Improving data perturbation testing techniques for Web services

The widespread use of service-oriented architectures (SOAs) and Web services in commercial software requires the adoption of development techniques to ensure the quality of Web services. Testing techniques and tools concern quality and play a critical role in accomplishing quality of SOA based systems. Existing techniques and tools for traditional systems are not appropriate to these new systems, making the development of Web services testing techniques and tools required. This article presents new testing techniques to automatically generate a set of test cases and data for Web services. The techniques presented here explore data perturbation of Web services messages upon data types, integrity and consistency. To support these techniques, a tool (GenAutoWS) was developed and applied to real problems. (C) 2010 Elsevier Inc. All rights reserved.

Wikis semânticos: da Web para a Web Semântica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Interfaccia web per un sistema di condivisione semantica dell'informazione: studio e implementazione

Questa tesi progettuale nasce per integrare gli sforzi attuali sullo sviluppo del web semantico. La piattaforma di riferimento sulla quale è stato svolto il presente lavoro è SMART-M3. Questa piattaforma mette a disposizione uno spazio condiviso di informazioni, rappresentate e accessibili secondo le tecnologie del web semantico. In questo scenario, nasce la necessità di disporre di un'interfaccia web capace di interagire con la piattaforma - in grado di risolvere la complessità intrinseca dei dati semantici - allo scopo di averne un completo controllo; ricerche precedenti a questo proposito hanno dato come frutto una libreria PHP che mi è stata consegnata come strumento per lo sviluppo dell'interfaccia. La tesi si è articolata in 3 fasi principali: una fase iniziale di documentazione sull'argomento, eseguita principalmente sul libro “A developer's guide to the semantic web” di Liyang Yu e sulla tesi “Ontologie per il web semantico: un'analisi comparativa.” di Indrit Beqiri; una seconda fase, quella principale, di sviluppo del progetto informatico; una terza fase, infine, di sviluppo di questo elaborato di tesi, da considerarsi come la trattazione di tutto il percorso soprascritto, dall'inizio alla fine, secondo l'ordine cronologico in cui si svolto l'intero processo della tesi.

Progetto di un'applicazione web per servizi di mobilità urbana tramite l'uso di OpenData

Apertura, partecipazione, collaborazione e possibilità di creare una competenza collettiva sono i motivi che portano alla nascita e alla diffusione degli OpenData, i quali favoriscono l'interoperabilità e la trasparenza dei governi nei confronti dei cittadini, inoltre migliorano l'efficienza delle amministrazioni pubbliche, e mettono in grado le persone di affrontare meglio le decisioni che riguardano la loro vita potendo utilizzare informazioni che prima non erano disponibili. Il lavoro svolto nell'elaborato si colloca nel settore della mobilità urbana e nasce dalla decisione dell'azienda Tper di mettere a disposizione i propri dati in formato OpenData sul sito web http://www.tper.it/tper-open-data. L'obiettivo principale è la realizzazione di un'applicazione in grado di fornire informazioni in tempo reale sulle linee di autobus, e relative fermate, in una determinata area di interesse.

Generazione di ontologie da rappresentazioni grafiche

La produzione ontologica è un processo fondamentale per la crescita del Web Semantico in quanto le ontologie rappresentano i vocabolari formali con cui strutturare il Web of Data. Le notazioni grafiche ontologiche costituiscono il mezzo ideale per progettare ontologie OWL sensate e ben strutturate. Tuttavia la successiva fase di generazione ontologica richiede all'utente un fastidioso cambio sia di prospettiva sia di strumentazione. Questa tesi propone dunque GraMOS, Graffoo to Manchester OWL Syntax, un motore di trasformazione da modelli Graffoo a ontologie formali in grado di fondere le due fasi di progettazione e generazione ontologica.

Analisi di tecniche per l'estrazione di informazioni da documenti testuali e non strutturati

Obiettivo di questa tesi dal titolo “Analisi di tecniche per l’estrazione di informazioni da documenti testuali e non strutturati” è quello di mostrare tecniche e metodologie informatiche che permettano di ricavare informazioni e conoscenza da dati in formato testuale. Gli argomenti trattati includono l'analisi di software per l'estrazione di informazioni, il web semantico, l'importanza dei dati e in particolare i Big Data, Open Data e Linked Data. Si parlerà inoltre di data mining e text mining.

REST-based sensor networks with OData

RESTful services gained a lot of attention recently, even in the enterprise world, which is traditionally more web-service centric. Data centric RESfFul services, as previously mainly known in web environments, established themselves as a second paradigm complementing functional WSDL-based SOA. In the Internet of Things, and in particular when talking about sensor motes, the Constraint Application Protocol (CoAP) is currently in the focus of both research and industry. In the enterprise world a protocol called OData (Open Data Protocol) is becoming the future RESTful data access standard. To integrate sensor motes seamlessly into enterprise networks, an embedded OData implementation on top of CoAP is desirable, not requiring an intermediary gateway device. In this paper we introduce and evaluate an embedded OData implementation. We evaluate the OData protocol in terms of performance and energy consumption, considering different data encodings, and compare it to a pure CoAP implementation. We were able to demonstrate that the additional resources needed for an OData/JSON implementation are reasonable when aiming for enterprise interoperability, where OData is suggested to solve both the semantic and technical interoperability problems we have today when connecting systems

The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases

This chapter presents fuzzy cognitive maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. The corresponding Web KnowARR framework incorporates findings from fuzzy logic. To this end, a first emphasis is particularly on the Web KnowARR framework along with a stakeholder management use case to illustrate the framework’s usefulness as a second focal point. This management form is to help projects to acceptance and assertiveness where claims for company decisions are actively involved in the management process. Stakeholder maps visually (re-) present these claims. On one hand, they resort to non-public content and on the other they resort to content that is available to the public (mostly on the Web). The Semantic Web offers opportunities not only to present public content descriptively but also to show relationships. The proposed framework can serve as the basis for the public content of stakeholder maps.

Building ontologies from folksonomies and linked data: Data structures and Algorithms

We present the data structures and algorithms used in the approach for building domain ontologies from folksonomies and linked data. In this approach we extracts domain terms from folksonomies and enrich them with semantic information from the Linked Open Data cloud. As a result, we obtain a domain ontology that combines the emergent knowledge of social tagging systems with formal knowledge from Ontologies.

DBpedia spotlight: shedding light on the web of documents

Interlinking text documents with Linked Open Data enables the Web of Data to be used as background knowledge within document-oriented applications such as search and faceted browsing. As a step towards interconnecting the Web of Documents with the Web of Data, we developed DBpedia Spotlight, a system for automatically annotating text documents with DBpedia URIs. DBpedia Spotlight allows users to congure the annotations to their specic needs through the DBpedia Ontology and quality measures such as prominence, topical pertinence, contextual ambiguity and disambiguation condence. We compare our approach with the state of the art in disambiguation, and evaluate our results in light of three baselines and six publicly available annotation systems, demonstrating the competitiveness of our system. DBpedia Spotlight is shared as open source and deployed as a Web Service freely available for public use.

Using SCXML to integrate semantic sensor information into context-aware user interfaces

This paper describes a novel architecture to introduce automatic annotation and processing of semantic sensor data within context-aware applications. Based on the well-known state-charts technologies, and represented using W3C SCXML language combined with Semantic Web technologies, our architecture is able to provide enriched higher-level semantic representations of user’s context. This capability to detect and model relevant user situations allows a seamless modeling of the actual interaction situation, which can be integrated during the design of multimodal user interfaces (also based on SCXML) for them to be adequately adapted. Therefore, the final result of this contribution can be described as a flexible context-aware SCXML-based architecture, suitable for both designing a wide range of multimodal context-aware user interfaces, and implementing the automatic enrichment of sensor data, making it available to the entire Semantic Sensor Web

Translational research combining orthologous genes and human diseases with the OGOLOD dataset

OGOLOD is a Linked Open Data dataset derived from different biomedical resources by an automated pipeline, using a tailored ontology as a scaffold. The key contribution of OGOLOD is that it links, in new RDF triples, genetic human diseases and orthologous genes, paving the way for a more efficient translational biomedical research exploiting the Linked Open Data cloud.

SRBench: A streaming RDF/SPARQL benchmark

We introduce SRBench, a general-purpose benchmark primarily designed for streaming RDF/SPARQL engines, completely based on real-world data sets from the Linked Open Data cloud. With the increasing problem of too much streaming data but not enough tools to gain knowledge from them, researchers have set out for solutions in which Semantic Web technologies are adapted and extended for publishing, sharing, analysing and understanding streaming data. To help researchers and users comparing streaming RDF/SPARQL (strRS) engines in a standardised application scenario, we have designed SRBench, with which one can assess the abilities of a strRS engine to cope with a broad range of use cases typically encountered in real-world scenarios. The data sets used in the benchmark have been carefully chosen, such that they represent a realistic and relevant usage of streaming data. The benchmark defines a concise, yet omprehensive set of queries that cover the major aspects of strRS processing. Finally, our work is complemented with a functional evaluation on three representative strRS engines: SPARQLStream, C-SPARQL and CQELS. The presented results are meant to give a first baseline and illustrate the state-of-the-art.

Language resources and linked data: a practical perspective

Recently, experts and practitioners in language resources have started recognizing the benefits of the linked data (LD) paradigm for the representation and exploitation of linguistic data on the Web. The adoption of the LD principles is leading to an emerging ecosystem of multilingual open resources that conform to the Linguistic Linked Open Data Cloud, in which datasets of linguistic data are interconnected and represented following common vocabularies, which facilitates linguistic information discovery, integration and access. In order to contribute to this initiative, this paper summarizes several key aspects of the representation of linguistic information as linked data from a practical perspective. The main goal of this document is to provide the basic ideas and tools for migrating language resources (lexicons, corpora, etc.) as LD on the Web and to develop some useful NLP tasks with them (e.g., word sense disambiguation). Such material was the basis of a tutorial imparted at the EKAW’14 conference, which is also reported in the paper.

Social tags and linked data for ontology development: a case study in the financial domain

We describe a domain ontology development approach that extracts domain terms from folksonomies and enrich them with data and vocabularies from the Linked Open Data cloud. As a result, we obtain lightweight domain ontologies that combine the emergent knowledge of social tagging systems with formal knowledge from Ontologies. In order to illustrate the feasibility of our approach, we have produced an ontology in the financial domain from tags available in Delicious, using DBpedia, OpenCyc and UMBEL as additional knowledge sources.