Many scientific disciplines are now data and information driven, and new scientific knowledge is often gained by scientists putting together data analysis and knowledge discovery “pipelines”. A related trend is that more and more scientific communities realize the benefits of sharing their data and computational services, and are thus contributing to a distributed data and computational community infrastructure (a.k.a. “the Grid”). However, this infrastructure is only a means to an end and scientists ideally should be bothered little with its existence. The goal is for scientists to focus on development and use of what we call scientific workflows. These are networks of analytical steps that may involve, e.g., database access

Scientific workflows are becoming increasingly important as a unifying mechanism for interlinking scientific data management, analysis, simulation, and visualization tasks. Scientific workflow systems are problem-solving environments, supporting scientists in the creation and execution of scientific workflows.

Process Support Systems (PSSs) support business organizations in modeling, improving, and automating their business process. Thanks to their ability in enacting process models, they can be used to guide people in performing their daily work and to automate the repetitive tasks that do not require human intervention. Given these potential benefits, it is surprising to observe that PSSs are not widely adopted. This is especially true in case of highly flexible and human-intensive processes such as design processes in general and software processes in particular. This fact can be explained by observing that currently available PSSs do not fulfill some crucial needs of modern business organizations. One of their major drawbacks is that they do not offer adequate mechanisms to cope with unforeseen situations. They are good at supporting business processes if all proceeds as expected, but if an unexpected situation is met, which would require to deviate from the process model, they often bec...

In the competitive global marketplace, business organizations often need to team up and operate as a virtual enterprise to achieve common business goals. Since the business environment of a virtual enterprise is highly dynamic, it is necessary to develop a workflow technology that is capable of handling dynamic workflows across enterprise boundaries. This paper describes a dynamic workflow model and a dynamic workflow management system for modeling and controlling the execution of inter-organizational business processes. The model extends the underlying model of WfMC’s WPDL by adding connectors, events, triggers and rules as its modeling constructs, encapsulating activity definitions, and allowing e-service requests as a part of the activity specification. The workflow management system makes use of an event and rule server to trigger business rules during the enactment of workflow processes to enforce business constraints and policies and/or to modify the process model at run-time. It also provides a mechanism to dynamically bind e-service requests to e-services.

This paper reports on enriching a (logic-based) query and transformation language for the Web, called Xcerpt, with temporal constructs and temporal reasoning capabilities. Advanced Web applications often refer to temporal data, especially to time points, complex time intervals, and durations. Salient to many advanced Web applications is that they often refer to various calendars. However, current Web languages and formalisms have rather primitive temporal constructs and temporal data processing capabilities -- if any. The focus of the project this paper reports on is not to specify yet another temporal logic and/or calculus.

CONTENTS 1 Contents 1 Executive Summary 2 2 Background 4 3 Scientific Workflows 4 3.1 Example Workflows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.1.1 Promoter Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.1.2 Mineral Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.1.3 Job Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.2 Requirements and Desiderata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.3 Di#erences to Business Workflows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 4 SPA Technology Development 10 4.1 Web Service Extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 4.2 Grid and other Extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 4.3 Actor-Oriented Modeling . . . . . . .

Faculté des Arts et des Sciences Thèse présentée à la Faculté des Études Supérieures en vue de l’obtention du grade de Philosophiæ Doctor (Ph.D.) en Informatique

Data-centric scientific workflows are often modeled as dataflow process networks. The simplicity of the dataflow framework facilitates workflow design, analysis, and optimization. However, modeling “control-flow intensive” tasks using dataflow constructs often leads to overly complicated workflows that are hard to comprehend, reuse, and maintain. We describe a generic framework, based on scientific workflow templates and frames, for embedding control-flow intensive subtasks within dataflow process networks. This approach can seamlessly handle complex control-flow without sacrificing the benefits of dataflow. We illustrate our approach with a real-world scientific workflow from the astrophysics domain, requiring remote execution and file transfer in a semi-reliable environment. For such workflows, we also describe a 3-layered architecture based on frames and templates where the top-layer consists of an overall dataflow process network, the second layer consists of a tranducer template for modeling the desired control-flow behavior, and the bottom layer consists of frames inside the template that are specialized by embedding the desired component implementation. Our approach can enable scientific workflows that are more robust (faulttolerance strategies can be defined by control-flow driven transducer templates) and at the same time more reusable, since the embedding of frames and templates yields more structured and modular workflow designs.

We present the project management support in ADAMS (ADvanced Artefact Management System), a web-based system that integrates project management features such as resource allocation and process control and artefact management features, such as coordination of cooperative workers and artefact versioning, as well as contextawareness and artefact traceability features. We also present an evaluation of the usefulness and adequacy of the functionalities that ADAMS provides to the project managed. This evaluation has been conducted during the last 3 years with Master students attending