Supporting effective unexpected exception handling in workflow management systems within organizaional contexts

Tese de doutoramento em Informática (Engenharia Informática), apresentada à Universidade de Lisboa através da Faculdade de Ciências, 2008Workflow Management Systems (WfMS) support the execution of organizational processes within organizations. Processes are modelled using high level languages specifying the sequence of tasks the organization has to perform. However, organizational processes do not have always a smooth flow conforming to any possible designed model and exceptions to the rule happen often. Organizations require flexibility to react to situations not predicted in the model. The required flexibility should be complemented with robustness to guarantee system reliability even in extreme situations. In our work, we have introduced the concept of WfMS resilience that comprises these two facets: robustness and flexibility. The main objective of our work is to increase resilience in WfMSs. From the events demanding for WfMS resilience, we focused on ad hoc effective unexpected exceptions as those for which no previous knowledge exist is the organization to derive the handling procedure and no plan can be a priori established. These exceptions usually require human intervention and problem solving activities, since the concrete situation may not be entirely understood before humans start reacting to the event. After discussing existing approaches to increase WfMS resilience, we have identified five levels of conformity. The fifth level, being the most demanding one, requires unrestricted humanistic interventions to workflow execution. In this thesis, we propose a system to support unrestricted users' interventions to the WfMS and we characterize the interventions as unstructured activities. The system has two modes of operation: it usually works under model control and changes to unstructured activities support when an exception is detected. The exception handling activities are carried out until the system is placed back into a coherent mode, where work may proceed undermodel execution control

Implementação de um laboratório de Big Data para processamento de dados em batch e streaming

Trabalho apresentado em XXX Jornadas Luso-Espanholas de Gestão Científica, 5-8 fevereiro 2020, Bragança, PortugalBig Data é uma área que pretende proporcionar capacidade de processamento dos dados, face ao crescimento exponencial de informação gerada de dia para dia, através de novas tecnologias para recolha, transformação, processamento e análise de dados provenientes de diversas fontes e em diversos formatos. Os desafios do Big Data são significativos, daí terem surgido diversas tecnologias num curto espaço de tempo, o que torna também desafiante a entrada nesta área de estudo/investigação. Este artigo apresenta um projeto de implementação de um laboratório de Big Data, para processamento de dados históricos e em movimento (streaming), cujo propósito é permitir a utilização/exploração das tecnologias associadas em atividades de ensino e investigação. São apresentadas as tecnologias, a arquitetura implementada e testes de processamento de dados realizados para validação da correta configuração e funcionamento do laboratório.Big Data is a field that aims to provide data processing capacity, facing the exponential growth of information generated daily, through new technologies for collecting, transforming, processing and analysing data from various sources and in various formats. The challenges of Big Data are significant, so many technologies have emerged in a short time, making the entry into this area of study / research challenging as well. This paper presents a project for the implementation of a big data laboratory for processing historical and data in motion (streaming), whose purpose is to allow the use / exploitation of associated technologies in teaching and research activities. The technologies, the implemented architecture and data processing tests performed to validate the correct configuration and operation of the laboratory are presented.info:eu-repo/semantics/publishedVersio

Supporting Effective Unexpected Exception Handling in Workflow Management Systems Within Organizational Contexts

Workflow Management Systems support the execution of organizational processes within organizations. Processes are modelled using high level languages specifying the sequence of tasks the organization has to perform. However, organizational processes do not have always a smooth flow conforming to any possible designed model and exceptions to the rule happen often. Organizations require flexibility to react to situations not predicted in the model. The required flexibility should be complemented with robustness to guarantee system reliability even in extreme situations. In our work, we have introduced the concept of WfMS resilience that comprises these two facets: robustness and flexibility. The main objective of our work is to increase resilience in Workflow Management Systems. From the events demanding for Workflow Management Systems resilience, we focused on ad hoc effective unexpected exceptions as those for which no previous knowledge exist is the organization to derive the handling procedure and no plan can be a priori established. These exceptions usually require human intervention and problem solving activities, since the concrete situation may not be entirely understood before humans start reacting to the event. After discussing existing approaches to increase WfMS resilience, we have identified five levels of conformity. The fifth level, being the most demanding one, requires unrestricted humanistic interventions to workflow execution. In this thesis, we propose a system to support unrestricted users' interventions to the WfMS and we characterize the interventions as unstructured activities. The system has two modes of operation: it usually works under model control and changes to unstructured activities support when an exception is detected. The exception handling activities are carried out until the system is placed back into a coherent mode, where work may proceed under model execution contro

Supporting effective unexpected exceptions handling in workflow management systems

This paper proposes a novel architectural framework handling effective unexpected exceptions in workflow management systems (WfMS). Effective unexpected exceptions are events for which the organizations lack handling strategies. Unstructured human interventions are necessary to overcome these situations, but clash with the type of model control currently exercised by WfMS. The proposed framework uses the notion of map guidance to orchestrate these human interventions. Map guidance empowers users with contextual information about the WfMS and environment, enables the interruption of model control on the affected instances, supports collaborative exception handling and facilitates regaining model control after the exception has been resolved. The framework implementation in the Open Symphony open source platform is also described

A Collaborative Framework for Unexpected Exception

Abstract. This paper proposes a collaborative framework handling unexpected exceptions in Workflow Management Systems (WfMS). Unexpected exceptions correspond to unpredicted situations for which the system can not suggest any solutions. We introduce the notion that exception recovery is a collaborative problem solving activity that should be addressed through an intertwined play between several actors performing two types of tasks: (1) diagnosing situations; and (2) planning recovery actions. We propose a set of dimensions to classify the exceptional situations and their relations to recovery strategies. We also discuss the importance of monitoring recovery actions within the scope of diagnosis tasks. The proposed solution is implemented through a dedicated workflow. 1

Workflow Recovery Framework for Exception Handling: Involving the User

Abstract. Unexpected exceptions in WfMS are situations not predicted during the design phase. Human involvement in handling this type of exceptions has been recognized to be a crucial factor. We developed a framework to support the user in handling these situations by redesigning the flow, ad hoc executing the affected tasks, and manipulating engine status. A good characterization of the exception is needed to help the user identifying the best executable solution. The proposed characterization results from integrating operational, tactical and strategic perspectives over unexpected exceptions. An open source platform was selected to establish a test base on which the framework will be tested.

Supporting Direct User Interventions in Exception Handling in Workflow . . .

We developed a framework to handle exceptions in WfMS. Specially, unexpected exceptions, which are situations not predicted during the design phase, and require human involvement. A good characterization of the exception is needed to help the user in the identification of the solution(s) from an available tool kit: redesigning the flow, ad hoc executing the affected tasks, and manipulating engine status. The proposed characterization results from integrating operational, tactical and strategic perspectives over unexpected exceptions. An open source platform was selected to establish a test base on which the framework will be tested. The framework will be implemented in one company and data from another company will be used for simulation