Social and Semantic Contexts in Tourist Mobile Applications

The ongoing growth of the World Wide Web along with the increase possibility of access information through a variety of devices in mobility, has defi nitely changed the way users acquire, create, and personalize information, pushing innovative strategies for annotating and organizing it. In this scenario, Social Annotation Systems have quickly gained a huge popularity, introducing millions of metadata on di fferent Web resources following a bottom-up approach, generating free and democratic mechanisms of classi cation, namely folksonomies. Moving away from hierarchical classi cation schemas, folksonomies represent also a meaningful mean for identifying similarities among users, resources and tags. At any rate, they suff er from several limitations, such as the lack of specialized tools devoted to manage, modify, customize and visualize them as well as the lack of an explicit semantic, making di fficult for users to bene fit from them eff ectively. Despite appealing promises of Semantic Web technologies, which were intended to explicitly formalize the knowledge within a particular domain in a top-down manner, in order to perform intelligent integration and reasoning on it, they are still far from reach their objectives, due to di fficulties in knowledge acquisition and annotation bottleneck. The main contribution of this dissertation consists in modeling a novel conceptual framework that exploits both social and semantic contextual dimensions, focusing on the domain of tourism and cultural heritage. The primary aim of our assessment is to evaluate the overall user satisfaction and the perceived quality in use thanks to two concrete case studies. Firstly, we concentrate our attention on contextual information and navigation, and on authoring tool; secondly, we provide a semantic mapping of tags of the system folksonomy, contrasted and compared to the expert users' classi cation, allowing a bridge between social and semantic knowledge according to its constantly mutual growth. The performed user evaluations analyses results are promising, reporting a high level of agreement on the perceived quality in use of both the applications and of the speci c analyzed features, demonstrating that a social-semantic contextual model improves the general users' satisfactio

Visual approaches to knowledge organization and contextual exploration

This thesis explores possible visual approaches for the representation of semantic structures, such as zz-structures. Some holistic visual representations of complex domains have been investigated through the proposal of new views - the so-called zz-views - that allow both to make visible the interconnections between elements and to support a contextual and multilevel exploration of knowledge. The potential of this approach has been examined in the context of two case studies that have led to the creation of two Web applications. The \ufb01rst domain of study regarded the visual representation, analysis and management of scienti\ufb01c bibliographies. In this context, we modeled a Web application, we called VisualBib, to support researchers in building, re\ufb01ning, analyzing and sharing bibliographies. We adopted a multi-faceted approach integrating features that are typical of three di\ufb00erent classes of tools: bibliography visual analysis systems, bibliographic citation indexes and personal research assistants. The evaluation studies carried out on a \ufb01rst prototype highlighted the positive impact of our visual model and encouraged us to improve it and develop further visual analysis features we incorporated in the version 3.0 of the application. The second case study concerned the modeling and development of a multimedia catalog of Web and mobile applications. The objective was to provide an overview of a significant number of tools that can help teachers in the implementation of active learning approaches supported by technology and in the design of Teaching and Learning Activities (TLAs). We analyzed and documented 281 applications, preparing for each of them a detailed multilingual card and a video-presentation, organizing all the material in an original purpose-based taxonomy, visually represented through a browsable holistic view. The catalog, we called AppInventory, provides contextual exploration mechanisms based on zz-structures, collects user contributions and evaluations about the apps and o\ufb00ers visual analysis tools for the comparison of the applications data and user evaluations. The results of two user studies carried out on groups of teachers and students shown a very positive impact of our proposal in term of graphical layout, semantic structure, navigation mechanisms and usability, also in comparison with two similar catalogs

A Graph-Based Web Services Discovery Framework for IoT EcoSystem

Nowadays, the Internet of Things (IoT) represents an important topic and research domain with multiple objectives. However, most IoTs communicate poorly across the multitude of network interfaces. It should be preferably used a single universal application layer protocol for the devices and services interconnection, regardless of how they are physically connected. The IoT paradigm boosts the device connectivity and the user accessibility benefits of services introduced within the network of connected objects associated with a context-awareness. Within this frame of reference, Web service is the appropriate technological approach to exhibit a set of related IoT functionalities loosely coupled with other services discovered or composed through the Web. In this work, we consider the heterogeneity of connecting technologies for IoT and the applications and devices integration in a single interoperable framework as a research objective. With this in mind, we introduce a five layers multigraph model for Web Services discovery and recommendation, and we address Web services-based applications for IoT data integration. The launched service discovery process permits the interaction between the user/application and the IoT environment. In this context, the choice of suitable services represents a challenge that covers the functionality and the required quality to combine composite services, namely mashups for IoT data management and interconnection. For proof of concept, we test a RESTful Web Services framework as an experimental platform to animate a graph-based approach for dynamic IoT services discovery. We develop a recommender system that performs graph analytics to produce a set of services according to the user's request. The quality of the recommendation process is evaluated by analyzing the correlation of user satisfaction

AppInventory: a Visual Catalogue of Web 2.0 and Mobile Applications for Supporting Teaching and Learning Activities.

The availability of hundreds of Web 2.0 and mobile applications represent a great opportunity in helping teachers adopt student centred methodologies. These applications support users in creating and sharing digital artefacts, in aggregating, remixing and collecting heterogeneous materials and in communicating within working groups. When incorporated into daily teaching and learning activities (TLA), such applications can improve the collaborative, cognitive and creative work of the students, enhancing and redefining traditional educational practices. Nevertheless, although these applications are generally easy to find and use, there is a lack of knowledge about their existence, their functions and their potential in an educational setting. In this paper we describe AppInventory, a novel platform which contains a digital catalogue of applications: they are organized by applying an original taxonomy; the users can browse among them benefiting from a visual approach and semantic connections modelled using zz-structures

Visual exploration of semantic-web-based knowledge structures

Humans have a curious nature and seek a better understanding of the world. Data, in- formation, and knowledge became assets of our modern society through the information technology revolution in the form of the internet. However, with the growing size of accumulated data, new challenges emerge, such as searching and navigating in these large collections of data, information, and knowledge. The current developments in academic and industrial contexts target the corresponding challenges using Semantic Web techno- logies. The Semantic Web is an extension of the Web and provides machine-readable representations of knowledge for various domains. These machine-readable representations allow intelligent machine agents to understand the meaning of the data and information; and enable additional inference of new knowledge. Generally, the Semantic Web is designed for information exchange and its processing and does not focus on presenting such semantically enriched data to humans. Visualizations support exploration, navigation, and understanding of data by exploiting humans’ ability to comprehend complex data through visual representations. In the context of Semantic- Web-Based knowledge structures, various visualization methods and tools are available, and new ones are being developed every year. However, suitable visualizations are highly dependent on individual use cases and targeted user groups. In this thesis, we investigate visual exploration techniques for Semantic-Web-Based knowledge structures by addressing the following challenges: i) how to engage various user groups in modeling such semantic representations; ii) how to facilitate understanding using customizable visual representations; and iii) how to ease the creation of visualizations for various data sources and different use cases. The achieved results indicate that visual modeling techniques facilitate the engagement of various user groups in ontology modeling. Customizable visualizations enable users to adjust visualizations to the current needs and provide different views on the data. Additionally, customizable visualization pipelines enable rapid visualization generation for various use cases, data sources, and user group

APPLICATIONS OF GRAPH THEORY FOR REUSE OF MODEL BASED SYSTEMS ENGINEERING DESIGN DATA

This dissertation contributes to systems engineering (SE) by introducing and demonstrating a novel graph-based design repository (GBDR) tool. GBDR enables engineers to leverage system design information from a heterogenous set of system models created using multiple model based systems engineering (MBSE) software tools as an integrated body of knowledge. Specifically, the research provides a set of approaches that allow the use of system models described in Systems Modeling Language and Lifecycle Modeling Language as an integrated body of design information. The coalesced body of system design information serves to support concept ideation and analysis within SE. The research accomplishes this by using a graph database to store system model information imported from digital artifacts created by MBSE tools and applying principles from graph theory and semantic web technologies to identify likely connections and equivalent concepts across system models, modeling languages, and metamodels. The research demonstrates that the presented tool can import, store, synthesize, search, display, distribute, and export information from multiple MBSE tools. As a practical demonstration, feasible subsystem design alternatives for a small unmanned aircraft system government reference architecture are identified from within a set of existing system models.OSD CAPECivilian, Office of the Secretary of DefenseApproved for public release. Distribution is unlimited

SylvaDB: A Polyglot and Multi-backend Graph Database Management System

This paper presents SylvaDB, a graph database management system designed to be used by people with no technical knowledge. SylvaDB is based on flexible schema definitions and has been developed taking into account the need to deal with semantic information. It relies on the mathematical notion of property graph. SylvaDB is an open source project and aims at lowering the barrier of adoption for anyone using graph databases. At the same time, it is robust and scalable enough to support collaborative large projects related to knowledge management, document archiving, and research