Semantic Annotation and Composition of Business Processes with Maestro

Born, Matthias; Hoffmann, Jörg; Kaczmarek, Tomasz; Kowalkiewicz, Marek; Marković, Ivan; Scicluna, James; Weber, Ingo; Zhou, Xuan

doi:10.1007/978-3-540-68234-9_56

Cited by 20 publications

(13 citation statements)

References 7 publications

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“…Similarly, the authors of [10] propose sBPMN, which integrates semantic technologies and BPMN to overcome the obvious gap between an abstract representation of process models and actual executable descriptions in BPEL. [11] follows the same track with the proposal of BPMO, an ontology, which partly is based on sBPMN, while [12] takes sBPMN as basis for the Maestro tool, which implements the realization of semantically annotated business tasks with concrete services by means of automatic discovery and composition. In [13], a reference architecture for semSOA in BPM is proposed, which aims to address the representation discrepancy business expertise and IT knowledge by making use of semantic web technologies.…”

Section: Related Workmentioning

confidence: 99%

“…Most existing approaches to PSP composition do not cover the combination of functional (semantic) aspects and non-functional (QoS-aware) optimization. For example, [12,18,19] considered for the micro-service domain [23], but soon they have also been applied to other domains, such as the integration of legacy services [24] or in our scenario for integrating heterogeneous services into business processes. Furthermore, containers have a better startup performance and a lower resource footprint than established virtual machines (VMs) [25], which makes them an obvious choice for an on-demand process execution environment.…”

Section: Related Workmentioning

confidence: 99%

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Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing

Mazzola¹,

Waibel²,

Kaphanke³

et al. 2018

Preprint

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A new requirement for the manufacturing companies in Industry 4.0 is to be flexible with respect to changes in demands, requiring them to react rapidly and efficiently on the production capacities. Together with the trend to use Service-Oriented Architectures (SOA), this requirement induces a need for agile collaboration among supply chain partners, but also between different divisions or branches of the same company. In order to address this collaboration challenge, we propose a novel pragmatic approach for the process analysis, implementation and execution. This is achieved through sets of semantic annotations of business process models encoded into BPMN 2.0 extensions. Building blocks for such manufacturing processes are the individual avaialble services, which are also semantically annotated according to the Everything-as-a-Service (XaaS) principles and stored into a common marketplace. The optimization of such manufacturing processes combines pattern-based semantic composition of services with their non-functional aspects. This is achieved by means of Quality-of-Services (QoS) based constraint optimization problem (COP) solving, resulting in an automatic implementation of service-based manufacturing processes. The produced solution is mapped back to the BPMN 2.0 standard formalism by the means of introduced extension elements, fully detailing the enactable optimal process service plan produced. This approach allows enacting a process instance, using just-in-time service leasing, allocation of resources, and dynamic replanning in case of failures. This proposition provides the best compromise between external visibility, control and flexibility. In this way, it provides an optimal approach for business process models implementation, with a full service-oriented taste, by implementing user-defined QoS metrics, just-in-time execution and basic dynamic repairing capabilities. This paper presents the described approach, the technical architecture and depicts one initial industrial application in the manufacturing domains of aluminum forging for bicycle hull body forming, where the advantages stemming from the main capabilities of this approach are sketched.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing

Mazzola¹,

Waibel²,

Kaphanke³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…For this purpose software tools have been developed that permit to enrich business process models with semantic annotations and subsequently discover web services that match these semantic descriptions. Examples include the Maestro tool [7], an extension of the ARIS modeling toolkit [48], WSMO Studio [9], or Pro-SEAT [41]. However, as these tools are directed towards business processes, they are mostly limited to particular business process modeling and ontology languages.…”

Section: Related Toolsmentioning

confidence: 99%

SeMFIS: A flexible engineering platform for semantic annotations of conceptual models

Fill

2017

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In this paper, we present SeMFIS-a flexible engineering platform for semantic annotations of conceptual models. Conceptual models have been used in the past for many purposes in the context of information systems' engineering. These purposes include for example the elicitation of requirements, the simulation of the behavior of future information systems, the generation of code or the interaction with information systems through models at runtime. Semantic annotations of conceptual models constitute a recently established approach for dynamically extending the semantic representation and semantic analysis scope of conceptual modeling languages. Thereby, elements in conceptual models are linked to concepts in ontologies via annotations. Thus, additional knowledge aspects can be represented without modifications of the modeling languages. These aspects can then be analyzed using queries, specifically designed algorithms or external tools and services. At its core, SeMFIS provides a set of meta models for visually representing ontologies and semantic annotations as models. In addition, the tool contains an analysis component, a web service interface, and an import/export component to query and exchange model information. SeM-FIS has been implemented using the freely available ADOxx meta modeling platform. It can thus be directly added to the large variety of other modeling methods based on this platform or used as an additional service for other tools. We present the main features of SeMFIS and briefly discuss use cases where it has been applied. SeMFIS is freely available via OMiLAB at http:// semfis-platform.org/.

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“…The first one, called Maestro for BPMN (Born, Hoffmann, Kaczmarek, Kowalkiewicz, Markovic, Scicluna, Weber, & Zhou, 2008, 2009, is a BPMN process modeling tool developed by SAP Research primarily for the purpose of research and early prototyping. We focus in what follows on our other prototype, which is implemented in the context of the commercial SAP NetWeaver platform (SAP, 2010).…”

Section: Positioning Of Our Prototypes At Sapmentioning

confidence: 99%

SAP Speaks PDDL: Exploiting a Software-Engineering Model for Planning in Business Process Management

Hoffmann¹,

Weber²,

Kraft³

2012

jair

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Planning is concerned with the automated solution of action sequencing problems described in declarative languages giving the action preconditions and effects. One important application area for such technology is the creation of new processes in Business Process Management (BPM), which is essential in an ever more dynamic business environment. A major obstacle for the application of Planning in this area lies in the modeling. Obtaining a suitable model to plan with -ideally a description in PDDL, the most commonly used planning language -is often prohibitively complicated and/or costly. Our core observation in this work is that this problem can be ameliorated by leveraging synergies with model-based software development. Our application at SAP, one of the leading vendors of enterprise software, demonstrates that even one-to-one model re-use is possible.The model in question is called Status and Action Management (SAM). It describes the behavior of Business Objects (BO), i.e., large-scale data structures, at a level of abstraction corresponding to the language of business experts. SAM covers more than 400 kinds of BOs, each of which is described in terms of a set of status variables and how their values are required for, and affected by, processing steps (actions) that are atomic from a business perspective. SAM was developed by SAP as part of a major model-based software engineering effort. We show herein that one can use this same model for planning, thus obtaining a BPM planning application that incurs no modeling overhead at all.We compile SAM into a variant of PDDL, and adapt an off-the-shelf planner to solve this kind of problem. Thanks to the resulting technology, business experts may create new processes simply by specifying the desired behavior in terms of status variable value changes: effectively, by describing the process in their own language.

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Semantic Annotation and Composition of Business Processes with Maestro

Cited by 20 publications

References 7 publications

Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing

Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing

SeMFIS: A flexible engineering platform for semantic annotations of conceptual models

SAP Speaks PDDL: Exploiting a Software-Engineering Model for Planning in Business Process Management

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