The Experts below are selected from a list of 84 Experts worldwide ranked by ideXlab platform
Lucinéia Heloisa Thom - One of the best experts on this subject based on the ideXlab platform.
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a semantic approach to the discovery of Workflow Activity patterns in event logs
International Journal of Business Process Integration and Management, 2012Co-Authors: Diogo R Ferreira, Lucinéia Heloisa ThomAbstract:Workflow Activity patterns represent a set of recurrent behaviours that can be found in a wide range of business processes. In this paper we address the problem of determining the presence of these patterns in process models. This is usually done manually by the analyst, who inspects the model and interprets its elements in terms of the semantics of those patterns. Here, we present an approach to perform this discovery based on the event log created during process execution. The approach makes use of an ontology and the semantic annotation of the event log in order to discover the patterns automatically by means of semantic reasoning. We illustrate the application of the proposed approach in a case study involving a purchase process implemented in a commercial Workflow system.
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on the capabilities of bpmn for Workflow Activity patterns representation
Business Process Modeling Notation, 2011Co-Authors: Lucinéia Heloisa Thom, Cirano Iochpe, Ivanna Maricruz Lazarte, Luzmaria Priego, Christine Verdier, Omar Chiotti, Pablo David VillarrealAbstract:This paper provides a complete version of the Workflow Activity Patterns (WAP) in the Business Process Modeling Notation (BPMN) as well as an extended evaluation of the capabilities of BPMN and their strengths and weaknesses when being utilizing for representing WAPs. When implementing the Activity patterns in existing Business Process Modeling tools, it is fundamental to represent them in BPMN. This representation may facilitate the adoption of the WAPs by BPMN tools as well as the use of the WAPs in process design.
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ontology based discovery of Workflow Activity patterns
Business Process Management, 2011Co-Authors: Diogo R Ferreira, Lucinéia Heloisa Thom, Susana P AlvesAbstract:Workflow Activity patterns represent a set of recurrent behaviors that can be found in a wide range of business processes. In this paper we address the problem of determining the presence of these patterns in process models. This is usually done manually by the analyst, and it requires interpreting the process in terms of the semantics of those patterns. We describe an ontology-based approach to perform this discovery in an automated way. The approach makes use of an ontology, and a mapping between the elements in the given process and the classes in the ontology. A reasoner is then used to discover the patterns, and a SPARQL query is used to retrieve them. The approach is illustrated for a business process in a travel booking scenario.
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On the Support of Workflow Activity Patterns in Process Modeling Tools: Purpose and Requirements
2009Co-Authors: Lucinéia Heloisa Thom, Manfred Reichert, Cirano IochpeAbstract:Patterns increase the reuse of existing knowledge (e.g., design solutions, source code) within organizations and help to achieve consistency between applications. Patterns for process design have received considerable attention by both business analysts and researchers. Several pattern categories have been proposed including patterns for control and data flow, resources, process change, and exception handling. Workflow Activity patterns, which can be used as building blocks for business process models (e.g., approval, task execution request), however, have not been explored in-depth so far. Related to this problem we have proposed a set of Workflow Activity patterns in the ProWAP project. Each Activity pattern represents a recurrent business function as it can be frequently found in business processes. The completeness and existence of our Activity patterns has been evaluated through an extensive analysis of real process models. In this paper we discuss how to implement Activity patterns within a BPM tool. In particular, we describe major goals and requirements of the BPM tool we are currently developing and in which we apply Workflow Activity patterns. In this context, we also provide a discussion regarding the notion we use for representing Activity patterns (BPMN 1.2 vs. UML 2.0).
Yun Yang - One of the best experts on this subject based on the ideXlab platform.
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Forecasting Scientific Cloud Workflow Activity Duration Intervals
Temporal QOS Management in Scientific Cloud Workflow Systems, 2012Co-Authors: Xiao Liu, Yun Yang, Jinjun ChenAbstract:As discussed in Chapter 2, Workflow Activity duration is one of the basic elements in the temporal consistency model, and thus its accuracy is critical for the effectiveness of temporal verification and all the other related components such as temporal checkpoint selection and temporal violation handling. Therefore, an accurate forecasting strategy is required to predict cloud Workflow Activity durations. However, it is not a trivial issue due to the dynamic nature of cloud computing environments. In this chapter, we present a statistical time-series-based forecasting strategy for scientific cloud Workflow Activity duration intervals. The comparison results demonstrate that our strategy has better performance than the other existing representative strategies. This chapter is organised as follows. Section 5.1 gives a general introduction about cloud Workflow Activity durations. Section 5.2 presents the specifically related work and problem analysis. Section 5.3 presents the novel statistical time-series-pattern-based forecasting strategy. Section 5.4 demonstrates the experimental results.
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A novel statistical time-series pattern based interval forecasting strategy for Activity durations in Workflow systems
Journal of Systems and Software, 2011Co-Authors: Zhiwei Ni, Yuanchun Jiang, Zhangjun Wu, Dong Yuan, Jinjun Chen, Yun YangAbstract:Forecasting Workflow Activity durations is of great importance to support satisfactory QoS in Workflow systems. Traditionally, a Workflow system is often designed to facilitate the process automation in a specific application domain where activities are of the similar nature. Hence, a particular forecasting strategy is employed by a Workflow system and applied uniformly to all its Workflow activities. However, with newly emerging requirement to serve as a type of middleware services for high performance computing infrastructures such as grid and cloud computing, more and more Workflow systems are designed to be general purpose to support Workflow applications from many different domains. Due to such a problem, the forecasting strategies in Workflow systems must adapt to different Workflow applications which are normally executed repeatedly such as data/computation intensive scientific applications (mainly with long-duration activities) and instance intensive business applications (mainly with short-duration activities). In this paper, with a systematic analysis of the above issues, we propose a novel statistical time-series pattern based interval forecasting strategy which has two different versions, a complex version for long-duration activities and a simple version for short-duration activities. The strategy consists of four major functional components: duration series building, duration pattern recognition, duration pattern matching and duration interval forecasting. Specifically, a novel hybrid non-linear time-series segmentation algorithm is designed to facilitate the discovery of duration-series patterns. The experimental results on real world examples and simulated test cases demonstrate the excellent performance of our strategy in the forecasting of Activity duration intervals for both long-duration and short-duration activities in comparison to some representative time-series forecasting strategies in traditional Workflow systems.
Diogo R Ferreira - One of the best experts on this subject based on the ideXlab platform.
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a semantic approach to the discovery of Workflow Activity patterns in event logs
International Journal of Business Process Integration and Management, 2012Co-Authors: Diogo R Ferreira, Lucinéia Heloisa ThomAbstract:Workflow Activity patterns represent a set of recurrent behaviours that can be found in a wide range of business processes. In this paper we address the problem of determining the presence of these patterns in process models. This is usually done manually by the analyst, who inspects the model and interprets its elements in terms of the semantics of those patterns. Here, we present an approach to perform this discovery based on the event log created during process execution. The approach makes use of an ontology and the semantic annotation of the event log in order to discover the patterns automatically by means of semantic reasoning. We illustrate the application of the proposed approach in a case study involving a purchase process implemented in a commercial Workflow system.
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ontology based discovery of Workflow Activity patterns
Business Process Management, 2011Co-Authors: Diogo R Ferreira, Lucinéia Heloisa Thom, Susana P AlvesAbstract:Workflow Activity patterns represent a set of recurrent behaviors that can be found in a wide range of business processes. In this paper we address the problem of determining the presence of these patterns in process models. This is usually done manually by the analyst, and it requires interpreting the process in terms of the semantics of those patterns. We describe an ontology-based approach to perform this discovery in an automated way. The approach makes use of an ontology, and a mapping between the elements in the given process and the classes in the ontology. A reasoner is then used to discover the patterns, and a SPARQL query is used to retrieve them. The approach is illustrated for a business process in a travel booking scenario.
Jinjun Chen - One of the best experts on this subject based on the ideXlab platform.
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Forecasting Scientific Cloud Workflow Activity Duration Intervals
Temporal QOS Management in Scientific Cloud Workflow Systems, 2012Co-Authors: Xiao Liu, Yun Yang, Jinjun ChenAbstract:As discussed in Chapter 2, Workflow Activity duration is one of the basic elements in the temporal consistency model, and thus its accuracy is critical for the effectiveness of temporal verification and all the other related components such as temporal checkpoint selection and temporal violation handling. Therefore, an accurate forecasting strategy is required to predict cloud Workflow Activity durations. However, it is not a trivial issue due to the dynamic nature of cloud computing environments. In this chapter, we present a statistical time-series-based forecasting strategy for scientific cloud Workflow Activity duration intervals. The comparison results demonstrate that our strategy has better performance than the other existing representative strategies. This chapter is organised as follows. Section 5.1 gives a general introduction about cloud Workflow Activity durations. Section 5.2 presents the specifically related work and problem analysis. Section 5.3 presents the novel statistical time-series-pattern-based forecasting strategy. Section 5.4 demonstrates the experimental results.
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A novel statistical time-series pattern based interval forecasting strategy for Activity durations in Workflow systems
Journal of Systems and Software, 2011Co-Authors: Zhiwei Ni, Yuanchun Jiang, Zhangjun Wu, Dong Yuan, Jinjun Chen, Yun YangAbstract:Forecasting Workflow Activity durations is of great importance to support satisfactory QoS in Workflow systems. Traditionally, a Workflow system is often designed to facilitate the process automation in a specific application domain where activities are of the similar nature. Hence, a particular forecasting strategy is employed by a Workflow system and applied uniformly to all its Workflow activities. However, with newly emerging requirement to serve as a type of middleware services for high performance computing infrastructures such as grid and cloud computing, more and more Workflow systems are designed to be general purpose to support Workflow applications from many different domains. Due to such a problem, the forecasting strategies in Workflow systems must adapt to different Workflow applications which are normally executed repeatedly such as data/computation intensive scientific applications (mainly with long-duration activities) and instance intensive business applications (mainly with short-duration activities). In this paper, with a systematic analysis of the above issues, we propose a novel statistical time-series pattern based interval forecasting strategy which has two different versions, a complex version for long-duration activities and a simple version for short-duration activities. The strategy consists of four major functional components: duration series building, duration pattern recognition, duration pattern matching and duration interval forecasting. Specifically, a novel hybrid non-linear time-series segmentation algorithm is designed to facilitate the discovery of duration-series patterns. The experimental results on real world examples and simulated test cases demonstrate the excellent performance of our strategy in the forecasting of Activity duration intervals for both long-duration and short-duration activities in comparison to some representative time-series forecasting strategies in traditional Workflow systems.
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implementation of a visual modeling tool for defining instance aspect in Workflow
International Symposium on Parallel and Distributed Processing and Applications, 2009Co-Authors: Jianxun Liu, Zefeng Zhu, Yiping Wen, Jinjun ChenAbstract:The instance-aspect oriented Workflow management system is to vertically combine multiple Workflow Activity instances and submit them for execution as a whole according to some batch or combination logics. It is inspired by the idea of aspect-oriented programming methodology and aims at improving the execution efficiency of business processes. Traditional Workflow systems do not support Workflow model with instance aspects. In our previous work, we have studied Workflow instance modeling technology. This paper makes a research on the principles, methods and implementation of a Workflow visual GUI tool for modeling instance aspects in Workflow. It is based on an open source GUI tool, Together Workflow Editor, and makes some expansion in instance aspect functionality.
Duncan D Ruiz - One of the best experts on this subject based on the ideXlab platform.
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extending uml Activity diagram for Workflow modeling in production systems
Hawaii International Conference on System Sciences, 2002Co-Authors: R M Bastos, Duncan D RuizAbstract:This paper presents an approach to describe business process in production systems using Workflow concepts. In this sense, we define an extension of the UML Activity diagram called Workflow Activity diagram (WAD) which applies C-WF model concepts. The C-Wf model represents the structural and functional enterprise objects involved in the business processes, such as enterprise activities, human resources, machine resources, etc. The WAD depicts the Workflow model identifying its activities and resources required for its execution defining its relationships and sequentially. By the intensive use of UML use cases, our approach reinforces the usability of UML in the context of business modeling.
