Model-driven engineering approach to design and implementation of robot control system

In this paper we apply a model-driven engineering approach to designing domain-specific solutions for robot control system development. We present a case study of the complete process, including identification of the domain meta-model, graphical notation definition and source code generation for subsumption architecture -- a well-known example of robot control architecture. Our goal is to show that both the definition of the robot-control architecture and its supporting tools fits well into the typical workflow of model-driven engineering development.Comment: Presented at DSLRob 2011 (arXiv:cs/1212.3308

Automating distributed workflow for electronic commerce: A model for building meta-workflow components

Business software development environments for web- based applications are at a very early stage in their potential lifecycle. The purpose of this research agenda is to develop a model for how business processes can be interpreted into primitive computer codes for web applications. We have taken a transaction perspective adapted from the distributed database approach to maintenance of integrity assuming the concepts of ACIDity (Atomicity, Consistency, Isolation, and Durability) and serializability. This perspective is consistent with emerging literature on “workflow agents” [e.g., Huhns and Singh, 1998]. In this paper, we design, develop, and show an example of a meta-level set of building blocks for a direct mapping between electronic commerce and workflow processes. To validate the sufficiency and completeness of the meta-level components proposed, a complete mapping of an electronic commerce application to meta-workflow components is proposed

Flexible and Emergent Workflows using Adaptive Agents

International audienceMost of existing workflow systems are rigid since they require to completely specify processes before their enactment and they also lack flexibility during their execution. This work proposes to view a workflow as a set of cooperative and adaptive agents interleaving its design and its execution leading to an emergent workflow. We use the theory of Adaptive Multi-Agent Systems (AMAS) to provide agents with adaptive capabilities and the whole multi-agent system with emergent "feature". We provide a meta-model linking workflow and AMAS concepts, and the specification of agent behavior and the resulting collaborations. A simulator has been implemented with the Make Agent Yourself platform

DPN -- Dependability Priority Numbers

This paper proposes a novel model-based approach to combine the quantitative dependability (safety, reliability, availability, maintainability and IT security) analysis and trade-off analysis. The proposed approach is called DPN (Dependability Priority Numbers) and allows the comparison of different actual dependability characteristics of a systems with its target values and evaluates them regarding trade-off analysis criteria. Therefore, the target values of system dependability characteristics are taken as requirements, while the actual value of a specific system design are provided by quantitative and qualitative dependability analysis (FHA, FMEA, FMEDA, of CFT-based FTA). The DPN approach evaluates the fulfillment of individual target requirements and perform trade-offs between analysis objectives. We present the workflow and meta-model of the DPN approach, and illustrate our approach using a case study on a brake warning contact system. Hence, we demonstrate how the model-based DPNs improve system dependability by selecting the project crucial dependable design alternatives or measures

Meta-model for Collaboration Modeling in Legal Sector

Cost effective and best practice legal services are highly relying on the coordination of collaborativeworkflow activities as well as of several resources needed to perform these activities and their flow ofinformation exchanges among many different participants. In the context of ever increasing numbers of legalcases and involved stakeholders in multi-party collaborations, we have discovered the appropriateness of theadaptation of workflow management systems in legal sector to address the resulting complexities andperformance issues in legal service collaborations. In this work, a meta-model for legal service collaborationmodeling which includes the main semantics of modeling elements, has been introduced as the basis fordefining the choreography for sector collaboration with the objective of facilitating legal collaborationmodeling in such a way as to provide a useful input for the creation of legal workflow specifications forsetting up legal workflow management systems. The meta-model was developed based on BusinessTransaction View meta-model in UN/CEFACT’s recommendations for business collaborations. The proposedmodeling framework could facilitate and guide the complex legal collaboration modeling processes withpromising results in workflow coordination.KEYWORDS: Meta-model, Legal Collaborations, Legal Activity Coordinatio

Learning Heterogeneous Similarity Measures for Hybrid-Recommendations in Meta-Mining

The notion of meta-mining has appeared recently and extends the traditional meta-learning in two ways. First it does not learn meta-models that provide support only for the learning algorithm selection task but ones that support the whole data-mining process. In addition it abandons the so called black-box approach to algorithm description followed in meta-learning. Now in addition to the datasets, algorithms also have descriptors, workflows as well. For the latter two these descriptions are semantic, describing properties of the algorithms. With the availability of descriptors both for datasets and data mining workflows the traditional modelling techniques followed in meta-learning, typically based on classification and regression algorithms, are no longer appropriate. Instead we are faced with a problem the nature of which is much more similar to the problems that appear in recommendation systems. The most important meta-mining requirements are that suggestions should use only datasets and workflows descriptors and the cold-start problem, e.g. providing workflow suggestions for new datasets. In this paper we take a different view on the meta-mining modelling problem and treat it as a recommender problem. In order to account for the meta-mining specificities we derive a novel metric-based-learning recommender approach. Our method learns two homogeneous metrics, one in the dataset and one in the workflow space, and a heterogeneous one in the dataset-workflow space. All learned metrics reflect similarities established from the dataset-workflow preference matrix. We demonstrate our method on meta-mining over biological (microarray datasets) problems. The application of our method is not limited to the meta-mining problem, its formulations is general enough so that it can be applied on problems with similar requirements

Authorization and access control of application data in Workflow systems

Workflow Management Systems (WfMSs) are used to support the modeling and coordinated execution of business processes within an organization or across organizational boundaries. Although some research efforts have addressed requirements for authorization and access control for workflow systems, little attention has been paid to the requirements as they apply to application data accessed or managed by WfMSs. In this paper, we discuss key access control requirements for application data in workflow applications using examples from the healthcare domain, introduce a classification of application data used in workflow systems by analyzing their sources, and then propose a comprehensive data authorization and access control mechanism for WfMSs. This involves four aspects: role, task, process instance-based user group, and data content. For implementation, a predicate-based access control method is used. We believe that the proposed model is applicable to workflow applications and WfMSs with diverse access control requirements

Structuring research methods and data with the research object model:genomics workflows as a case study

Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e. g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as "which particular data was input to a particular workflow to test a particular hypothesis?", and "which particular conclusions were drawn from a particular workflow?". Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well. Availability: The Research Object is available at http://www.myexperiment.org/packs/428 The Wf4Ever Research Object Model is available at http://wf4ever.github.io/r