Supporto a editor Web-Based in Ambiente Service-Oriented: modellazione dell'Ambiente Dati

Nell'ambito delle Service-Oriented Architecture, il linguaggio JOLIE, assieme al suo editor jEye, consentono la realizzazione di orchestratori. Questa tesi realizza (modello e implementazione) il supporto per l'Ambiente Dati

Supporting semantic web technologies in the pervasive service ecosystems middleware

Semantic Web technologies are strategic in order to fulfill the openness requirement of Self-Aware Pervasive Service Ecosystems. In fact they provide agents with the ability to cope with distributed data, using RDF to represent information, ontologies to describe relations between concepts from any domain (e.g. equivalence, specialization/extension, and so on) and reasoners to extract implicit knowledge. The aim of this thesis is to study these technologies and design an extension of a pervasive service ecosystems middleware capable of exploiting semantic power, and deepening performance implications.

A fuzzy grassroots ontology for improving social semantic web search

The web is continuously evolving into a collection of many data, which results in the interest to collect and merge these data in a meaningful way. Based on that web data, this paper describes the building of an ontology resting on fuzzy clustering techniques. Through continual harvesting folksonomies by web agents, an entire automatic fuzzy grassroots ontology is built. This self-updating ontology can then be used for several practical applications in fields such as web structuring, web searching and web knowledge visualization.A potential application for online reputation analysis, added value and possible future studies are discussed in the conclusion.

Ontology driven integration platform for clinical and translational research

Semantic Web technologies offer a promising framework for integration of disparate biomedical data. In this paper we present the semantic information integration platform under development at the Center for Clinical and Translational Sciences (CCTS) at the University of Texas Health Science Center at Houston (UTHSC-H) as part of our Clinical and Translational Science Award (CTSA) program. We utilize the Semantic Web technologies not only for integrating, repurposing and classification of multi-source clinical data, but also to construct a distributed environment for information sharing, and collaboration online. Service Oriented Architecture (SOA) is used to modularize and distribute reusable services in a dynamic and distributed environment. Components of the semantic solution and its overall architecture are described.

Cross-lingual ontology matching as a challenge for the Multilingual Semantic Web

Recently, the Semantic Web has experienced significant advancements in standards and techniques, as well as in the amount of semantic information available online. Nevertheless, mechanisms are still needed to automatically reconcile information when it is expressed in different natural languages on the Web of Data, in order to improve the access to semantic information across language barriers. In this context several challenges arise [1], such as: (i) ontology translation/localization, (ii) cross-lingual ontology mappings, (iii) representation of multilingual lexical information, and (iv) cross-lingual access and querying of linked data. In the following we will focus on the second challenge, which is the necessity of establishing, representing and storing cross-lingual links among semantic information on the Web. In fact, in a “truly” multilingual Semantic Web, semantic data with lexical representations in one natural language would be mapped to equivalent or related information in other languages, thus making navigation across multilingual information possible for software agents.

Did you validate your ontology? OOPS!

The application of methodologies for building ontologies can im-prove ontology quality. However, such quality is not guaranteed because of the difficulties involved in ontology modelling. These difficulties are related to the inclusion of anomalies or bad practices within the ontology development. Sev-eral authors have provided lists of typical anomalies detected in ontologies dur-ing the last decade. In this context, our aim in this paper is to describe OOPS! (OntOlogy Pitfall Scanner!), a tool for detecting pitfalls in ontologies.

A Metadirectory of Web Components for Mashup Composition

Because of the growing availability of third-party APIs, services, widgets and any other reusable web component, mashup developers now face a vast amount of candidate components for their developments. Moreover, these components quite often are scattered in many different repositories and web sites, which makes difficult their selection or discovery. In this paper, we discuss the problem of component selection in Service-Oriented Architectures (SOA) and Mashup-Driven Development, and introduce the Linked Mashups Ontology (LiMOn), a model that allows describing mashups and their components for integrating and sharing mashup information such as categorization or dependencies. The model has allowed the building of an integrated, centralized metadirectory of web components for query and selection, which has served to evaluate the model. The metadirectory allows accessing various heterogeneous repositories of mashups and web components while using external information from the Linked Data cloud, helping mashup development.

Antipattern detection in web ontologies: an experiment using SPARQL queries

Ontology antipatterns are structures that reflect ontology modelling problems because they lead to inconsistencies, bad reasoning performance or bad formalisation of domain knowledge. We propose four methods for the detection of antipatterns using SPARQL queries.We conduct some experiments to detect antipattern in a corpus of OWL ontologies.

Detecting Good Practices and Pitfalls when Publishing Vocabularies on the Web

The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies bringing their semantic to the data being published. These ontologies should be evaluated at different stages, both during their development and their publication. As important as correctly modelling the intended part of the world to be captured in an ontology, is publishing, sharing and facilitating the (re)use of the obtained model. In this paper, 11 evaluation characteristics, with respect to publish, share and facilitate the reuse, are proposed. In particular, 6 good practices and 5 pitfalls are presented, together with their associated detection methods. In addition, a grid-based rating system is generated. Both contributions, the set of evaluation characteristics and the grid system, could be useful for ontologists in order to reuse existing LD vocabularies or to check the one being built.

Creating and modelling personal socio-economic networks in on-line banking

The banking industry is observing how new competitors threaten its millennial business model by targeting unbanked people, offering new financial services to their customer base, and even enabling new channels for existing services and customers. The knowledge on users, their behaviour, and expectations become a key asset in this new context. Well aware of this situation, the Center for Open Middleware, a joint technology center created by Santander Bank and Universidad Politécnica de Madrid, has launched a set of initiatives to allow the experimental analysis and management of socio-economic information. PosdataP2P service is one of them, which seeks to model the economic ties between the holders of university smart cards, leveraging on the social networks the holders are subscribed to. In this paper we describe the design principles guiding the development of the system, its architecture and some implementation details.

OOPS! (OntOlogy Pitfall Scanner!): a web-based tool for ontology evaluation

Presentación en Workshop EUON 2014

Modelado y Comparación de Colecciones en la Web Semántica

En esta tesis se estudia la representación, modelado y comparación de colecciones mediante el uso de ontologías en el ámbito de la Web Semántica. Las colecciones, entendidas como agrupaciones de objetos o elementos con entidad propia, son construcciones que aparecen frecuentemente en prácticamente todos los dominios del mundo real, y por tanto, es imprescindible disponer de conceptualizaciones de estas estructuras abstractas y de representaciones de estas conceptualizaciones en los sistemas informáticos, que definan adecuadamente su semántica. Mientras que en muchos ámbitos de la Informática y la Inteligencia Artificial, como por ejemplo la programación, las bases de datos o la recuperación de información, las colecciones han sido ampliamente estudiadas y se han desarrollado representaciones que responden a multitud de conceptualizaciones, en el ámbito de la Web Semántica, sin embargo, su estudio ha sido bastante limitado. De hecho hasta la fecha existen pocas propuestas de representación de colecciones mediante ontologías, y las que hay sólo cubren algunos tipos de colecciones y presentan importantes limitaciones. Esto impide la representación adecuada de colecciones y dificulta otras tareas comunes como la comparación de colecciones, algo crítico en operaciones habituales como las búsquedas semánticas o el enlazado de datos en la Web Semántica. Para solventar este problema esta tesis hace una propuesta de modelización de colecciones basada en una nueva clasificación de colecciones de acuerdo a sus características estructurales (homogeneidad, unicidad, orden y cardinalidad). Esta clasificación permite definir una taxonomía con hasta 16 tipos de colecciones distintas. Entre otras ventajas, esta nueva clasificación permite aprovechar la semántica de las propiedades estructurales de cada tipo de colección para realizar comparaciones utilizando las funciones de similitud y disimilitud más apropiadas. De este modo, la tesis desarrolla además un nuevo catálogo de funciones de similitud para las distintas colecciones, donde se han recogido las funciones de (di)similitud más conocidas y también algunas nuevas. Esta propuesta se ha implementado mediante dos ontologías paralelas, la ontología E-Collections, que representa los distintos tipos de colecciones de la taxonomía y su axiomática, y la ontología SIMEON (Similarity Measures Ontology) que representa los tipos de funciones de (di)similitud para cada tipo de colección. Gracias a estas ontologías, para comparar dos colecciones, una vez representadas como instancias de la clase más apropiada de la ontología E-Collections, automáticamente se sabe qué funciones de (di)similitud de la ontología SIMEON pueden utilizarse para su comparación. Abstract This thesis studies the representation, modeling and comparison of collections in the Semantic Web using ontologies. Collections, understood as groups of objects or elements with their own identities, are constructions that appear frequently in almost all areas of the real world. Therefore, it is essential to have conceptualizations of these abstract structures and representations of these conceptualizations in computer systems, that define their semantic properly. While in many areas of Computer Science and Artificial Intelligence, such as Programming, Databases or Information Retrieval, the collections have been extensively studied and there are representations that match many conceptualizations, in the field Semantic Web, however, their study has been quite limited. In fact, there are few representations of collections using ontologies so far, and they only cover some types of collections and have important limitations. This hinders a proper representation of collections and other common tasks like comparing collections, something critical in usual operations such as semantic search or linking data on the Semantic Web. To solve this problem this thesis makes a proposal for modelling collections based on a new classification of collections according to their structural characteristics (homogeneity, uniqueness, order and cardinality). This classification allows to define a taxonomy with up to 16 different types of collections. Among other advantages, this new classification can leverage the semantics of the structural properties of each type of collection to make comparisons using the most appropriate (dis)similarity functions. Thus, the thesis also develops a new catalog of similarity functions for the different types of collections. This catalog contains the most common (dis)similarity functions as well as new ones. This proposal is implemented through two parallel ontologies, the E-Collections ontology that represents the different types of collections in the taxonomy and their axiomatic, and the SIMEON ontology (Similarity Measures Ontology) that represents the types of (dis)similarity functions for each type of collection. Thanks to these ontologies, to compare two collections, once represented as instances of the appropriate class of E-Collections ontology, we can know automatically which (dis)similarity functions of the SIMEON ontology are suitable for the comparison. Finally, the feasibility and usefulness of this modeling and comparison of collections proposal is proved in the field of oenology, applying both E-Collections and SIMEON ontologies to the representation and comparison of wines with the E-Baco ontology.

A Personal Agent Architecture for Task Automation in the Web of Data. Bringing intelligence to everyday tasks

Internet está evolucionando hacia la conocida como Live Web. En esta nueva etapa en la evolución de Internet, se pone al servicio de los usuarios multitud de streams de datos sociales. Gracias a estas fuentes de datos, los usuarios han pasado de navegar por páginas web estáticas a interacturar con aplicaciones que ofrecen contenido personalizado, basada en sus preferencias. Cada usuario interactúa a diario con multiples aplicaciones que ofrecen notificaciones y alertas, en este sentido cada usuario es una fuente de eventos, y a menudo los usuarios se sienten desbordados y no son capaces de procesar toda esa información a la carta. Para lidiar con esta sobresaturación, han aparecido múltiples herramientas que automatizan las tareas más habituales, desde gestores de bandeja de entrada, gestores de alertas en redes sociales, a complejos CRMs o smart-home hubs. La contrapartida es que aunque ofrecen una solución a problemas comunes, no pueden adaptarse a las necesidades de cada usuario ofreciendo una solucion personalizada. Los Servicios de Automatización de Tareas (TAS de sus siglas en inglés) entraron en escena a partir de 2012 para dar solución a esta liminación. Dada su semejanza, estos servicios también son considerados como un nuevo enfoque en la tecnología de mash-ups pero centra en el usuarios. Los usuarios de estas plataformas tienen la capacidad de interconectar servicios, sensores y otros aparatos con connexión a internet diseñando las automatizaciones que se ajustan a sus necesidades. La propuesta ha sido ámpliamante aceptada por los usuarios. Este hecho ha propiciado multitud de plataformas que ofrecen servicios TAS entren en escena. Al ser un nuevo campo de investigación, esta tesis presenta las principales características de los TAS, describe sus componentes, e identifica las dimensiones fundamentales que los defines y permiten su clasificación. En este trabajo se acuña el termino Servicio de Automatización de Tareas (TAS) dando una descripción formal para estos servicios y sus componentes (llamados canales), y proporciona una arquitectura de referencia. De igual forma, existe una falta de herramientas para describir servicios de automatización, y las reglas de automatización. A este respecto, esta tesis propone un modelo común que se concreta en la ontología EWE (Evented WEb Ontology). Este modelo permite com parar y equiparar canales y automatizaciones de distintos TASs, constituyendo un aporte considerable paraa la portabilidad de automatizaciones de usuarios entre plataformas. De igual manera, dado el carácter semántico del modelo, permite incluir en las automatizaciones elementos de fuentes externas sobre los que razonar, como es el caso de Linked Open Data. Utilizando este modelo, se ha generado un dataset de canales y automatizaciones, con los datos obtenidos de algunos de los TAS existentes en el mercado. Como último paso hacia el lograr un modelo común para describir TAS, se ha desarrollado un algoritmo para aprender ontologías de forma automática a partir de los datos del dataset. De esta forma, se favorece el descubrimiento de nuevos canales, y se reduce el coste de mantenimiento del modelo, el cual se actualiza de forma semi-automática. En conclusión, las principales contribuciones de esta tesis son: i) describir el estado del arte en automatización de tareas y acuñar el término Servicio de Automatización de Tareas, ii) desarrollar una ontología para el modelado de los componentes de TASs y automatizaciones, iii) poblar un dataset de datos de canales y automatizaciones, usado para desarrollar un algoritmo de aprendizaje automatico de ontologías, y iv) diseñar una arquitectura de agentes para la asistencia a usuarios en la creación de automatizaciones. ABSTRACT The new stage in the evolution of the Web (the Live Web or Evented Web) puts lots of social data-streams at the service of users, who no longer browse static web pages but interact with applications that present them contextual and relevant experiences. Given that each user is a potential source of events, a typical user often gets overwhelmed. To deal with that huge amount of data, multiple automation tools have emerged, covering from simple social media managers or notification aggregators to complex CRMs or smart-home Hub/Apps. As a downside, they cannot tailor to the needs of every single user. As a natural response to this downside, Task Automation Services broke in the Internet. They may be seen as a new model of mash-up technology for combining social streams, services and connected devices from an end-user perspective: end-users are empowered to connect those stream however they want, designing the automations they need. The numbers of those platforms that appeared early on shot up, and as a consequence the amount of platforms following this approach is growing fast. Being a novel field, this thesis aims to shed light on it, presenting and exemplifying the main characteristics of Task Automation Services, describing their components, and identifying several dimensions to classify them. This thesis coins the term Task Automation Services (TAS) by providing a formal definition of them, their components (called channels), as well a TAS reference architecture. There is also a lack of tools for describing automation services and automations rules. In this regard, this thesis proposes a theoretical common model of TAS and formalizes it as the EWE ontology This model enables to compare channels and automations from different TASs, which has a high impact in interoperability; and enhances automations providing a mechanism to reason over external sources such as Linked Open Data. Based on this model, a dataset of components of TAS was built, harvesting data from the web sites of actual TASs. Going a step further towards this common model, an algorithm for categorizing them was designed, enabling their discovery across different TAS. Thus, the main contributions of the thesis are: i) surveying the state of the art on task automation and coining the term Task Automation Service; ii) providing a semantic common model for describing TAS components and automations; iii) populating a categorized dataset of TAS components, used to learn ontologies of particular domains from the TAS perspective; and iv) designing an agent architecture for assisting users in setting up automations, that is aware of their context and acts in consequence.