Applying semantic web services to enterprise web

Enterprise Web provides a convenient, extendable, integrated platform for information sharing and knowledge management. However, it still has many drawbacks due to complexity and increasing information glut, as well as the heterogeneity of the information processed. Research in the field of Semantic Web Services has shown the possibility of adding higher level of semantic functionality onto the top of current Enterprise Web, enhancing usability and usefulness of resource, enabling decision support and automation. This paper aims to explore the use of Semantic Web Services in Enterprise Web and discuss the Semantic Web Services (SWS) approach for designing Enterprise Web applications. A Semantic Web Service oriented model is presented, in which resources and services are described by ontology, and processed through Semantic Web Service, allowing integrated administration, interoperability and automated reasoning

The ReSIST Resilience Knowledge Base

We describe a prototype knowledge base that uses semantic web technologies to provide a service for querying a large and expanding collection of public data about resilience, dependability and security. We report progress and identify opportunities to support resilience-explicit computing by developing metadata-based descriptions of resilience mechanisms that can be used to support design time and, potentially, run-time decision making

Transparent and scalable client-side server selection using netlets

Replication of web content in the Internet has been found to improve service response time, performance and reliability offered by web services. When working with such distributed server systems, the location of servers with respect to client nodes is found to affect service response time perceived by clients in addition to server load conditions. This is due to the characteristics of the network path segments through which client requests get routed. Hence, a number of researchers have advocated making server selection decisions at the client-side of the network. In this paper, we present a transparent approach for client-side server selection in the Internet using Netlet services. Netlets are autonomous, nomadic mobile software components which persist and roam in the network independently, providing predefined network services. In this application, Netlet based services embedded with intelligence to support server selection are deployed by servers close to potential client communities to setup dynamic service decision points within the network. An anycast address is used to identify available distributed decision points in the network. Each service decision point transparently directs client requests to the best performing server based on its in-built intelligence supported by real-time measurements from probes sent by the Netlet to each server. It is shown that the resulting system provides a client-side server selection solution which is server-customisable, scalable and fault transparent

Decision support for optimised irrigation scheduling

The system, developed under the FLOW-AID (an FP6 project), is a farm level water management system of special value in situations where the water availability and quality is limited. This market-ready precision irrigation management system features new models, hardware and software. The hardware platform delivers a maintenance-free low cost dielectric tensiometer and several low-end irrigation or fertigation controllers for serving different situations. The software includes a complete, web based, Decision Support System (DSS) that consists of an expert planner for farm zoning (MOPECO) and a universal irrigation scheduler, based on crop-water stress models (UNIPI) and water and nutrient uptake calculations. The system, designed also to service greenhouse fertigation and hydroponics, is scalable from one to many zones. It consists of 1) a data gathering tool which uploads agronomic data, from monitored crops around the world, to a central web Data Base (DB), and 2) a web based Decision Support System (DSS). The DSS processes intelligently the data of the crop using Crop Response Models, Nutrient Uptake Models and Water Uptake Models. The central system returns over Internet to the low-end controller a command file containing water scheduling and nutrient supply guideline

IMPLEMENTASI APLIKASI PEMINJAMAN KENDARAAN DINAS OPERASIONAL BERBASIS MOBILE ANDROID MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW)

In the current modern era, the business sector, especially banking, has used a lot of technology. This is done because to support the work process of a business. The technology needs analysis that has been carried out is the mobile and web application system for the Operational Service Vehicle Loan (KDO) which is expected to be online 1 x 24 hours, has backup recovery and can be accessed via web and android so that the operational service vehicle loan process at Bank UOB Jakarta can run. more efficient. Like large companies in general, each company has procedures and SOPs (Standard Operating Procedures) in the process of borrowing KDO (Operational Service Vehicles. In this case PT. Bank OUB Jakarta is still implementing the Service Operational Vehicle Borrowing (KDO) system manually and has not implemented decision support system in leasing operational official vehicles. Therefore, a decision support system is needed to support and facilitate employees in choosing a car. Many decision support system methods are often used, including the Simple Additive Weighting (SAW) method. Application development methods in research This study uses Simple Additive Weighting (SAW) which is expected to help the Operational Service Vehicle Loan process at PT. Bank UOB Jakarta to be efficient. The results of this study have successfully made an application for a decision support system for loaning operational service vehicles at PT Bank UOB Jakarta using m the Simple Additive Weighting (SAW) method based on android mobile by using the input of 5 criteria for borrowing operational official vehicles. Keywords: Mobile Application, Operational Service vehicle loan, onlin

An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data

As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards. The key feature of the portal is the ability to display co-plotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standards-based web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data. Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations

A decision support system for QoS-enabled distributed web services architecture

Service selection is crucial for fulfilling the requirements of service requestors. While in the real service-oriented environment, Quality of Services (QoS) is one of the greatest concerns for consumers during service selection. Existing web services "standards do not tackle the QoS issue adequately when service discovery and selection are performed. In this paper, we argue that the process of services selection is a kind of decision making" to decide which service should be selected dependent on their QoS and trustworthiness values as well as their functional capabilities. Hence, we propose a service selection solution which utilizes the Decision Support Systems Module (DSS Module) to select the most appropriate service. In DSS module we introduce Service Trust to carry out the service QoS measurement based on the Context-specific Quality Aspects. The architecture of DSS module is presented in detail and the solution is also integrated into one of the components "domain broker" in our proposed distributed web services architecture. The contributions of this paper are two fold. Firstly, we apply DSS module into web services, thus opening a new, fertile ground for DSS research in web services literature and secondly, we provide a novel and feasible solution for QoS-based service selection

A new trend for knowledge-based decision support systems design

Knowledge-based decision support systems (KBDSS) have evolved greatly over the last few decades. The key technologies underpinning the development of KBDSS can be classified into three categories: technologies for knowledge modelling and representation, technologies for reasoning and inference and web-based technologies. In the meantime, service systems have emerged and become increasingly important to value adding activities in the current knowledge economy. This paper provides a review on the recent advances in the three types of technologies, as well as the main application domains of KBDSS as service systems. Based on the examination of literature, future research directions are recommended for the development of KBDSS in general and in particular to support decision-making in service industry

A method for service quality assessment in a service ecosystem

the increasing proliferation of independent application service providers is making traditional IT infrastructure insufficient when dealing with new issues that appear in a dynamic outsourcing business model. Quality of Service (QoS) gradually becomes an essential benchmark to differentiate diverse service providers during service selection process. In this paper, we argue service selection can be deemed as a decision making process - to decide which services providers should be selected within the specified service provision context during a definitive timeslot. Thus, existing decision support approaches can be leveraged if applicable. Hence, we propose a service selection solution which utilizes the Decision Support Systems Module (DSS Module) to select the most appropriate service. In DSS module we introduce AHP model to carry out the service QoS measurement based on the Context-specific Quality Aspects. The contributions of this paper are two folds. Firstly, we provide a novel and feasible solution for QoS-based service selection and secondly, we apply DSS module into web services, thus opening a new, fertile ground for DSS research in service ecosystem literature

The role of linked data and the semantic web in building operation

Effective Decision Support Systems (DSS) for building service managers require adequate performance data from many building data silos in order to deliver a complete view of building performance. Current performance analysis techniques tend to focus on a limited number of data sources, such as BMS measured data (temperature, humidity, C02), excluding a wealth of other data sources increasingly available in the modern building, including weather data, occupant feedback, mobile sensors & feedback systems, schedule information, equipment usage information. This paper investigates the potential for using Linked Data and Semantic Web technologies to improve interoperability across AEC domains, overcoming many of the roadblocks hindering information transfer currently