International Journal of Business Process Integration and Management 

About: International Journal of Business Process Integration and Management is an academic journal published by Inderscience Publishers. The journal publishes majorly in the area(s): Business process modeling & Business process. It has an ISSN identifier of 1741-8763. Over the lifetime, 208 publications have been published receiving 2800 citations. The journal is also known as: IJBPIM & Business process integration and management.

Describing and reasoning on Web Services using process algebra

Abstract: We argue that essential facets of Web Services (WSs), and especially, those useful to understand their interaction, are best described using process-algebraic notations. WS description and execution languages such as BPEL are essentially process description languages; they are based on primitives for behaviour description and message exchange, which can also be found in more abstract languages such as Process Algebras (PAs). One legitimate question is therefore whether the WSs community can benefit from the sophisticated languages and tools developed in the PA area. Our investigations suggest a positive answer and we claim that PAs provide solutions to a number of challenges raised by the WSs paradigm, among which are central issues of orchestration and choreography. We show on a case study that readily available tools based on PA are effective at verifying that compositions of services obtained by choreography and orchestration conform their requirements and respect properties. We suggest a general frame...

Contextualisation of business processes

Abstract: Flexibility has emerged as an important requirement in the design of business processes. Research on process flexibility, however, has traditionally been focused on the intrinsic capability of a process to adapt to a new environment (e.g. workflow escalation, ad hoc modelling). This paper proposes to extend the existing body of research by studying the extrinsic drivers for process flexibility, that is, the root causes that actually drive the demand for flexible business processes. The drivers for flexibility can be found in the context of a process and may include among others time, location, weather, legislation or performance requirements. We argue for a stronger and more explicit consideration of these contextual factors in the design of business processes in order to make processes more adaptive. This paper discusses why context matters and how context can be conceptualised, classified and integrated with existing approaches to business process modelling. We use a goal-oriented process modelling approach to be able to identify relevant context elements and propose a framework and a meta model for classifying relevant context. These extensions are an essential foundation for the definition and implementation of truly agile processes, and as such of high practical and theoretical value.

Using Process Mining to Learn from Process Changes in Evolutionary Systems

Abstract: Traditional information systems struggle with the requirement to provide flexibility and process support while still enforcing some degree of control. Accordingly, adaptive Process Management Systems (PMSs) have emerged that provide some flexibility by enabling dynamic process changes during runtime. Based on the assumption that these process changes are recorded explicitly, we present two techniques for mining change logs in adaptive PMSs; that is, we do not only analyse the execution logs of the operational processes, but also consider the adaptations made at the process instance level. The change processes discovered through process mining provide an aggregated overview of all changes that happened so far. Using process mining as an analysis tool we show in this paper how better support can be provided for truly flexible processes by understanding when and why process changes become necessary.

Towards supporting the life cycle of large scale scientific experiments

Abstract: One of the main challenges of scientific experiments is to allow scientists to manage and exchange their scientific computational resources (data, programs, models, etc.). The effective management of such experiments requires a specific set of cardinal facilities, such as experiment specification techniques, workflow derivation heuristics and provenance mechanisms. These facilities may characterise the experiment life cycle into three phases: composition, execution, and analysis. Works concerned with supporting scientific workflows are mainly concerned with the execution and analysis phase. Therefore, they fail to support the scientific experiment throughout its life cycle as a set of integrated experimentation technologies. In large scale experiments this represents a research challenge. We propose an approach for managing large scale experiments based on provenance gathering during all phases of the life cycle. We foresee that such approach may aid scientists to have more control on the trials of the scientific experiment.

Activity patterns in process-aware information systems: basic concepts and empirical evidence

Abstract: Recently, a variety of workflow patterns have been suggested for capturing different aspects in process-aware information systems (PAISs), including control and data flow, resources, process change and exception handling. All these patterns are highly relevant for implementing PAISs and for designing process modelling languages. However, current patterns provide only a partial answer to the question of which business functions a designer might want to reuse when modelling processes. This paper presents a revised version of a collection of activity patterns to deal with this challenge. Each of them is related to a recurrent business function as it can be frequently found in process models (e.g., task execution request, notification, approval). We describe the identified activity patterns and their variants in detail. The main purpose of our paper is to discuss results from empirical studies in which we analysed more than 200 process models in order to evidence the practical relevance of the patterns. This includes a detailed analysis of the context in which activity patterns occur as well as the frequency of this occurrence. These empirical findings can be used for the design of more intelligent, pattern-based process modelling tools.