Semantic Business Process Management Research Articles

An Open Platform for Modeling Method Conceptualization: The OMiLAB Digital Ecosystem

This paper motivates, describes, demonstrates in use, and evaluates the Open Models Laboratory (OMiLAB) - an open digital ecosystem designed to support conceptualization and operationalization of conceptual modeling methods. The OMiLAB ecosystem is motivated by a generalized understanding of model value and is targeted to research and education stakeholders fulfilling various roles in a modeling method's lifecycle - modelers, domain experts, methodologists, modeling software developers, knowledge workers, model-driven software engineers etc. While much is reported on novel modeling methods and tools for various domains, only limited knowledge is available on the conceptualization of such methods by means of a full-fledged dedicated open ecosystem and a methodology that facilitates entry points for novices, as well as an open innovation space for experienced stakeholders. This gap is maintained by the lack of an open process and platform for (a) conducting research in the field of modeling method design, (b) developing agile modeling tools and model-driven digital products, and (c) experimentation with, and dissemination of such methods & related prototypes. OMiLAB incorporates principles, practices, procedures, tools and services required to address the forecited issues, as it aims to be the operational deployment for a conceptualization and operationalization process built on several pillars: (a) a granularly defined concept whose building blocks can be customized for the domain of choice; (b) an Agile Modeling Method Engineering framework supporting quick prototyping of modeling tools; (c) a model-aware “Digital Product Design Lab”; and (d) dissemination channels for reaching a global community. Demonstration and evaluation of the OMiLAB in research is hereby carried out by two selected application cases for domains- and case-specific requirements: the iStar case for requirements engineering, and the EnterKnow case for semantic business process management systems. These two cases show the broad spectrum of modeling methods realized within the OMiLAB, ranging from conventional conceptual modeling methods (iStar) toward the model-aware development and operationalization of Digital Products (EnterKnow). Besides these exemplary cases, OMiLAB has proven to effectively satisfy requirements raised by almost 50 modeling methods, supporting researchers in designing novel modeling methods, developing tools and disseminating outcomes. The educational impact of the OMiLAB is also measured in terms of international visibility and feedback from the NEMO Summer School series, whose attendants directly interact with both the physical and virtual environments of the OMiLAB.

Enfoque para la gestión de procesos de negocio semánticos utilizando ontologías

Las oportunidades de mercado actuales y los avances en las Tecnologías de Información y Comunicaciones, alientan a las organizaciones a establecer redes de colaboración. Las redes de colaboración consisten en relaciones entre organizaciones por un período de tiempo determinado para alcanzar objetivos de negocio comunes, lo cual implica una integración orientada a procesos entre organizaciones heterogéneas y autónomas, que debe ser alcanzada tanto en una perspectiva de negocio como en una perspectiva de implementación. La Gestión de Procesos de Negocio Semánticos es un enfoque que permite incrementar el nivel de automatización mediante el uso de ontologías y servicios Web, lo cual permite enfrentar los retos actuales de la Gestión de Procesos de Negocio, tales como descubrimiento de servicios, reutilización de procesos, y análisis de los procesos ejecutados. En este trabajo de investigación se presenta el diseño e implementación de un modelo de procesos de negocio, el cual es modelado usando el lenguaje BPMN y anotado semánticamente con conceptos de la ontología BPMO, permitiendo llevar a cabo el descubrimiento de servicios Web, fragmentación de procesos y reutilización de procesos, así como consultas sobre las instancias del modelo de proceso generadas mediante un razonador automático.

Ontological approach to enhance results of business process mining and analysis

PurposeThe purpose of this paper is to propose a solution to the problem of a lack of machine processable semantics in business process management.Design/methodology/approachThe paper introduces a methodology that combines domain and company‐specific ontologies and databases to obtain multiple levels of abstraction for process mining and analysis. The authors valuated this approach with a real case study from the apparel domain, using a prototype system and techniques developed in the Process Mining Framework (ProM). The results of this approach are compared with similar research.FindingsSemantically enriching process execution data can successfully raise analysis from the syntactic to the semantic level, and enable multiple perspectives of analysis on business processes. Combining this approach with complementary research in semantic business process management (SBPM) can provide results comparable to multidimensional analysis in data warehouse and on line analytical processing (OLAP) technologies.Originality/valueThe approach and prototype described in this paper improve the richness of semantics available for open‐source process mining and analysis tools like ProM, and the richness and detail of the resulting analysis.

Ontology-based approaches for cross-enterprise collaboration: a literature review on semantic business process management

Based on an in-depth analysis of the existing approaches in applying semantic technologies to business process management (BPM) research in the perspective of cross-enterprise collaboration or so-called business-to-business integration, we analyse, discuss and compare methodologies, applications and best practices of the surveyed approaches with the proposed criteria. This article identifies various relevant research directions in semantic BPM (SBPM). Founded on the result of our investigation, we summarise the state of art of SBPM. We also address areas and directions for further research activities.

Analyzing behavioral properties of semantic business processes with parametric data

One of the basic problems in (semantic) business process management concerns the behavioral analysis at design time so that only correct processes are exposed. Although this analysis requires the semantic propagation of data and system preconditions through processes and between processes to be considered, some concrete data are usually obtained at runtime and cannot be used in early process development phases. This paper proposes Parametric Unary RDF Annotated Petri Net Systems (P-U-RDF-PN Systems) as a formalism to alleviate this problem. The formalism allows analyzing behavioral properties of semantic business processes at design time. Parametric values are used to represent the data that will be obtained at runtime, allowing to also consider them in the analysis phase. The paper formally defines the semantics of the formalism in terms of enabling and firing of transitions as well as the concept of reachability graph. It also presents how to compute and analyze this parametric reachability graph. The analysis is based on an adaption of model checking techniques, being temporal logic the formalism used to specify the system properties to be analyzed. Finally, an implementation prototype using RDF and SPARQL tools and a Satisfiability Modulo Theories solver is presented, with some experiments evaluating how scalable the prototype is. Copyright © 2010 John Wiley & Sons, Ltd.

Policy-enabled goal-oriented requirements engineering for semantic Business Process Management

Business process management (BPM) develops into a new paradigm for enterprise computing that uses information technology (IT) not only to support or execute business processes, but also to continuously monitor and improve these processes in order to better achieve business objectives. BPM’s variant Semantic Business Process Management (SBPM) is meant to further close the gap between business and IT by attaching business semantics to the IT artefacts used for BPM. A current problem in SBPM is that the specification of the business requirements that the business processes must respond to and that follow from the enterprise’s strategic decisions, is not fully integrated with the design of the business processes themselves. In this paper we propose an approach in which business requirements for business processes are formally modelled and the skeleton of the designs of these business processes is automatically generated from these models. The approach presented here focuses upon the modelling of policies (i.e. a kind of business requirements for business processes) and on the subsequent design of business processes that comply to these policies. A first contribution is extending an existing goal-oriented requirements specification language, i.e. Formal Tropos (FT), to incorporate policies, called Policy-extended Formal Tropos (PFT). A second contribution is offering an automated transformation to create business process design skeletons out of the PFT models. The paper also reports upon a case study that was conducted as a first, though preliminary, empirical test of our approach.

Semantic business process space for intelligent management of sales order business processes

A company's competitiveness relies heavily on its business processes and accurate knowledge to execute its business processes with agility and efficiency. Business Process Management (BPM) initially promised to provide the business world with suitable tools and techniques for successful BPM without help from the IT world. However, the current practice of BPM has several fundamental problems, including difficulty with automatic discovery and the integration of business processes across organizations. Understanding that the main cause of these problems lies in the lack of semantics on business process, we first define a variety of business process ontologies in order to build a semantic business process space (SBPS) for the limited area of sales order. We then explain how the SBPS satisfies the requirements for successful implementation of semantic BPM (SBPM) and demonstrate with a scenario how SBPM can be realized in the environment of SBPS. Our novel approach will reduce the time and cost necessary for the development of a new business process in a fast-changing environment and provide practitioners with useful insights into the proper implementation of the SBPM. Although our paper defines semantic business process knowledge for only a limited domain, its insights can be readily extended to other areas of business.

SEMPA – Ein Ansatz des Semantischen Prozessmanagements zur Planung von Prozessmodellen

Currently process modeling is mostly done manually. Therefore, the initial design of process models as well as changes to process models which are frequently necessary to react to new market developments or new regulations are time-consuming tasks. In this paper we introduce SEMPA, an approach for the partly automatic planning of process models. Using ontologies to semantically describe actions – as envisioned in Semantic Business Process Management –, a process model for a specified problem setting can be created automatically. In comparison to existing planning algorithms our approach creates process models including control structures and is able to cope with complex and numerical input and output parameters of actions. The prototypical implementation as well as an example taken from the financial services domain illustrate the practical benefit of our approach.