Abstract. BPEL4WS is a well-established business process standard that can be used to orchestrate service-based workflows. However, the rapid growth and automation demands of e-business and grid applications require BPEL4WS to provide enhanced semantic annotations to achieve the goal of business processes automation. Here, OWL-S (OWL for Web Services) is designed to represent such kind of semantic information. Furthermore, there exists a similarity in the conceptual model of OWL-S and BPEL4WS that can be employed to overcome the lack of semantics in BPEL4WS by mapping the BPEL4WS process model to the OWL-S suite of ontologies. The mapped OWL-S service can be used to increase flexibility and to automate BPEL based grid scenarios even further. This is achieved by dynamic discovery, composition and invocation of OWL-S services, for example within e-business and grid environments. Hence, the aim of this paper is to establish a mapping from the BPEL process model to the complete OWL-S suite of ontologies. We present a mapping strategy and a tool supporting this strategy. This allows the semantic annotation of workflows defined as BPEL4WS processes to enable the automation of a variety of e-business tasks.
Business applications are more and more often developed on the basis of Web services. The aim is to provide platform independence and loose coupling between business applications to facilitate distributed and grid computing scenarios. However, most efforts to deploy and publish Web services are manual. Manual discovery, invocation and composition of Web services in a distributed computing environment significantly hamper the automatic process of enterprise application integration. Semantic enhancements in Web services aim at making the process of Web services discovery, invocation and composition dynamic by exposing the machine understandable description of Web service capabilities and Web service requests. In this paper we compare recent dynamic Web service composition approaches. We highlight some dynamic composition issues and compare existing approaches with respect to these issues. Based on these findings we present a new and generic semantic Web services integration and composition lifecycle tofacilitate the semantic based integration and composition of Grid services. The proposed semantic Web services integration and composition life cycle explains the necessary integration phases beginning with the modeling and developing of processes as Web service composition and ending with their execution. With this lifecycle, integration hurdles among diferent service composition approaches will be diminished. Disciplines Physical Sciences and Mathematics
Purpose Citation analysis is an important measure for the assessment of quality and impact of academic entities (authors, papers and publication venues) used for ranking of research articles, authors and publication venues. It is a common observation that high-level publication venues, with few exceptions (Nature, Science and PLOS ONE), are usually topic specific. The purpose of this paper is to investigate the claim correlation analysis between topic specificity and citation count of different types of publication venues (journals, conferences and workshops). Design/methodology/approach The topic specificity was calculated using the information theoretic measure of entropy (which tells us about the disorder of the system). The authors computed the entropy of the titles of the papers published in each venue type to investigate their topic specificity. Findings It was observed that venues usually with higher citations (high-level publication venues) have low entropy and venues with lesser citations (not-high-level publication venues) have high entropy. Low entropy means less disorder and more specific to topic and vice versa. The input data considered here were DBLP-V7 data set for the last 10 years. Experimental analysis shows that topic specificity and citation count of publication venues are negatively correlated to each other. Originality/value This paper is the first attempt to discover correlation between topic sensitivity and citation counts of publication venues. It also used topic specificity as a feature to rank academic entities.
The need for smart e-learning environments is resulting in new challenges for researchers and practitioners to develop intelligent systems that can be used to automate the Higher Education (HE) activities in an intelligent way. Some common examples of such activities are “analyzing, finding, and ranking the right resource to teach a course,” “analyzing and finding the people with common research interests to start joint research projects,” and “using data analytics and machine reasoning techniques for conducting the exams with different levels of complexities.” Ontological reasoning and smart data analytics can play an important role in analyzing and automating these HE activities and processes. In this paper, we present a framework named as Higher Education Activities and Processes Automation Framework (HEAPAF). The HEAPAF framework can be used to identify, extract, process, and produce the semantically enriched data in machine understandable format from different educational resources. We also present the Higher Education Ontology (HEO) that we designed and developed to accommodate the HE data and then to perform analysis and reasoning on it. As a proof of concept, we present a case study on the topic, “analyzing, finding, and ranking the right resources to teach a course,” which can dramatically improve the learning patterns of students in the growing smart educational environment. Finally, we provide the evaluation of our framework as evidence of its competency and consistency in improving academic analytics for educational activities and processes by using machine reasoning.
With the advancement of technology, academics and curriculum developers are always under pressure to provide students with skills that match the market’s requirements. A systematic and continuous examination of the market is needed, to stay up to date with the required skills, and then to update the curriculum to train the students with required market skills. In this article, we present a framework referred to as Align My Curriculum (AMC). The AMC framework aims to facilitate alignment between acquired university curriculum outcomes and required market skills. It can be used to classify, compare and visualize the data of a university curriculum and job vacancies in the market. The presented framework benefits academics and curriculum developers by improving the courses and therefore bridging the skills gap. Stakeholders from both academia and industry can gain insights into the predominant required and acquired skills. In addition, it may be useful for analysts, students, and job applicants. This article describes the architecture, implementation and experimental results, with visual analysis to help decision and policy-makers.
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