arXiv subjects

Richard McClatchey

Publications and source records attributed to Richard McClatchey.

At least 55 records · Page 3Linked to original sources

arXiv2007

The Requirements for Ontologies in Medical Data Integration: A Case Study

Evidence-based medicine is critically dependent on three sources of information: a medical knowledge base, the patients medical record and knowledge of available resources, including where appropriate, clinical protocols. Patient data is often scattered in a variety of databases and may, in a distributed model, be held across several disparate repositories. Consequently addressing the needs of an evidence-based medicine community presents issues of biomedical data integration, clinical interpretation and knowledge management. This paper outlines how the Health-e-Child project has approached the challenge of requirements specification for (bio-) medical data integration, from the level of cellular data, through disease to that of patient and population. The approach is illuminated through the requirements elicitation and analysis of Juvenile Idiopathic Arthritis (JIA), one of three diseases being studied in the EC-funded Health-e-Child project.

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arXiv2007

Scheduling in Data Intensive and Network Aware (DIANA) Grid Environments

In Grids scheduling decisions are often made on the basis of jobs being either data or computation intensive: in data intensive situations jobs may be pushed to the data and in computation intensive situations data may be pulled to the jobs. This kind of scheduling, in which there is no consideration of network characteristics, can lead to performance degradation in a Grid environment and may result in large processing queues and job execution delays due to site overloads. In this paper we describe a Data Intensive and Network Aware (DIANA) meta-scheduling approach, which takes into account data, processing power and network characteristics when making scheduling decisions across multiple sites. Through a practical implementation on a Grid testbed, we demonstrate that queue and execution times of data-intensive jobs can be significantly improved when we introduce our proposed DIANA scheduler. The basic scheduling decisions are dictated by a weighting factor for each potential target location which is a calculated function of network characteristics, processing cycles and data location and size. The job scheduler provides a global ranking of the computing resources and then selects an optimal one on the basis of this overall access and execution cost. The DIANA approach considers the Grid as a combination of active network elements and takes network characteristics as a first class criterion in the scheduling decision matrix along with computation and data. The scheduler can then make informed decisions by taking into account the changing state of the network, locality and size of the data and the pool of available processing cycles.

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arXiv2006

From Grid Middleware to a Grid Operating System

Grid computing has made substantial advances during the last decade. Grid middleware such as Globus has contributed greatly in making this possible. There are, however, significant barriers to the adoption of Grid computing in other fields, most notably day-to-day user computing environments. We will demonstrate in this paper that this is primarily due to the limitations of the existing Grid middleware which does not take into account the needs of everyday scientific and business users. In this paper we will formally advocate a Grid Operating System and propose an architecture to migrate Grid computing into a Grid operating system which we believe would help remove most of the technical barriers to the adoption of Grid computing and make it relevant to the day-to-day user. We believe this proposed transition to a Grid operating system will drive more pervasive Grid computing research and application development and deployment in future.

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arXiv2006

Bulk Scheduling with the DIANA Scheduler

Results from the research and development of a Data Intensive and Network Aware (DIANA) scheduling engine, to be used primarily for data intensive sciences such as physics analysis, are described. In Grid analyses, tasks can involve thousands of computing, data handling, and network resources. The central problem in the scheduling of these resources is the coordinated management of computation and data at multiple locations and not just data replication or movement. However, this can prove to be a rather costly operation and efficient sing can be a challenge if compute and data resources are mapped without considering network costs. We have implemented an adaptive algorithm within the so-called DIANA Scheduler which takes into account data location and size, network performance and computation capability in order to enable efficient global scheduling. DIANA is a performance-aware and economy-guided Meta Scheduler. It iteratively allocates each job to the site that is most likely to produce the best performance as well as optimizing the global queue for any remaining jobs. Therefore it is equally suitable whether a single job is being submitted or bulk scheduling is being performed. Results indicate that considerable performance improvements can be gained by adopting the DIANA scheduling approach.

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arXiv2006

Final Results from and Exploitation Plans for MammoGrid

The MammoGrid project has delivered the first deployed instance of a healthgrid for clinical mammography that spans national boundaries. During the last year, the final MammoGrid prototype has undergone a series of rigorous tests undertaken by radiologists in the UK and Italy and this paper draws conclusions from those tests for the benefit of the Healthgrid community. In addition, lessons learned during the lifetime of the project are detailed and recommendations drawn for future health applications using grids. Following the completion of the project, plans have been put in place for the commercialisation of the MammoGrid system and this is also reported in this article. Particular emphasis is placed on the issues surrounding the transition from collaborative research project to a marketable product. This paper concludes by highlighting some of the potential areas of future development and research.

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arXiv2006

Health-e-Child : An Integrated Biomedical Platform for Grid-Based Paediatric Applications

There is a compelling demand for the integration and exploitation of heterogeneous biomedical information for improved clinical practice, medical research, and personalised healthcare across the EU. The Health-e-Child project aims at developing an integrated healthcare platform for European Paediatrics, providing seamless integration of traditional and emerging sources of biomedical information. The long-term goal of the project is to provide uninhibited access to universal biomedical knowledge repositories for personalised and preventive healthcare, large-scale information-based biomedical research and training, and informed policy making. The project focus will be on individualised disease prevention, screening, early diagnosis, therapy and follow-up of paediatric heart diseases, inflammatory diseases, and brain tumours. The project will build a Grid-enabled European network of leading clinical centres that will share and annotate biomedical data, validate systems clinically, and diffuse clinical excellence across Europe by setting up new technologies, clinical workflows, and standards. This paper outlines the design approach being adopted in Health-e-Child to enable the delivery of an integrated biomedical information platform.

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arXiv2006

Deriving Conceptual Data Models from Domain Ontologies for Bioinformatics

This paper studies the role that ontologies can play in establishing conceptual data models during the process of information systems development. A mapping algorithm has been proposed and embedded in a special purpose Transformation-Engine to generate a conceptual data model from a given domain ontology. In addition, this paper focuses on applying the proposed approach to a bioinformatics context as the nature of biological data is considered a barrier in representing biological conceptual data models. Both quantitative and qualitative methods have been adopted to critically evaluate this new approach. The results of this evaluation indicate that the quality of the generated conceptual data models can reflect the problem domain entities and the associations between them. The results are encouraging and support the potential role that this approach can play in providing a suitable starting point for conceptual data model development.

cs.SE↗

arXiv2006

Digital Libraries: From Process Modelling to Grid-based Service Oriented Architecture

Graphical Business Process Modelling Languages (BPML) like Role Activity Diagrams (RAD) provide ease and flexibility for modelling business behaviour. However, these languages show limited applicability in terms of enactment over distributed systems paradigms like Service Oriented Architecture (SOA) based grid computing. This paper investigates RAD modelling of a Scientific Publishing Process (SPP) for Digital Libraries (DL) and tries to determine the suitability of Pi-Calculus based formal approaches to enact SOA based grid computing. In order to achieve this purpose, the Pi-Calculus based formal transformation from a RAD model of SPP for DL draws attention towards a number of challenging issues including issues that require particular design considerations for appropriate enactment in a SOA based grid system.

cs.DL↗

arXiv2006

Bulk Scheduling with DIANA Scheduler

Results from and progress on the development of a Data Intensive and Network Aware (DIANA) Scheduling engine, primarily for data intensive sciences such as physics analysis, are described. Scientific analysis tasks can involve thousands of computing, data handling, and network resources and the size of the input and output files and the amount of overall storage space allocated to a user necessarily can have significant bearing on the scheduling of data intensive applications. If the input or output files must be retrieved from a remote location, then the time required transferring the files must also be taken into consideration when scheduling compute resources for the given application. The central problem in this study is the coordinated management of computation and data at multiple locations and not simply data movement. However, this can be a very costly operation and efficient scheduling can be a challenge if compute and data resources are mapped without network cost. We have implemented an adaptive algorithm within the DIANA Scheduler which takes into account data location and size, network performance and computation capability to make efficient global scheduling decisions. DIANA is a performance-aware as well as an economy-guided Meta Scheduler. It iteratively allocates each job to the site that is likely to produce the best performance as well as optimizing the global queue for any remaining pending jobs. Therefore it is equally suitable whether a single job is being submitted or bulk scheduling is being performed. Results suggest that considerable performance improvements are to be gained by adopting the DIANA scheduling approach.

cs.DC↗

arXiv2006

A Formal Architecture-Centric Model-Driven Approach for the Automatic Generation of Grid Applications

This paper discusses the concept of model-driven software engineering applied to the Grid application domain. As an extension to this concept, the approach described here, attempts to combine both formal architecture-centric and model-driven paradigms. It is a commonly recognized statement that Grid systems have seldom been designed using formal techniques although from past experience such techniques have shown advantages. This paper advocates a formal engineering approach to Grid system developments in an effort to contribute to the rigorous development of Grids software architectures. This approach addresses quality of service and cross-platform developments by applying the model-driven paradigm to a formal architecture-centric engineering method. This combination benefits from a formal semantic description power in addition to model-based transformations. The result of such a novel combined concept promotes the re-use of design models and facilitates developments in Grid computing.

cs.SE↗

arXiv2006

Engineering Conceptual Data Models from Domain Ontologies: A Critical Evaluation

This paper studies the differences and similarities between domain ontologies and conceptual data models and the role that ontologies can play in establishing conceptual data models during the process of information systems development. A mapping algorithm has been proposed and embedded in a special purpose Transformation Engine to generate a conceptual data model from a given domain ontology. Both quantitative and qualitative methods have been adopted to critically evaluate this new approach. In addition, this paper focuses on evaluating the quality of the generated conceptual data model elements using Bunge-Wand-Weber and OntoClean ontologies. The results of this evaluation indicate that the generated conceptual data model provides a high degree of accuracy in identifying the substantial domain entities along with their attributes and relationships being derived from the consensual semantics of domain knowledge. The results are encouraging and support the potential role that this approach can take part in process of information system development.

cs.SE↗

arXiv2005

A Model-driven Approach for Grid Services Engineering

As a consequence to the hype of Grid computing, such systems have seldom been designed using formal techniques. The complexity and rapidly growing demand around Grid technologies has favour the use of classical development techniques, resulting in no guidelines or rules and unstructured engineering processes. This paper advocates a formal approach to Grid applications development in an effort to contribute to the rigorous development of Grids software architectures. This approach addresses cross-platform interoperability and quality of service; the model-driven paradigm is applied to a formal architecture-centric engineering method in order to benefit from the formal semantic description power in addition to model-based transformations. The result of such a novel combined concept promotes the re-use of design models and eases developments in Grid computing by providing an adapted development process and ensuring correctness at each design step.

cs.SE↗

arXiv2005

The MammoGrid Virtual Organisation - Federating Distributed Mammograms

The MammoGrid project aims to deliver a prototype which enables the effective collaboration between radiologists using grid, service-orientation and database solutions. The grid technologies and service-based database management solution provide the platform for integrating diverse and distributed resources, creating what is called a virtual organisation. The MammoGrid Virtual Organisation facilitates the sharing and coordinated access to mammography data, medical imaging software and computing resources of participating hospitals. Hospitals manage their local database of mammograms, but in addition, radiologists who are part of this organisation can share mammograms, reports, results and image analysis software. The MammoGrid Virtual Organisation is a federation of autonomous multi-centres sites which transcends national boundaries. This paper outlines the service-based approach in the creation and management of the federated distributed mammography database and discusses the role of virtual organisations in distributed image analysis.

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arXiv2005

JClarens: A Java Framework for Developing and Deploying Web Services for Grid Computing

High Energy Physics (HEP) and other scientific communities have adopted Service Oriented Architectures (SOA) as part of a larger Grid computing effort. This effort involves the integration of many legacy applications and programming libraries into a SOA framework. The Grid Analysis Environment (GAE) is such a service oriented architecture based on the Clarens Grid Services Framework and is being developed as part of the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) at European Laboratory for Particle Physics (CERN). Clarens provides a set of authorization, access control, and discovery services, as well as XMLRPC and SOAP access to all deployed services. Two implementations of the Clarens Web Services Framework (Python and Java) offer integration possibilities for a wide range of programming languages. This paper describes the Java implementation of the Clarens Web Services Framework called JClarens. and several web services of interest to the scientific and Grid community that have been deployed using JClarens.

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arXiv2005

Resource Management Services for a Grid Analysis Environment

Selecting optimal resources for submitting jobs on a computational Grid or accessing data from a data grid is one of the most important tasks of any Grid middleware. Most modern Grid software today satisfies this responsibility and gives a best-effort performance to solve this problem. Almost all decisions regarding scheduling and data access are made by the software automatically, giving users little or no control over the entire process. To solve this problem, a more interactive set of services and middleware is desired that provides users more information about Grid weather, and gives them more control over the decision making process. This paper presents a set of services that have been developed to provide more interactive resource management capabilities within the Grid Analysis Environment (GAE) being developed collaboratively by Caltech, NUST and several other institutes. These include a steering service, a job monitoring service and an estimator service that have been designed and written using a common Grid-enabled Web Services framework named Clarens. The paper also presents a performance analysis of the developed services to show that they have indeed resulted in a more interactive and powerful system for user-centric Grid-enabled physics analysis.

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arXiv2005

Heterogeneous Relational Databases for a Grid-enabled Analysis Environment

Grid based systems require a database access mechanism that can provide seamless homogeneous access to the requested data through a virtual data access system, i.e. a system which can take care of tracking the data that is stored in geographically distributed heterogeneous databases. This system should provide an integrated view of the data that is stored in the different repositories by using a virtual data access mechanism, i.e. a mechanism which can hide the heterogeneity of the backend databases from the client applications. This paper focuses on accessing data stored in disparate relational databases through a web service interface, and exploits the features of a Data Warehouse and Data Marts. We present a middleware that enables applications to access data stored in geographically distributed relational databases without being aware of their physical locations and underlying schema. A web service interface is provided to enable applications to access this middleware in a language and platform independent way. A prototype implementation was created based on Clarens [4], Unity [7] and POOL [8]. This ability to access the data stored in the distributed relational databases transparently is likely to be a very powerful one for Grid users, especially the scientific community wishing to collate and analyze data distributed over the Grid.

cs.DC↗

arXiv2005

A Semantic Grid-based E-Learning Framework (SELF)

E-learning can be loosely defined as a wide set of applications and processes, which uses available electronic media (and tools) to deliver vocational education and training. With its increasing recognition as an ubiquitous mode of instruction and interaction in the academic as well as corporate world, the need for a scaleable and realistic model is becoming important. In this paper we introduce SELF; a Semantic grid-based E-Learning Framework. SELF aims to identify the key-enablers in a practical grid-based E-learning environment and to minimize technological reworking by proposing a well-defined interaction plan among currently available tools and technologies. We define a dichotomy with E-learning specific application layers on top and semantic grid-based support layers underneath. We also map the latest open and freeware technologies with various components in SELF.

cs.DC↗

arXiv2004

Reverse Engineering Ontology to Conceptual Data Models

Ontologies facilitate the integration of heterogeneous data sources by resolving semantic heterogeneity between them. This research aims to study the possibility of generating a domain conceptual model from a given ontology with the vision to grow this generated conceptual data model into a global conceptual model integrating a number of existing data and information sources. Based on ontologically derived semantics of the BWW model, rules are identified that map elements of the ontology language (DAML+OIL) to domain conceptual model elements. This mapping is demonstrated using TAMBIS ontology. A significant corollary of this study is that it is possible to generate a domain conceptual model from a given ontology subject to validation that needs to be performed by the domain specialist before evolving this model into a global conceptual model.

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