Provision of an integrated data analysis platform for computational neuroscience experiments

© Emerald Group Publishing Limited. Purpose – The purpose of this paper is to provide an integrated analysis base to facilitate computational neuroscience experiments, following a user-led approach to provide access to the integrated neuroscience data and to enable the analyses demanded by the biomedical research community. Design/methodology/approach – The design and development of the N4U analysis base and related information services addresses the existing research and practical challenges by offering an integrated medical data analysis environment with the necessary building blocks for neuroscientists to optimally exploit neuroscience workflows, large image data sets and algorithms to conduct analyses. Findings – The provision of an integrated e-science environment of computational neuroimaging can enhance the prospects, speed and utility of the data analysis process for neurodegenerative diseases. Originality/value – The N4U analysis base enables conducting biomedical data analyses by indexing and interlinking the neuroimaging and clinical study data sets stored on the grid infrastructure, algorithms and scientific workflow definitions along with their associated provenance information

Runtime Adaptation of Scientific Service Workflows

Software landscapes are rather subject to change than being complete after having been built. Changes may be caused by a modified customer behavior, the shift to new hardware resources, or otherwise changed requirements. In such situations, several challenges arise. New architectural models have to be designed and implemented, existing software has to be integrated, and, finally, the new software has to be deployed, monitored, and, where appropriate, optimized during runtime under realistic usage scenarios. All of these situations often demand manual intervention, which causes them to be error-prone. This thesis addresses these types of runtime adaptation. Based on service-oriented architectures, an environment is developed that enables the integration of existing software (i.e., the wrapping of legacy software as web services). A workflow modeling tool that aims at an easy-to-use approach by separating the role of the workflow expert and the role of the domain expert. After the development of workflows, tools that observe the executing infrastructure and perform automatic scale-in and scale-out operations are presented. Infrastructure-as-a-Service providers are used to scale the infrastructure in a transparent and cost-efficient way. The deployment of necessary middleware tools is automatically done. The use of a distributed infrastructure can lead to communication problems. In order to keep workflows robust, these exceptional cases need to treated. But, in this way, the process logic of a workflow gets mixed up and bloated with infrastructural details, which yields an increase in its complexity. In this work, a module is presented that can deal automatically with infrastructural faults and that thereby allows to keep the separation of these two layers. When services or their components are hosted in a distributed environment, some requirements need to be addressed at each service separately. Although techniques as object-oriented programming or the usage of design patterns like the interceptor pattern ease the adaptation of service behavior or structures. Still, these methods require to modify the configuration or the implementation of each individual service. On the other side, aspect-oriented programming allows to weave functionality into existing code even without having its source. Since the functionality needs to be woven into the code, it depends on the specific implementation. In a service-oriented architecture, where the implementation of a service is unknown, this approach clearly has its limitations. The request/response aspects presented in this thesis overcome this obstacle and provide a SOA-compliant and new methods to weave functionality into the communication layer of web services. The main contributions of this thesis are the following: Shifting towards a service-oriented architecture: The generic and extensible Legacy Code Description Language and the corresponding framework allow to wrap existing software, e.g., as web services, which afterwards can be composed into a workflow by SimpleBPEL without overburdening the domain expert with technical details that are indeed handled by a workflow expert. Runtime adaption: Based on the standardized Business Process Execution Language an automatic scheduling approach is presented that monitors all used resources and is able to automatically provision new machines in case a scale-out becomes necessary. If the resource's load drops, e.g., because of less workflow executions, a scale-in is also automatically performed. The scheduling algorithm takes the data transfer between the services into account in order to prevent scheduling allocations that eventually increase the workflow's makespan due to unnecessary or disadvantageous data transfers. Furthermore, a multi-objective scheduling algorithm that is based on a genetic algorithm is able to additionally consider cost, in a way that a user can define her own preferences rising from optimized execution times of a workflow and minimized costs. Possible communication errors are automatically detected and, according to certain constraints, corrected. Adaptation of communication: The presented request/response aspects allow to weave functionality into the communication of web services. By defining a pointcut language that only relies on the exchanged documents, the implementation of services must neither be known nor be available. The weaving process itself is modeled using web services. In this way, the concept of request/response aspects is naturally embedded into a service-oriented architecture

3rd EGEE User Forum

We have organized this book in a sequence of chapters, each chapter associated with an application or technical theme introduced by an overview of the contents, and a summary of the main conclusions coming from the Forum for the chapter topic. The first chapter gathers all the plenary session keynote addresses, and following this there is a sequence of chapters covering the application flavoured sessions. These are followed by chapters with the flavour of Computer Science and Grid Technology. The final chapter covers the important number of practical demonstrations and posters exhibited at the Forum. Much of the work presented has a direct link to specific areas of Science, and so we have created a Science Index, presented below. In addition, at the end of this book, we provide a complete list of the institutes and countries involved in the User Forum

High-Performance Cloud Computing: A View of Scientific Applications

Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a Service Level Agreement (SLA), which ensure the desired Quality of Service (QoS). Aneka, an enterprise Cloud computing solution, harnesses the power of compute resources by relying on private and public Clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the Cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape

A Lightweight App Distribution Strategy to Generate Interest in Complex Commercial Apps: Case Study of an Automated Wound Measurement System

Tablet-based healthcare technologies automating clinical triage procedures hold exciting promise for increased precision and expediency. These point-of-care (POC) solutions are often complex, and their introduction to the marketplace may encounter cost and usability barriers. One example triage procedure is wound measurement. This paper demonstrates an innovative approach to POC wound measurement by introducing a free “light” version of a wound measurement mobile app that serves as a teaser for a full-featured commercial offering. We first describe the commercial offering; a 3D wound assessment tablet application. Then we present the smartphone app that inherits features from the tablet app. The smartphone app adopts a simple scaling algorithm to address the lack of a highly advanced computer vision system for the automated wound measurement task that exists in the tablet app. This paper describes the design process for developing this smartphone app, provides a detailed exposition of the scaling algorithm, and discusses the significance of this approach to app development and distribution

PESSCARA: An Example Infrastructure for Big Data Research

Big data requires a flexible system for data management and curation which has to be intuitive, and it should also be able to execute non-linear analysis pipelines suitable to handle with the nature of big data. This is certainly true for medical images where the amount of data grows exponentially every year and the nature of images rapidly changes with technological advances and rapid genomic advances. In this chapter, we describe a system that provides flexible management for medical images plus a wide array of associated metadata, including clinical data, genomic data, and clinical trial information. The system consists of open-source Content Management System (CMS) that has a highly configurable workflow; has a single interface that can store, manage, enable curation, and retrieve imaging-based studies; and can handle the requirement for data auditing and project management. Furthermore, the system can be extended to interact with all the modern big data analysis technologies

The DECIDE Project: Designing and Implementing a Prototype Service for Supporting Early Diagnosis of Alzheimer's Disease

This paper will present the design and implementation challenges of the innovative DECIDE service, to support research and early diagnosis of Alzheimer’s and other neurodegenerative diseases. DECIDE service, which is based on a Grid eInfrastructure, offers a set of tools providing quantitative measurements, to help researchers and clinicians make more informed diagnosis. As the service specifically targets the clinical community, it differs significantly from other initiatives since it needs to comply with the requirements imposed by the clinical routine in terms of accuracy, robustness, ease of use, data handling policies, adherence to clinical praxis. Moreover, sustainability aspects will also be discussed, since DECIDE aims to propose such service as a reference at European level, possibly extending it to other pathologies. We will then summarize the main results obtained to date, and the possible future developments

A formal architecture-centric and model driven approach for the engineering of science gateways

From n-Tier client/server applications, to more complex academic Grids, or even the most recent and promising industrial Clouds, the last decade has witnessed significant developments in distributed computing. In spite of this conceptual heterogeneity, Service-Oriented Architecture (SOA) seems to have emerged as the common and underlying abstraction paradigm, even though different standards and technologies are applied across application domains. Suitable access to data and algorithms resident in SOAs via so-called ‘Science Gateways’ has thus become a pressing need in order to realize the benefits of distributed computing infrastructures.In an attempt to inform service-oriented systems design and developments in Grid-based biomedical research infrastructures, the applicant has consolidated work from three complementary experiences in European projects, which have developed and deployed large-scale production quality infrastructures and more recently Science Gateways to support research in breast cancer, pediatric diseases and neurodegenerative pathologies respectively. In analyzing the requirements from these biomedical applications the applicant was able to elaborate on commonly faced issues in Grid development and deployment, while proposing an adapted and extensible engineering framework. Grids implement a number of protocols, applications, standards and attempt to virtualize and harmonize accesses to them. Most Grid implementations therefore are instantiated as superposed software layers, often resulting in a low quality of services and quality of applications, thus making design and development increasingly complex, and rendering classical software engineering approaches unsuitable for Grid developments.The applicant proposes the application of a formal Model-Driven Engineering (MDE) approach to service-oriented developments, making it possible to define Grid-based architectures and Science Gateways that satisfy quality of service requirements, execution platform and distribution criteria at design time. An novel investigation is thus presented on the applicability of the resulting grid MDE (gMDE) to specific examples and conclusions are drawn on the benefits of this approach and its possible application to other areas, in particular that of Distributed Computing Infrastructures (DCI) interoperability, Science Gateways and Cloud architectures developments