A Social Network-based Framework for Data Services Selection in Modern Web Application Design

Abstract. In recent years the design of enterprise Web applications is more and more based on the integration of resources delivered through data services from outside the organization boundaries. Searching and composing existing data services offer many advantages, namely, the availability of widespread solutions in the form of services and data shared over the Web, and reduced development costs. In this scenario, new methods for speeding up the design process are emerging and, in particular, developers' social networks have been established, where developers follow other developers to learn from their choices in selecting suitable services. In this paper, we propose a framework to support data service selection for modern Web application design, by also considering the developers' social network. The network of social relationships, properly weighted with the developers' credibility, is used to compute developers' rank. This rank qualifies developers' experience in selecting data services

A PageRank-based Reputation Model for VGI Data

AbstractQuality of data is one of the key issues in the domain of Volunteered geographic information (VGI). To this purpose, in literature VGI data has been sometime compared with authoritative geospatial data. Evaluation of single contributions to VGI databases is more relevant for some applications and typically relies on evaluating reputation of contributors and using it as proxy measures for data quality. In this paper, we present a novel approach for reputation evaluation that is based on the well known PageRank algorithm for Web pages. We use a simple model for describing different versions of a geospatial entity in terms of corrections and completions. Authors, VGI contributions and their mutual relationships are modeled as nodes of a graph. In order to evaluate reputation of authors and contributions in the graph we propose an algorithm that is based on the personalized version of PageRank

Selection, Ranking and Composition of Semantically Enriched Business Processes

In Service Oriented Architectures a Business Process can be composed of several subprocesses, often exposed as platform-independent and autonomously implemented Web services. In this paper, we propose a methodological framework to support the selection, ranking and composition of semantically annotated subprocesses coming from distinct Business Process Repositories according to advanced semantics-enabled techniques

Big data as a service for monitoring cyber-physical production systems

The introduction of Internet of Services technologies is promoting manufacturing servitization of Cyber Physical Production Systems for the most important Manufacturing 4.0 capabilities, namely self-awareness, self-configuration and selfrepairing. In addition, industrial data are emerging as a new industrial asset, creating new opportunities for operations improvement, and increase industrial value through the capitalisation of immaterial assets. These recent research trends also raised several challenges and, among them, Big Data acquisition and storage. In this paper, we describe a Data as a Service approach, designed to deal with the Big Data environment. The service is able to manage data volume and velocity during the data collection phase, accumulating and summarizing measures from the machine fleet, and to proper organize them in order to serve advanced Manufacturing 4.0 facilities. Experiments on service performances demonstrate the efficiency of the proposed service

Linked Data Services and Semantics-enabled Mashup (Chapter 11)

The Web of Linked Data can be seen as a global database, where resources are identified through URIs, are self-described (by means of the URI dereferencing mechanism), and are globally connected through RDF links. Recently, research on the Web of Linked Data has been devoted to the study of models and languages to add functionalities to the Web of Linked Data by means of Linked Data services. In this chapter, we propose a new approach for “serving up” Linked Data by semantics-enabled mashup of existing Web APIs. A basic semantics-enabled model of Web APIs is proposed. The model has been designed (1) to support providers who publish new Web APIs used to access the Web of Linked Data, (2) to support the Web designer who aims at exploring and selecting available Web APIs to build or maintain a Web mashup, and (3) to make it available on top of the Web of Linked Data. Based on the proposed model, we define automated matching techniques apt to establish semantic linksamong Linked Web APIs. The model and the techniques we propose adhere to the Linked Data principles for publishing new resources on the Web of data: (1) HTTP URIs are used to identify published Web APIs, (2) useful RDF information are provided on the Web API description when someone looks up a Web API through its URI, and (3) semantic links are set to relate Web APIs to each other, thus enabling easy development and sharing of new Web mashups

Ontology-based Integration for Sharing Knowledge over the Web

In this paper, we propose a methodology developed in the framework of the VISPO project for engineering a three-layer ontology, based on the conceptualization, integration, synthesis and categorization of XML data descriptions provided by a number of sources in a virtual district, where different enterprises cooperate for business purposes. Ontologies are proposed as an unifying framework for different viewpoints by providing a shared understanding in a subject domain. Our methodology generates an ontology organized into concepts and concept relationships at different levels of detail, to provide multiple, unified views of the datasources containing heterogeneous information about the domain of interest

Characterization and search of web services through intensional knowledge

Web service technologies are widely adopted to access services and compose new applications starting from software components available from the shelf. Consequently, more and more service descriptions are becoming available on the network to designers, who often filter them according to keyword-based search, thus obtaining huge amounts of matching results, that, if not properly controlled, lead to an information overload that might cause confusion rather than knowledge. In this paper, we propose to apply data mining techniques to SOAP-based service descriptions in order to infer patterns providing a summarized and integrated representation of service functionalities. These patterns provide succinct (intensional) knowledge that can be directly queried or used to drive exploratory searches. Specifically, we proposeW-DREAM (Web services DiscoveRy via intEnsionAl knowledge Mining), an infrastructure to perform intensional service representation and querying to support application designers to select the web services that best suit their need