Small-world networks, distributed hash tables and the e-resource discovery problem

Resource discovery is one of the most important underpinning problems behind producing a scalable, robust and efficient global infrastructure for e-Science. A number of approaches to the resource discovery and management problem have been made in various computational grid environments and prototypes over the last decade. Computational resources and services in modern grid and cloud environments can be modelled as an overlay network superposed on the physical network structure of the Internet and World Wide Web. We discuss some of the main approaches to resource discovery in the context of the general properties of such an overlay network. We present some performance data and predicted properties based on algorithmic approaches such as distributed hash table resource discovery and management. We describe a prototype system and use its model to explore some of the known key graph aspects of the global resource overlay network - including small-world and scale-free properties

Sensor Search Techniques for Sensing as a Service Architecture for The Internet of Things

The Internet of Things (IoT) is part of the Internet of the future and will comprise billions of intelligent communicating "things" or Internet Connected Objects (ICO) which will have sensing, actuating, and data processing capabilities. Each ICO will have one or more embedded sensors that will capture potentially enormous amounts of data. The sensors and related data streams can be clustered physically or virtually, which raises the challenge of searching and selecting the right sensors for a query in an efficient and effective way. This paper proposes a context-aware sensor search, selection and ranking model, called CASSARAM, to address the challenge of efficiently selecting a subset of relevant sensors out of a large set of sensors with similar functionality and capabilities. CASSARAM takes into account user preferences and considers a broad range of sensor characteristics, such as reliability, accuracy, location, battery life, and many more. The paper highlights the importance of sensor search, selection and ranking for the IoT, identifies important characteristics of both sensors and data capture processes, and discusses how semantic and quantitative reasoning can be combined together. This work also addresses challenges such as efficient distributed sensor search and relational-expression based filtering. CASSARAM testing and performance evaluation results are presented and discussed.Comment: IEEE sensors Journal, 2013. arXiv admin note: text overlap with arXiv:1303.244

Systems biology driven software design for the research enterprise

<p>Abstract</p> <p>Background</p> <p>In systems biology, and many other areas of research, there is a need for the interoperability of tools and data sources that were not originally designed to be integrated. Due to the interdisciplinary nature of systems biology, and its association with high throughput experimental platforms, there is an additional need to continually integrate new technologies. As scientists work in isolated groups, integration with other groups is rarely a consideration when building the required software tools.</p> <p>Results</p> <p>We illustrate an approach, through the discussion of a purpose built software architecture, which allows disparate groups to reuse tools and access data sources in a common manner. The architecture allows for: the rapid development of distributed applications; interoperability, so it can be used by a wide variety of developers and computational biologists; development using standard tools, so that it is easy to maintain and does not require a large development effort; extensibility, so that new technologies and data types can be incorporated; and non intrusive development, insofar as researchers need not to adhere to a pre-existing object model.</p> <p>Conclusion</p> <p>By using a relatively simple integration strategy, based upon a common identity system and dynamically discovered interoperable services, a light-weight software architecture can become the focal point through which scientists can both get access to and analyse the plethora of experimentally derived data.</p

Application of Semantics to Solve Problems in Life Sciences

Fecha de lectura de Tesis: 10 de diciembre de 2018La cantidad de información que se genera en la Web se ha incrementado en los últimos años. La mayor parte de esta información se encuentra accesible en texto, siendo el ser humano el principal usuario de la Web. Sin embargo, a pesar de todos los avances producidos en el área del procesamiento del lenguaje natural, los ordenadores tienen problemas para procesar esta información textual. En este cotexto, existen dominios de aplicación en los que se están publicando grandes cantidades de información disponible como datos estructurados como en el área de las Ciencias de la Vida. El análisis de estos datos es de vital importancia no sólo para el avance de la ciencia, sino para producir avances en el ámbito de la salud. Sin embargo, estos datos están localizados en diferentes repositorios y almacenados en diferentes formatos que hacen difícil su integración. En este contexto, el paradigma de los Datos Vinculados como una tecnología que incluye la aplicación de algunos estándares propuestos por la comunidad W3C tales como HTTP URIs, los estándares RDF y OWL. Haciendo uso de esta tecnología, se ha desarrollado esta tesis doctoral basada en cubrir los siguientes objetivos principales: 1) promover el uso de los datos vinculados por parte de la comunidad de usuarios del ámbito de las Ciencias de la Vida 2) facilitar el diseño de consultas SPARQL mediante el descubrimiento del modelo subyacente en los repositorios RDF 3) crear un entorno colaborativo que facilite el consumo de Datos Vinculados por usuarios finales, 4) desarrollar un algoritmo que, de forma automática, permita descubrir el modelo semántico en OWL de un repositorio RDF, 5) desarrollar una representación en OWL de ICD-10-CM llamada Dione que ofrezca una metodología automática para la clasificación de enfermedades de pacientes y su posterior validación haciendo uso de un razonador OWL

Semantic Web integration of Cheminformatics resources with the SADI framework

<p>Abstract</p> <p>Background</p> <p>The diversity and the largely independent nature of chemical research efforts over the past half century are, most likely, the major contributors to the current poor state of chemical computational resource and database interoperability. While open software for chemical format interconversion and database entry cross-linking have partially addressed database interoperability, computational resource integration is hindered by the great diversity of software interfaces, languages, access methods, and platforms, among others. This has, in turn, translated into limited reproducibility of computational experiments and the need for application-specific computational workflow construction and semi-automated enactment by human experts, especially where emerging interdisciplinary fields, such as systems chemistry, are pursued. Fortunately, the advent of the Semantic Web, and the very recent introduction of RESTful Semantic Web Services (SWS) may present an opportunity to integrate all of the existing computational and database resources in chemistry into a machine-understandable, unified system that draws on the entirety of the Semantic Web.</p> <p>Results</p> <p>We have created a prototype framework of Semantic Automated Discovery and Integration (SADI) framework SWS that exposes the QSAR descriptor functionality of the Chemistry Development Kit. Since each of these services has formal ontology-defined input and output classes, and each service consumes and produces RDF graphs, clients can automatically reason about the services and available reference information necessary to complete a given overall computational task specified through a simple SPARQL query. We demonstrate this capability by carrying out QSAR analysis backed by a simple formal ontology to determine whether a given molecule is drug-like. Further, we discuss parameter-based control over the execution of SADI SWS. Finally, we demonstrate the value of computational resource envelopment as SADI services through service reuse and ease of integration of computational functionality into formal ontologies.</p> <p>Conclusions</p> <p>The work we present here may trigger a major paradigm shift in the distribution of computational resources in chemistry. We conclude that envelopment of chemical computational resources as SADI SWS facilitates interdisciplinary research by enabling the definition of computational problems in terms of ontologies and formal logical statements instead of cumbersome and application-specific tasks and workflows.</p

A Framework to Enable the Semantic Inferencing and Querying of Multimedia Content

Cultural institutions, broadcasting companies, academic, scientific and defence organisations are producing vast quantities of digital multimedia content. With this growth in audiovisual material comes the need for standardised representations encapsulating the rich semantic meaning required to enable the automatic filtering, machine processing, interpretation and assimilation of multimedia resources. Additionally generating high-level descriptions is difficult and manual creation is expensive although significant progress has been made in recent years on automatic segmentation and low-level feature recognition for multimedia. Within this paper we describe the application of semantic web technologies to enable the generation of high-level, domain-specific, semantic descriptions of multimedia content from low-level, automatically-extracted features. By applying the knowledge reasoning capabilities provided by ontologies and inferencing rules to large, multimedia data sets generated by scientific research communities, we hope to expedite solutions to the complex scientific problems they face

Discovering Services during Service-Based System Design Using UML

Recently, there has been a proliferation of service-based systems, i.e., software systems that are composed of autonomous services but can also use software code. In order to support the development of these systems, it is necessary to have new methods, processes, and tools. In this paper, we describe a UML-based framework to assist with the development of service-based systems. The framework adopts an iterative process in which software services that can provide functional and nonfunctional characteristics of a system being developed are discovered, and the identified services are used to reformulate the design models of the system. The framework uses a query language to represent structural, behavioral, and quality characteristics of services to be identified, and a query processor to match the queries against service registries. The matching process is based on distance measurements between the queries and service specifications. A prototype tool has been implemented. The work has been evaluated in terms of recall, precision, and performance measurements