Hong Qing Yu

A Method for Automated Web Service Selection

Automated Web service selection is a key challenge in Service Oriented Architecture (SOA) research. With SOA becoming more popular in industry, and more Web services becoming available in the e-business market, the main issue changes from service discovery to service selection and ranking. In this paper, we propose a novel nonfunctional property-based service selection method by modifying the Logic Scoring Preference (LSP) method with Ordered Weighted Averaging (OWA) Operators. Moreover, the dynamic mechanism for evaluating metadata based QoS criteria of each service is presented for this method.

Service Selection Based on Non-functional Properties

Service-oriented Architecture supports software to be composed from services dynamically. Selecting and composing appropriate services according to business process, policies and non-functional constraints is an essential challenge. This paper proposes a method for automatic selection of the most relevant service for composition based on non-functional properties and the users context. In doing this we also propose a method of obtaining and evaluating non-functional aspects.

Using Linked Data to Annotate and Search Educational Video Resources for Supporting Distance Learning

Multimedia educational resources play an important role in education, particularly for distance learning environments. With the rapid growth of the multimedia web, large numbers of educational video resources are increasingly being created by several different organizations. It is crucial to explore, share, reuse, and link these educational resources for better e-learning experiences. Most of the video resources are currently annotated in an isolated way, which means that they lack semantic connections. Thus, providing the facilities for annotating these video resources is highly demanded. These facilities create the semantic connections among video resources and allow their metadata to be understood globally. Adopting Linked Data technology, this paper introduces a video annotation and browser platform with two online tools: Annomation and SugarTube. Annomation enables users to semantically annotate video resources using vocabularies defined in the Linked Data cloud. SugarTube allows users to browse semantically linked educational video resources with enhanced web information from different online resources. In the prototype development, the platform uses existing video resources for the history courses from the Open University (United Kingdom). The result of the initial development demonstrates the benefits of applying Linked Data technology in the aspects of reusability, scalability, and extensibility.

A Backwards Composition Context Based Service Selection Approach for Service Composition

In SOA applications are built from individual services offered by different providers. Typically an application comprises of several such services usually stemming from different providers leading to the question of which services to select and compose. We present the new concept of composition context together with a novel service selection algorithm. The approach has been evaluated in our test bed and shows good scalability.

inContext: A Pervasive and Collaborative Working Environment for Emerging Team Forms

Participants in current team collaborations belong to different organizations, work on multiple objectives at the same time, and frequently change locations. They use different devices and infrastructures in collaboration processes that can last from a few hours to several years. All these factors pose new challenges to the development of collaborative working environments (CWEs). Existing CWEs are unable to support emerging teams because diverse collaboration services are not well integrated or adapting to the team context. We present the inContext approach to providing a novel pervasive CWE infrastructure for emerging team forms. inContext aggregates disparate collaboration services using Web services and Semantic Web technologies and provides a platform that captures diverse dynamic aspects of team collaborations. By utilizing runtime and historical context and interaction information, adaptation techniques can be deployed to cope with the changes of emerging teams.

Automated Context-Aware Service Selection for Collaborative Systems

Service-Oriented Architecture (SOA) can provide a paradigm for constructing context-aware collaboration systems. Particularly, the promise of inexpensive context-aware collaboration devices and context-awareness for supporting the selection of suitable services at run-time have provoked growing adoptation of SOA in collaborative systems. In this paper, we introduce an approach for selecting the most suitable service within a SOA based collaboration system, where suitability depends on the users context. The approach includes context modelling, generation of context-aware selection criteria and a suitable service selection methodology.

SmartLink: a web-based editor and search environment for linked services

Despite considerable research dedicated to Semantic Web Services (SWS), structured semantics are still not used significantly to annotate Web services and APIs. This is due to the complexity of comprehensive SWS models and has led to the emergence of a new approach dubbed Linked Services. Linked Services adopt Linked Data principles to produce simplified, RDFbased service descriptions that are easier to create and interpret. However, current Linked Services editors assume the existence of services documentation in the form of HTML or WSDL files. Therefore, we introduce SmartLink, a Web-based editor and search environment for Linked Services. Based on an easy-to-use Web form and a REST-ful API, SmartLink allows both humans as well as machines to produce light-weight service descriptions from scratch.

Two-Staged Approach for Semantically Annotating and Brokering TV-related Services

Nowadays, more and more distributed digital TV and TV-related resources are published on the Web, such as Electronic Personal TV Guide (EPG) data. To enable applications to access these resources easily, the TV resource data is commonly provided by Web service technologies. The huge variety of data related to the TV domain and the wide range of services that provide it, raises the need to have a broker to discover, select and orchestrate services to satisfy the runtime requirements of applications that invoke these services. The variety of data and heterogeneous nature of the service capabilities makes it a challenging domain for automated web-service discovery and composition. To overcome these issues, we propose a two-stage service annotation approach, which is resolved by integrating Linked Services and IRS-III semantic web services framework, to complete the lifecycle of service annotating, publishing, deploying, discovering, orchestration and dynamic invocation. This approach satisfies both developer’s and application’s requirements to use Semantic Web Services (SWS) technologies manually and automatically.

An automated approach to Semantic Web Services Mediation

Semantic Web Services (SWS) aim at the automated discovery, selection and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. However, heterogeneities between distinct SWS representations pose strong limitations w.r.t. interoperability and reusability. Hence, semantic-level mediation, i.e. mediation between concurrent semantic representations of services, is a key requirement to allow SWS matchmaking algorithms to compare capabilities of distinct SWS. Semantic-level mediation requires to identify similarities across distinct SWS representations. Since current approaches rely either on manual one-to-one mappings or on semi-automatic mappings based on the exploitation of linguistic or structural similarities, these are perceived to be costly and error-prone. We propose a mediation approach enabling the implicit representation of similarities across distinct SWS by grounding these in so-called Mediation Spaces (MS). Given a set of SWS and their respective MS grounding, a general-purpose mediator automatically computes similarities to identify the most appropriate SWS for a given request. A prototypical application illustrates our approach.

Linked Context: A Linked Data Approach to Personalised Service Provisioning

Nowadays personalised service provisioning becomes more feasible due to the increasing availability of smart devices, such as smart phones, tablet computers, Personal Digital Assistants and Play stations. These smart devices can dynamically detect the context data and upload them to support other interesting software applications, such as Facebook and Google maps. Context can become richer and more retrievable if links are established for semantically related context data sets. Taking advantage of the recent digital and Web technologies, this paper proposes a novel Linked Context model that applies the Linked Data principles to model and obtain context data from both users and services in one unified framework to support personalised service provisioning at runtime.