One archive, many readings. Personal archives as complex networks in the semantic web

Personal archives are the archives created by individuals for their own purposes. Among these are the library and documentary collections of writers and scholars. It is only recently that archival literature has begun to focus on this category of archives, emphasising how their heterogeneous nature necessitates the conciliation of different approaches to archival description, and calling for a broader understanding of the principle of provenance, recognising that multiple creators, including subsequent researchers, can contribute to shaping personal archives over time by adding new layers of contexts. Despite these advances in the theoretical debate, current architectures for archival representation remain behind. Finding aids privilege a single point of view and do not allow subsequent users to embed their own, potentially conflicting, readings. Using semantic web technologies this study aims to define a conceptual model for writers' archives based on existing and widely adopted models in the cultural heritage and humanities domains. The model developed can be used to represent different types of documents at various levels of analysis, as well as record content and components. It also enables the representation of complex relationships and the incorporation of additional layers of interpretation into the finding aid, transforming it from a static search tool into a dynamic research platform.  The personal archive and library of Giuseppe Raimondi serves as a case study for the creation of an archival knowledge base using the proposed conceptual model. By querying the knowledge graph through SPARQL, the effectiveness of the model is evaluated. The results demonstrate that the model addresses the primary representation challenges identified in archival literature, from both a technological and methodological standpoint. The ultimate goal is to bring the output par excellence of archival science, i.e. the finding aid, more in line with the latest developments in archival thinking.

Wikis semàntiques : Què són? Com són? Com treballen? Quan calen?

En aquest treball s'analitza el funcionament de Semantic MediaWiki, que es basa en MediaWiki, una wiki tradicional mundialment coneguda per ser la base amb què es va desenvolupar Wikipedia. Abans s'identifiquen les principals tecnologies de la web semàntica i es defineix el propòsit de les wikis semàntiques.

Uso de wikis semánticas

En el presente PFC vamos a estudiar a fondo las wikis semánticas, para tratar de plasmar primeramente el estado del arte de éstas, su aprovechamiento y uso real, más allá de su concepción teórica o prototípica. Posteriormente utilizaremos una de ellas para realizar un ejercicio práctico, cargando una ontología nueva desarrollada para ésta y probando la potencia de las consultas sobre ésta.

Uso de wikis semánticas

En este trabajo se ha realizado una tarea de investigación con la finalidad de construir una ontología para cargarla en una wiki semántica y así analizar su funcionamiento.

Uso de wikis semánticas

Este es el producto obtenido del proyecto final de carrera sobre el uso de wikis semánticas en el que se describen lo que son ontologías, sus lenguajes, las wikis semánticas y un caso práctico.

Disseny d'ontologia i anàlisi comparatiu de bases de dades semàntiques

Introducció als conceptes bàsics de la web semàntica, disseny d'una ontologia original i anàlisi comparatiu de dos magatzems de dades semàntics: VirtuosoDB i OWLIM.

Ontologia del LinkedIn : Primer pas per inferir informació a partir de les ofertes de feina

El cas que ens ocupa és la xarxa social LinkedIn. La quantitat d'ofertes i demandes de feina fan a vegades difícil extreure'n la informació necessària. Es vol crear una ontologia per tal de nodrir les dades presents en la web LinkedIn amb informació semàntica. Mitjançant el programari Protégé es pretén crear aquesta ontologia i, mitjançant les API que ofereix LinkedIn, un mitjà per inferir informació respecte a les ofertes i demandes de feina.

TFC: Ontología turística geográfica

Este trabajo muestra una ontología de carácter turístico que relaciona puntos de interés turístico con documentos digitales en Internet. El proyecto también incluye un prototipo de buscador para mostrar el funcionamiento de la ontología

Bases de datos en el contexto de la web semántica

Comparativa sobre sistemas de gestión de bases de datos orientados a la web semántica, tanto nativos como habilitados para esta función.

Web semántica y servicios web semanticos

Des d'aquest TFC volem estudiar l'evolució de la Web actual cap a la Web Semàntica.

Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web

Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is sound

Dealing with Semantic Heterogeneity Issues on the Web

The Semantic Web is an extension of the traditional Web in which meaning of information is well defined, thus allowing a better interaction between people and computers. To accomplish its goals, mechanisms are required to make explicit the semantics of Web resources, to be automatically processed by software agents (this semantics being described by means of online ontologies). Nevertheless, issues arise caused by the semantic heterogeneity that naturally happens on the Web, namely redundancy and ambiguity. For tackling these issues, we present an approach to discover and represent, in a non-redundant way, the intended meaning of words in Web applications, while taking into account the (often unstructured) context in which they appear. To that end, we have developed novel ontology matching, clustering, and disambiguation techniques. Our work is intended to help bridge the gap between syntax and semantics for the Semantic Web construction

A Semantic Scraping Model for Web Resources - Applying Linked Data to Web Page Screen Scraping

In spite of the increasing presence of Semantic Web Facilities, only a limited amount of the available resources in the Internet provide a semantic access. Recent initiatives such as the emerging Linked Data Web are providing semantic access to available data by porting existing resources to the semantic web using different technologies, such as database-semantic mapping and scraping. Nevertheless, existing scraping solutions are based on ad-hoc solutions complemented with graphical interfaces for speeding up the scraper development. This article proposes a generic framework for web scraping based on semantic technologies. This framework is structured in three levels: scraping services, semantic scraping model and syntactic scraping. The first level provides an interface to generic applications or intelligent agents for gathering information from the web at a high level. The second level defines a semantic RDF model of the scraping process, in order to provide a declarative approach to the scraping task. Finally, the third level provides an implementation of the RDF scraping model for specific technologies. The work has been validated in a scenario that illustrates its application to mashup technologies

Semantic Heterogeneity Issues on the Web

The Semantic Web is an extension of the traditional Web in which meaning of information is well defined, thus allowing a better interaction between people and computers. To accomplish its goals, mechanisms are required to make explicit the semantics of Web resources, to be automatically processed by software agents (this semantics being described by means of online ontologies). Nevertheless, issues arise caused by the semantic heterogeneity that naturally happens on the Web, namely redundancy and ambiguity. For tackling these issues, we present an approach to discover and represent, in a non-redundant way, the intended meaning of words in Web applications, while taking into account the (often unstructured) context in which they appear. To that end, we have developed novel ontology matching, clustering, and disambiguation techniques. Our work is intended to help bridge the gap between syntax and semantics for the Semantic Web construction.

A core ontological model for semantic sensor web infrastructures

Semantic Sensor Web infrastructures use ontology-based models to represent the data that they manage; however, up to now, these ontological models do not allow representing all the characteristics of distributed, heterogeneous, and web-accessible sensor data. This paper describes a core ontological model for Semantic Sensor Web infrastructures that covers these characteristics and that has been built with a focus on reusability. This ontological model is composed of different modules that deal, on the one hand, with infrastructure data and, on the other hand, with data from a specific domain, that is, the coastal flood emergency planning domain. The paper also presents a set of guidelines, followed during the ontological model development, to satisfy a common set of requirements related to modelling domain-specific features of interest and properties. In addition, the paper includes the results obtained after an exhaustive evaluation of the developed ontologies along different aspects (i.e., vocabulary, syntax, structure, semantics, representation, and context).