aim of achieving complex strategic goals, impossible to be accomplished on their own. A non exhaustive list of systems targeted by such paradigms includes Business Process Management, Clinical Guidelines and Careflow Protocols, Service-Oriented and Multi-Agent Systems. It is largely recognized that engineering these systems requires novel modeling techniques. In particular, many authors are claiming that an open, declarative perspective is needed to complement the closed, procedural nature of the state of the art specification languages. For example, the ConDec language has been recently proposed to target the declarative and open specification of Business Processes, overcoming the over-specification and over-constraining issues of classical procedural approaches. On the one hand, the success of such novel modeling languages strongly depends on their usability by non-IT savvy: they must provide an appealing, intuitive graphical front-end. On the other hand, they must be prone to verification, in order to guarantee the trustworthiness and reliability of the developed model, as well as to ensure that the actual executions of the system effectively comply with it. In this dissertation, we claim that Computational Logic is a suitable framework for dealing with the specification, verification, execution, monitoring and analysis of these systems. We propose to adopt an extended version of the ConDec language for specifying interaction models with a declarative, open flavor. We show how all the (extended) ConDec constructs can be automatically translated to the CLIMB Computational Logic-based language, and illustrate how its corresponding reasoning techniques can be successfully exploited to provide support and verification capabilities along the whole life cycle of the targeted systems.

Specification and Verification of Declarative Open Interaction Models

Give us 5 minutes and we will show you the best book to read today. This is it, the specification and verification of declarative open interaction models a logic based approach that will be your best choice for better reading book. Your five times will not spend wasted by reading this website. You can take the book as a source to make better concept. Referring the books that can be situated with your needs is sometime difficult. But here, this is so easy. You can find the best thing of book that you can read.

Foundations of data-aware process analysis: a database theory perspective

In this work we survey the research on foundations of data-aware (business) processes that has been carried out in the database theory community. We show that this community has indeed developed over the years a multi-faceted culture of merging data and processes. We argue that it is this community that should lay the foundations to solve, at least from the point of view of formal analysis, the dichotomy between data and processes still persisting in business process management.

Compliance monitoring in business processes

In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

Inducing declarative logic-based models from labeled traces

In this work we propose an approach for the automatic discoveryof logic-based models starting from a set of process executiontraces. The approach is based on a modified Inductive Logic Programmingalgorithm, capable of learning a set of declarative rules. The advantage of using a declarative description is twofold. First, theprocess is represented in an intuitive and easily readable way; second,a family of proof procedures associated to the chosen language can beused to support the monitoring and management of processes (conformancetesting, properties verification and interoperability checking, inparticular). The approach consists in first learning integrity constraints expressedas logical formulas and then translating them into a declarative graphicallanguage named DecSerFlow. We demonstrate the viability of the approach by applying it to a realdataset from a health case process and to an artificial dataset from ane-commerce protocol.

Exploiting Inductive Logic Programming Techniques for Declarative Process Mining

In the last few years, there has been a growing interest in the adoption of declarative paradigms for modeling and verifying process models. These paradigms provide an abstract and human understandable way of specifying constraints that must hold among activities executions rather than focusing on a specific procedural solution. Mining such declarative descriptions is still an open challenge. In this paper, we present a logic-based approach for tackling this problem. It relies on Inductive Logic Programming techniques and, in particular, on a modified version of the Inductive Constraint Logic algorithm. We investigate how, by properly tuning the learning algorithm, the approach can be adopted to mine models expressed in the ConDec notation, a graphical language for the declarative specification of business processes. Then, we sketch how such a mining framework has been concretely implemented as a ProM plug-in called DecMiner. We finally discuss the effectiveness of the approach by means of an example which shows the ability of the language to model concurrent activities and of DecMiner to learn such a model.