Semantic Business Process Research Articles

Execution of Knowledge-Intensive Processes by Utilizing Ontology-Based Reasoning

Modeling and executing knowledge-intensive processes (KiPs) are challenging with state-of-the-art approaches, and the specific demands of KiPs are the subject of ongoing research. In this context, little attention has been paid to the ontology-driven combination of data-centric and semantic business process modeling, which finds additional motivation by enabling the division of labor between humans and artificial intelligence. Such approaches have characteristics that could allow support for KiPs based on the inferencing capabilities of reasoners. We confirm this as we show that reasoners can infer the executability of tasks based on a currently researched ontology- and data-driven business process model (ODD-BP model). Further support for KiPs by the proposed inference mechanism results from its ability to infer the relevance of tasks, depending on the extent to which their execution would contribute to process progress. Besides these contributions along with the execution perspective (start-to-end direction), we will also show how our approach can help to reach specific process goals by inferring the relevance of process elements regarding their support to achieve such goals (end-to-start direction). The elements with the most valuable process progress can be identified in the intersection of both, the execution and goal perspective. This paper will introduce this new approach and verifies its practicability with an evaluation of a KiP in the field of emergency call centers.

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.

An Automated Method for the Construction of Semantic Business Process Patterns

The effectiveness of reuse in the development of software prompted researchers to look for reuse techniques for business process modelling. Indeed, a variety of reusable business artefact types has been proposed during the last decade. Among the recently proposed reuse artefact types, semantic business process patterns (SB2Ps) offer process patterns that encapsulate knowledge and commonly used practices in a particular domain. The design using an SB2P provides for the adaptation of these practices and it offers guidance on possible variations. This paper presents an automated method to construct SB2P starting from a set of process models in a given domain. The proposed method has the merit of accounting for the semantic, structural and behavioural information of the initial models. In addition, it produces process patterns where common fragments are distinguished from variation points, which assists business process designers in reusing an SB2P to meet their requirements. The method is illustrated through a case study in the cost accounting domain.

An automated method for the construction of semantic business process patterns

An automated method for the construction of semantic business process patterns

Detecting potential weaknesses in business processes

Purpose – Automating the task of identifying process weaknesses using process models is promising, as many organizations have to manage a large amount of process models. The purpose of this paper is to introduce a pattern-based approach for automatically detecting potential process weaknesses in semantic process models, thus supporting the task of business process improvement. Design/methodology/approach – Based on design research, combined with a case study, the authors explore the design, application and evaluation of a pattern-based process weakness detection approach within the setting of a real-life case study in a German bank. Findings – Business process weakness detection can be automated to a remarkable extent using pattern matching and a semantic business process modeling language. A case study provided evidence that such an approach highly supports business process analysts. Research limitations/implications – The presented approach is limited by the fact that not every potential process weakness detected by pattern matching is really a weakness but just gives the impression to be one. Hence, after detecting a weakness, analysts still have to decide on its authenticity. Practical implications – Applying weakness patterns to semantic process models via pattern matching allows organizations to automatically and efficiently identify process improvement potentials. Hence, this research helps to avoid time- and resource-consuming manual analysis of process model landscapes. Originality/value – The approach is not restricted to a single modeling language. Furthermore, by applying the pattern matching approach to a semantic modeling language, the authors avoid ambiguous search results. A case study proves the usefulness of the approach.

Semantic composition of business processes using Armstrong's Axioms

AbstractLack of sufficient semantic description in the content of Web services makes it difficult to find and compose suitable Web services during analysis, search, and matching processes. Semantic Web Services are Web services that have been enhanced with formal semantic description, which provides well-defined meaning. Due to insertion of semantics, meeting user demands will be made possible through logical deductions achieving resolutions automatically. We have developed an inference-based semantic business process composition agent (SCA) that employs inference techniques. The semantic composition agent system is responsible for the synthesis of new services from existing ones in a semi-automatic fashion. SCA System composes available Web Ontology Language for Web services atomic processes utilizing Revised Armstrong's Axioms (RAAs) in inferring functional dependencies. RAAs are embedded in the knowledge base ontologies of SCA System. Experiments show that the proposed SCA System produces process sequences as a composition plan that satisfies user's requirement for a complex task. The novelty of the SCA System is that for the first time Armstrong's Axioms are revised and used for semantic-based planning and inferencing of Web services.

Research on Consistency Verification of Semantic Business Process Model Based on SWRL

At the moment Semantic Business Process Model (SBPM) build on the semantic annotation, the specification of process activity, the control flow between activities and business functions of process. However, the correctness of SBPM is based on technical knowledge and experiences of the model designer, which is apparently not feasible for complex and dynamic business processes. Therefore, the goal of this paper is present a formalization description which was understood by business experts and model designers, establishing a new method to verify the consistency between SBPM and requirement of enterprise. Our techniques are based on the SWRL and Business rule.

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.

Semantic Business Process Integration in Cloud Manufacturing Paradigm

Global competition in the manufacturing industry forces to build a cross-organizational business process cooperative environment, in which manufacturers can share and utilize distributed resources and competencies for rapidly and cost-effectively developing products. But the varying manufacturing resources are heterogeneity which limits the business process execution in an automated way. This paper presents an approach for cross-organizational business processes integration in the cloud manufacturing paradigm. The main idea is to encapsulate an organization’s resources and competencies within appropriate interfaces and advertise it as semantic web services, called manufacturing service. An executable business process is achieved by manufacturing services composition. We give a detailed presentation of the cloud manufacturing service model. Semantically description of service not only contains resources’ capability, but also is considered as mediators to bridge the gap between the modeled processes and their implementation. The main integration process is introduced based our approach.

Research on Semantic Business Process Model in Logistics Distribution Field

Nowadays, business process has the problem of no unified standard, the lack of machine-understandable semantics and so on. Thus, in order to make the business analysts and IT staff have no communication obstacles to process modeling, we may make use of the standard that both sides can understand to express business process-introducing ontology technology. Therefore, this paper, from the bottleneck of logistics distribution business process, constructs logistics distribution domain ontology, and adds semantics for business process. It helps to achieve business process automation and intelligent, and may reduce the workload of user. At the same time, we also solve the problems of the concept sharing and information integration in logistics distribution field.

Model Checking Analysis of Semantically Annotated Business Processes

Semantic business processes require new analysis techniques able to deal with behavioral properties that also consider semantic aspects. In this paper, a model checking method is introduced including semantic aspects in both the model description and the formula to be verified. In addition, Unary resource description framework (RDF) annotated Petri net systems, a formalism that allows the semantic description of business processes using RDF annotations, is formally defined and used to represent the input model of the model checker. Finally, the prototype implementations of both the Unary RDF annotated Petri net formalism and a model checker framework based on the use of RDF and SPARQL tools are also presented.

Ontology-Based Exception Handling for Semantic Business Process Execution

Along with the widespread acceptance of business process management (BPM) and Semantic Web services composition technologies, Semantic Web service oriented programming is becoming an efficient way to develop modern business applications. As Semantic Web services are inherently unreliable, how to develop reliable service oriented applications is a significant and challenging problem, especially in complex, untamed and dynamic services environment. However, current business process programming languages for Semantic Web services provide almost no support for exception handling, and runtime environments are weak in providing reliability and adaptability. In this paper, we propose an ontology based exception handling method for semantic business processes using Semantic Programming Language (SPL). We identity a new exception taxonomy described as exception ontology and devise an event-driven exception events detection mechanism. We also devise an exception handling framework based on Multi agent system for SPL program. Especially, the framework provides forward recovery support with dynamically substituting failed services when an exception arises during execution by semantically equivalent or semantically similar Web services.

Ontology-based semantic matching for business process management

A company's competitiveness relies heavily on its business processes, and thus the need to execute business processes with agility and efficiency is ever-increasing. However, examination of current practice of business process management reveals the problem that it does not satisfy the need and the main reason for the problem is that sufficient semantic information associated with business processes is not included in the definition of business processes. This paper aims to build semantic business process space, which stores such semantic information as various generic and specific ontologies and to illustrate how such semantic information can be utilized when searching for a proper business process, which is the most essential element for the successful implementation of business process management. To that end, we have extended existing semantic matching method that matches only functional properties to a new one which matches non-functional properties as well as functional ones. As a way of validating our approach, we have shown how semantic business process space can be built from a part of the sales order process adopted from SAP R/3 ERP application and illustrated semantic matching using an example. We believe that this study will give practitioners a clear insight into implementing efficient business process management.

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.

Beyond soundness: on the verification of semantic business process models

The verification of control-flow soundness is well understood as an important step before deploying business process models. However, the control flow does not capture what the process activities actually do when they are executed. Semantic annotations offer the opportunity to take this into account. Inspired by semantic Web service approaches such as OWL-S and WSMO, we consider process models in which the individual activities are annotated with logical preconditions and effects, specified relative to an ontology that axiomatizes the underlying business domain. Verification then addresses the overall process behavior, arising from the interaction between control-flow and behavior of individual activities. To this end, we combine notions from the workflow community with notions from the AI actions and change literature. We introduce a formal execution semantics for annotated business processes. We point out four verification tasks that arise, concerning precondition/effect conflicts, reachability, and executability. We examine the borderline between classes of processes that can, or cannot, be verified in polynomial time. For precondition/effect conflicts, we show that the borderline is the same as that of the logic underlying the ontology axioms. For reachability and executability, we identify a class of processes that can be verified in polynomial time by a fixpoint algorithm which we design for that purpose. We show that this class of processes is maximal in the sense that, when generalizing it in any of the most relevant directions, the validation tasks become computationally hard.

Semantic reengineering of business processes

This paper discusses transforming ontological models into non-ontological models of business processes, when the process of articulating different data models is known as reengineering domains. As a crucial factor in achieving interoperability and semantic reengineering of the domains with the different levels of semantic representation (expressiveness), we point out the role of foundational ontology that serves to enable global meaning of the process knowledge and that is, in this paper, additionally connected with the process theory (process algebra). The main focus of the process theory is on the system that interacts with one another, such as the business processes, whereas the main idea of semantic reengineering is transforming ontological models into the semantic business processes that can be (semi-)automatically executed via a workflow engine. Therefore, as a promising solution in achieving interoperability between the real enterprise needs and the business process models, we involve the Pi-Calculus as a process theory to provide semantics between the ontological models based on the DOLCE Description and Situation (D&S) Plan and Tasks Ontology (DDPO) and the business process models that are expressed in Business Process Execution Language (BPEL).