L'ingénierie des documents d'affaires dans le cadre du web sémantique

Dans cette thèse, nous présentons les problèmes d’échange de documents d'affaires et proposons une méthode pour y remédier. Nous proposons une méthodologie pour adapter les standards d’affaires basés sur XML aux technologies du Web sémantique en utilisant la transformation des documents définis en DTD ou XML Schema vers une représentation ontologique en OWL 2. Ensuite, nous proposons une approche basée sur l'analyse formelle de concept pour regrouper les classes de l'ontologie partageant une certaine sémantique dans le but d'améliorer la qualité, la lisibilité et la représentation de l'ontologie. Enfin, nous proposons l’alignement d'ontologies pour déterminer les liens sémantiques entre les ontologies d'affaires hétérogènes générés par le processus de transformation pour aider les entreprises à communiquer fructueusement.

Um ambiente para especificação e execução AD-HOC de processos de negócio baseados em serviços Web

Recently the focus given to Web Services and Semantic Web technologies has provided the development of several research projects in different ways to addressing the Web services composition issue. Meanwhile, the challenge of creating an environment that provides the specification of an abstract business process and that it is automatically implemented by a composite service in a dynamic way is considered a currently open problem. WSDL and BPEL provided by industry support only manual service composition because they lack needed semantics so that Web services are discovered, selected and combined by software agents. Services ontology provided by Semantic Web enriches the syntactic descriptions of Web services to facilitate the automation of tasks, such as discovery and composition. This work presents an environment for specifying and ad-hoc executing Web services-based business processes, named WebFlowAH. The WebFlowAH employs common domain ontology to describe both Web services and business processes. It allows processes specification in terms of users goals or desires that are expressed based on the concepts of such common domain ontology. This approach allows processes to be specified in an abstract high level way, unburdening the user from the underline details needed to effectively run the process workflow

As tecnologias da Web Semântica no domínio bibliográfico

Pós-graduação em Ciência da Informação - FFC

Wikis semânticos: da Web para a Web Semântica

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

Websislapam: sistema de avaliações de pessoas baseado em tecnologias WEB

This work, entitled Websislapam: People Rating System Based on Web Technologies, allows the creation of questionnaires, and the organization of entities and people who participate in evaluations. Entities collect data from people with the help of resources that reduce typing mistakes. The Websislapam maintains a database and provides graphical reporting, which enable the analysis of those tested. Developed using Web technologies such as PHP, Javascript, CSS, and others. Developed with the paradigm of object-oriented programming and the MySQL DBMS. For the theoretical basis, research in the areas of System Database, Web Technologies and Web Engineering were performed. It was determined the evaluation process, systems and Web-based applications, Web and System Engineering Database. Technologies applied in the implementation of Websislapam been described. In a separate chapter presented the main features and artifacts used in the development of Websislapam. A case study demonstrates the practical use of the system

MWRegEx : monitor web de expresiones regulares

[ES] El Trabajo de Fin de Grado, Monitor Web de Expresiones Regulares (MWRegEx), es una herramienta basada en tecnologías web, desarrollada usando el entorno Visual Studio. El objetivo principal de la aplicación es dar apoyo a la docencia de expresiones regulares, en el marco de la enseñanza del manejo de ristras de caracteres en las asignaturas de programación del Grado en Ingeniería Informática.  La aplicación permite obtener el dibujo de un autómata de una expresión regular, facilitando su comprensión; además, permite aplicar la expresión a diferentes ristras de caracteres, mostrando las coincidencias encontradas, y ofrece una versión de la expresión adaptada a su uso en literales string de lenguajes como Java y otros. La herramienta se ha implementado en dos partes: un servicio web, escrito en C#, donde se realizan todos los análisis de las expresiones regulares y las ristras a contrastar; y un cliente web, implementado usando tecnología asp.net, con JavaScript y JQuery, que gestiona la interfaz de usuario y muestra los resultados. Esta separación permite que el servicio web pueda ser reutilizado con otras aplicaciones cliente. El autómata que representa una expresión regular esta dibujado usando la librería Raphaël JavaScript que permite manejar los elementos SVG. Cada elemento de la expresión regular tiene un dibujo diferente y único para así diferenciarlo. Toda la interfaz gráfica de usuario está internacionalizada de manera tal que pueda adaptarse a diferentes idiomas y regiones sin la necesidad de realizar cambios de ingeniería ni en el código. Tanto el servicio web como la parte cliente están estructurados para que se puedan agregar nuevas modificaciones sin que esto genere una onda expansiva a lo largo de las diversas clases existentes.

Aplicación Web para Ayuntamiento de Las Palmas de Gran Canaria : [Parte B]

[ES] Este Trabajo de Fin de Grado es un servicio basado en tecnologías web. El objetivo principal es ofrecer un servicio de creación y gestión de actas para el Ayuntamiento de Las Palmas de Gran Canaria. Para ello, consta de dos módulos principales, uno para “crear actas” y otro para “editar actas”. También se ha desarrollado otro módulo llamado plantillas donde se genera un PDF a partir de una plantilla preestablecida. Esta aplicación ha sido dividida en diferentes partes. La primera parte consistió en generar todas las configuraciones de base de datos necesarias para el funcionamiento de la aplicación. Después generamos todos los ficheros HTML y las interconexiones entre ellos. Finalmente, dotamos  a esos HTML estáticos de un estilo mucho más claro y organizado, dando a la aplicación una apariencia mucho más bonita. Una vez finalizada la parte frontal de la aplicación, empezamos a implementar la lógica detrás de la aplicación. Los módulos de “crear” y “editar” se hicieron utilizando formularios HTML y combinando la información obtenida de esos formularios con unas plantillas HTML generadas por nosotros. Toda esa información obtenida de los formularios se guarda en unos ficheros .txt para poder ser utilizados por el módulo editar. El módulo de plantillas nos muestra un editor HTML rellenado con una plantilla que ha sido previamente seleccionada por el usuario. Los ficheros pdf de este módulo no pueden editados con posterioridad  por lo que no se generan ficheros .txt. Por último, hay dos módulos que nos permiten ver todas las actas generadas por la aplicación. El primero de los dos módulos es el módulo de búsqueda, que nos permite buscar una palabra clave dentro de todos los ficheros pdf. El otro módulo nos muestra todas las actas que han sido marcadas como “cerradas”. Esta aplicación ha sido diseñada de forma modular, de manera que podemos añadir o quitar módulos de manera sencilla.

Semantic Publishing: issues, solutions and new trends in scholarly publishing within the Semantic Web era

This work is concerned with the increasing relationships between two distinct multidisciplinary research fields, Semantic Web technologies and scholarly publishing, that in this context converge into one precise research topic: Semantic Publishing. In the spirit of the original aim of Semantic Publishing, i.e. the improvement of scientific communication by means of semantic technologies, this thesis proposes theories, formalisms and applications for opening up semantic publishing to an effective interaction between scholarly documents (e.g., journal articles) and their related semantic and formal descriptions. In fact, the main aim of this work is to increase the users' comprehension of documents and to allow document enrichment, discovery and linkage to document-related resources and contexts, such as other articles and raw scientific data. In order to achieve these goals, this thesis investigates and proposes solutions for three of the main issues that semantic publishing promises to address, namely: the need of tools for linking document text to a formal representation of its meaning, the lack of complete metadata schemas for describing documents according to the publishing vocabulary, and absence of effective user interfaces for easily acting on semantic publishing models and theories.

Autorenwerkzeuge für digitale, multimediale und interaktive Lernbausteine im Web 2.0

Die Forschungsarbeit siedelt sich im Dreieck der Erziehungswissenschaften, der Informatik und der Schulpraxis an und besitzt somit einen starken interdisziplinären Charakter. Aus Sicht der Erziehungswissenschaften handelt es sich um ein Forschungsprojekt aus den Bereichen E-Learning und Multimedia Learning und der Fragestellung nach geeigneten Informatiksystemen für die Herstellung und den Austausch von digitalen, multimedialen und interaktiven Lernbausteinen. Dazu wurden zunächst methodisch-didaktische Vorteile digitaler Lerninhalte gegenüber klassischen Medien wie Buch und Papier zusammengetragen und mögliche Potentiale im Zusammenhang mit neuen Web2.0-Technologien aufgezeigt. Darauf aufbauend wurde für existierende Autorenwerkzeuge zur Herstellung digitaler Lernbausteine und bestehende Austauschplattformen analysiert, inwieweit diese bereits Web 2.0-Technologien unterstützen und nutzen. Aus Sicht der Informatik ergab sich aus der Analyse bestehender Systeme ein Anforderungsprofil für ein neues Autorenwerkzeug und eine neue Austauschplattform für digitale Lernbausteine. Das neue System wurde nach dem Ansatz des Design Science Research in einem iterativen Entwicklungsprozess in Form der Webapplikation LearningApps.org realisiert und stetig mit Lehrpersonen aus der Schulpraxis evaluiert. Bei der Entwicklung kamen aktuelle Web-Technologien zur Anwendung. Das Ergebnis der Forschungsarbeit ist ein produktives Informatiksystem, welches bereits von tausenden Nutzern in verschiedenen Ländern sowohl in Schulen als auch in der Wirtschaft eingesetzt wird. In einer empirischen Studie konnte das mit der Systementwicklung angestrebte Ziel, die Herstellung und den Austausch von digitalen Lernbausteinen zu vereinfachen, bestätigt werden. Aus Sicht der Schulpraxis liefert LearningApps.org einen Beitrag zur Methodenvielfalt und zur Nutzung von ICT im Unterricht. Die Ausrichtung des Werkzeugs auf mobile Endgeräte und 1:1-Computing entspricht dem allgemeinen Trend im Bildungswesen. Durch die Verknüpfung des Werkzeugs mit aktuellen Software Entwicklungen zur Herstellung von digitalen Schulbüchern werden auch Lehrmittelverlage als Zielgruppe angesprochen.

Autorenwerkzeuge für digitale, multimediale und interaktive Lernbausteine im Web 2.0

Die vorliegende Forschungsarbeit siedelt sich im Dreieck der Erziehungswissenschaften, der Informatik und der Schulpraxis an und besitzt somit einen starken interdisziplinären Charakter. Aus Sicht der Erziehungswissenschaften handelt es sich um ein Forschungsprojekt aus den Bereichen E-Learning und Multimedia Learning und der Fragestellung nach geeigneten Informatiksystemen für die Herstellung und den Austausch von digitalen, multimedialen und interaktiven Lernbausteinen. Dazu wurden zunächst methodisch-didaktische Vorteile digitaler Lerninhalte gegenüber klassischen Medien wie Buch und Papier zusammengetragen und mögliche Potentiale im Zusammenhang mit neuen Web 2.0-Technologien aufgezeigt. Darauf aufbauend wurde für existierende Autorenwerkzeuge zur Herstellung digitaler Lernbausteine und bestehende Austauschplattformen analysiert, inwieweit diese bereits Web 2.0-Technologien unterstützen und nutzen. Aus Sicht der Informatik ergab sich aus der Analyse bestehender Systeme ein Anforderungsprofil für ein neues Autorenwerkzeug und eine neue Austauschplattform für digitale Lernbausteine. Das neue System wurde nach dem Ansatz des Design Science Research in einem iterativen Entwicklungsprozess in Form der Webapplikation LearningApps.org realisiert und stetig mit Lehrpersonen aus der Schulpraxis evaluiert. Bei der Entwicklung kamen aktuelle Web-Technologien zur Anwendung. Das Ergebnis der Forschungsarbeit ist ein produktives Informatiksystem, welches bereits von tausenden Nutzern in verschiedenen Ländern sowohl in Schulen als auch in der Wirtschaft eingesetzt wird. In einer empirischen Studie konnte das mit der Systementwicklung angestrebte Ziel, die Herstellung und den Austausch von digitalen Lernbausteinen zu vereinfachen, bestätigt werden. Aus Sicht der Schulpraxis liefert LearningApps.org einen Beitrag zur Methodenvielfalt und zur Nutzung von ICT im Unterricht. Die Ausrichtung des Werkzeugs auf mobile Endgeräte und 1:1-Computing entspricht dem allgemeinen Trend im Bildungswesen. Durch die Verknüpfung des Werkzeugs mit aktuellen Software-Entwicklungen zur Herstellung von digitalen Schulbüchern werden auch Lehrmittelverlage als Zielgruppe angesprochen.

Integration of WSNs into enterprise systems based on semantic physical business entities

Internet of Things based systems are anticipated to gain widespread use in industrial applications. Standardization efforts, like 6L0WPAN and the Constrained Application Protocol (CoAP) have made the integration of wireless sensor nodes possible using Internet technology and web-like access to data (RESTful service access). While there are still some open issues, the interoperability problem in the lower layers can now be considered solved from an enterprise software vendors' point of view. One possible next step towards integration of real-world objects into enterprise systems and solving the corresponding interoperability problems at higher levels is to use semantic web technologies. We introduce an abstraction of real-world objects, called Semantic Physical Business Entities (SPBE), using Linked Data principles. We show that this abstraction nicely fits into enterprise systems, as SPBEs allow a business object centric view on real-world objects, instead of a pure device centric view. The interdependencies between how currently services in an enterprise system are used and how this can be done in a semantic real-world aware enterprise system are outlined, arguing for the need of semantic services and semantic knowledge repositories. We introduce a lightweight query language, which we use to perform a quantitative analysis of our approach to demonstrate its feasibility.

Linked services for M2M communication with Enterprise IT systems

Linking the physical world to the Internet, also known as the Internet of Things, has increased available information and services in everyday life and in the Enterprise world. In Enterprise IT an increasing number of communication is done between IT backend systems and small IoT devices, for example sensor networks or RFID readers. This introduces some challenges in terms of complexity and integration. We are working on the integration of IoT devices into Enterprise IT by leveraging SOA techniques and Semantic Web technologies. We present a SOA based integration platform for connecting WSNs and large enterprise business processes. For ensuring interoperability our platform is based on Linked Services. These are thoroughly described, machine-readable, machine-reasonable service descriptions.

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.

Linked Opinions: Describing Sentiments on the Structured Web of Data

In the paper we report on the results of our experiments on the construction of the opinion ontology. Our aim is to show the benefits of publishing in the open, on the Web, the results of the opinion mining process in a structured form. On the road to achieving this, we attempt to answer the research question to what extent opinion information can be formalized in a unified way. Furthermore, as part of the evaluation, we experiment with the usage of Semantic Web technologies and show particular use cases that support our claims.

OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web

OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web 1. INTRODUCTION. LINGUISTIC TOOLS AND ANNOTATIONS: THEIR LIGHTS AND SHADOWS Computational Linguistics is already a consolidated research area. It builds upon the results of other two major ones, namely Linguistics and Computer Science and Engineering, and it aims at developing computational models of human language (or natural language, as it is termed in this area). Possibly, its most well-known applications are the different tools developed so far for processing human language, such as machine translation systems and speech recognizers or dictation programs. These tools for processing human language are commonly referred to as linguistic tools. Apart from the examples mentioned above, there are also other types of linguistic tools that perhaps are not so well-known, but on which most of the other applications of Computational Linguistics are built. These other types of linguistic tools comprise POS taggers, natural language parsers and semantic taggers, amongst others. All of them can be termed linguistic annotation tools. Linguistic annotation tools are important assets. In fact, POS and semantic taggers (and, to a lesser extent, also natural language parsers) have become critical resources for the computer applications that process natural language. Hence, any computer application that has to analyse a text automatically and ‘intelligently’ will include at least a module for POS tagging. The more an application needs to ‘understand’ the meaning of the text it processes, the more linguistic tools and/or modules it will incorporate and integrate. However, linguistic annotation tools have still some limitations, which can be summarised as follows: 1. Normally, they perform annotations only at a certain linguistic level (that is, Morphology, Syntax, Semantics, etc.). 2. They usually introduce a certain rate of errors and ambiguities when tagging. This error rate ranges from 10 percent up to 50 percent of the units annotated for unrestricted, general texts. 3. Their annotations are most frequently formulated in terms of an annotation schema designed and implemented ad hoc. A priori, it seems that the interoperation and the integration of several linguistic tools into an appropriate software architecture could most likely solve the limitations stated in (1). Besides, integrating several linguistic annotation tools and making them interoperate could also minimise the limitation stated in (2). Nevertheless, in the latter case, all these tools should produce annotations for a common level, which would have to be combined in order to correct their corresponding errors and inaccuracies. Yet, the limitation stated in (3) prevents both types of integration and interoperation from being easily achieved. In addition, most high-level annotation tools rely on other lower-level annotation tools and their outputs to generate their own ones. For example, sense-tagging tools (operating at the semantic level) often use POS taggers (operating at a lower level, i.e., the morphosyntactic) to identify the grammatical category of the word or lexical unit they are annotating. Accordingly, if a faulty or inaccurate low-level annotation tool is to be used by other higher-level one in its process, the errors and inaccuracies of the former should be minimised in advance. Otherwise, these errors and inaccuracies would be transferred to (and even magnified in) the annotations of the high-level annotation tool. Therefore, it would be quite useful to find a way to (i) correct or, at least, reduce the errors and the inaccuracies of lower-level linguistic tools; (ii) unify the annotation schemas of different linguistic annotation tools or, more generally speaking, make these tools (as well as their annotations) interoperate. Clearly, solving (i) and (ii) should ease the automatic annotation of web pages by means of linguistic tools, and their transformation into Semantic Web pages (Berners-Lee, Hendler and Lassila, 2001). Yet, as stated above, (ii) is a type of interoperability problem. There again, ontologies (Gruber, 1993; Borst, 1997) have been successfully applied thus far to solve several interoperability problems. Hence, ontologies should help solve also the problems and limitations of linguistic annotation tools aforementioned. Thus, to summarise, the main aim of the present work was to combine somehow these separated approaches, mechanisms and tools for annotation from Linguistics and Ontological Engineering (and the Semantic Web) in a sort of hybrid (linguistic and ontological) annotation model, suitable for both areas. This hybrid (semantic) annotation model should (a) benefit from the advances, models, techniques, mechanisms and tools of these two areas; (b) minimise (and even solve, when possible) some of the problems found in each of them; and (c) be suitable for the Semantic Web. The concrete goals that helped attain this aim are presented in the following section. 2. GOALS OF THE PRESENT WORK As mentioned above, the main goal of this work was to specify a hybrid (that is, linguistically-motivated and ontology-based) model of annotation suitable for the Semantic Web (i.e. it had to produce a semantic annotation of web page contents). This entailed that the tags included in the annotations of the model had to (1) represent linguistic concepts (or linguistic categories, as they are termed in ISO/DCR (2008)), in order for this model to be linguistically-motivated; (2) be ontological terms (i.e., use an ontological vocabulary), in order for the model to be ontology-based; and (3) be structured (linked) as a collection of ontology-based triples, as in the usual Semantic Web languages (namely RDF(S) and OWL), in order for the model to be considered suitable for the Semantic Web. Besides, to be useful for the Semantic Web, this model should provide a way to automate the annotation of web pages. As for the present work, this requirement involved reusing the linguistic annotation tools purchased by the OEG research group (http://www.oeg-upm.net), but solving beforehand (or, at least, minimising) some of their limitations. Therefore, this model had to minimise these limitations by means of the integration of several linguistic annotation tools into a common architecture. Since this integration required the interoperation of tools and their annotations, ontologies were proposed as the main technological component to make them effectively interoperate. From the very beginning, it seemed that the formalisation of the elements and the knowledge underlying linguistic annotations within an appropriate set of ontologies would be a great step forward towards the formulation of such a model (henceforth referred to as OntoTag). Obviously, first, to combine the results of the linguistic annotation tools that operated at the same level, their annotation schemas had to be unified (or, preferably, standardised) in advance. This entailed the unification (id. standardisation) of their tags (both their representation and their meaning), and their format or syntax. Second, to merge the results of the linguistic annotation tools operating at different levels, their respective annotation schemas had to be (a) made interoperable and (b) integrated. And third, in order for the resulting annotations to suit the Semantic Web, they had to be specified by means of an ontology-based vocabulary, and structured by means of ontology-based triples, as hinted above. Therefore, a new annotation scheme had to be devised, based both on ontologies and on this type of triples, which allowed for the combination and the integration of the annotations of any set of linguistic annotation tools. This annotation scheme was considered a fundamental part of the model proposed here, and its development was, accordingly, another major objective of the present work. All these goals, aims and objectives could be re-stated more clearly as follows: Goal 1: Development of a set of ontologies for the formalisation of the linguistic knowledge relating linguistic annotation. Sub-goal 1.1: Ontological formalisation of the EAGLES (1996a; 1996b) de facto standards for morphosyntactic and syntactic annotation, in a way that helps respect the triple structure recommended for annotations in these works (which is isomorphic to the triple structures used in the context of the Semantic Web). Sub-goal 1.2: Incorporation into this preliminary ontological formalisation of other existing standards and standard proposals relating the levels mentioned above, such as those currently under development within ISO/TC 37 (the ISO Technical Committee dealing with Terminology, which deals also with linguistic resources and annotations). Sub-goal 1.3: Generalisation and extension of the recommendations in EAGLES (1996a; 1996b) and ISO/TC 37 to the semantic level, for which no ISO/TC 37 standards have been developed yet. Sub-goal 1.4: Ontological formalisation of the generalisations and/or extensions obtained in the previous sub-goal as generalisations and/or extensions of the corresponding ontology (or ontologies). Sub-goal 1.5: Ontological formalisation of the knowledge required to link, combine and unite the knowledge represented in the previously developed ontology (or ontologies). Goal 2: Development of OntoTag’s annotation scheme, a standard-based abstract scheme for the hybrid (linguistically-motivated and ontological-based) annotation of texts. Sub-goal 2.1: Development of the standard-based morphosyntactic annotation level of OntoTag’s scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996a) and also the recommendations included in the ISO/MAF (2008) standard draft. Sub-goal 2.2: Development of the standard-based syntactic annotation level of the hybrid abstract scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996b) and the ISO/SynAF (2010) standard draft. Sub-goal 2.3: Development of the standard-based semantic annotation level of OntoTag’s (abstract) scheme. Sub-goal 2.4: Development of the mechanisms for a convenient integration of the three annotation levels already mentioned. These mechanisms should take into account the recommendations included in the ISO/LAF (2009) standard draft. Goal 3: Design of OntoTag’s (abstract) annotation architecture, an abstract architecture for the hybrid (semantic) annotation of texts (i) that facilitates the integration and interoperation of different linguistic annotation tools, and (ii) whose results comply with OntoTag’s annotation scheme. Sub-goal 3.1: Specification of the decanting processes that allow for the classification and separation, according to their corresponding levels, of the results of the linguistic tools annotating at several different levels. Sub-goal 3.2: Specification of the standardisation processes that allow (a) complying with the standardisation requirements of OntoTag’s annotation scheme, as well as (b) combining the results of those linguistic tools that share some level of annotation. Sub-goal 3.3: Specification of the merging processes that allow for the combination of the output annotations and the interoperation of those linguistic tools that share some level of annotation. Sub-goal 3.4: Specification of the merge processes that allow for the integration of the results and the interoperation of those tools performing their annotations at different levels. Goal 4: Generation of OntoTagger’s schema, a concrete instance of OntoTag’s abstract scheme for a concrete set of linguistic annotations. These linguistic annotations result from the tools and the resources available in the research group, namely • Bitext’s DataLexica (http://www.bitext.com/EN/datalexica.asp), • LACELL’s (POS) tagger (http://www.um.es/grupos/grupo-lacell/quees.php), • Connexor’s FDG (http://www.connexor.eu/technology/machinese/glossary/fdg/), and • EuroWordNet (Vossen et al., 1998). This schema should help evaluate OntoTag’s underlying hypotheses, stated below. Consequently, it should implement, at least, those levels of the abstract scheme dealing with the annotations of the set of tools considered in this implementation. This includes the morphosyntactic, the syntactic and the semantic levels. Goal 5: Implementation of OntoTagger’s configuration, a concrete instance of OntoTag’s abstract architecture for this set of linguistic tools and annotations. This configuration (1) had to use the schema generated in the previous goal; and (2) should help support or refute the hypotheses of this work as well (see the next section). Sub-goal 5.1: Implementation of the decanting processes that facilitate the classification and separation of the results of those linguistic resources that provide annotations at several different levels (on the one hand, LACELL’s tagger operates at the morphosyntactic level and, minimally, also at the semantic level; on the other hand, FDG operates at the morphosyntactic and the syntactic levels and, minimally, at the semantic level as well). Sub-goal 5.2: Implementation of the standardisation processes that allow (i) specifying the results of those linguistic tools that share some level of annotation according to the requirements of OntoTagger’s schema, as well as (ii) combining these shared level results. In particular, all the tools selected perform morphosyntactic annotations and they had to be conveniently combined by means of these processes. Sub-goal 5.3: Implementation of the merging processes that allow for the combination (and possibly the improvement) of the annotations and the interoperation of the tools that share some level of annotation (in particular, those relating the morphosyntactic level, as in the previous sub-goal). Sub-goal 5.4: Implementation of the merging processes that allow for the integration of the different standardised and combined annotations aforementioned, relating all the levels considered. Sub-goal 5.5: Improvement of the semantic level of this configuration by adding a named entity recognition, (sub-)classification and annotation subsystem, which also uses the named entities annotated to populate a domain ontology, in order to provide a concrete application of the present work in the two areas involved (the Semantic Web and Corpus Linguistics). 3. MAIN RESULTS: ASSESSMENT OF ONTOTAG’S UNDERLYING HYPOTHESES The model developed in the present thesis tries to shed some light on (i) whether linguistic annotation tools can effectively interoperate; (ii) whether their results can be combined and integrated; and, if they can, (iii) how they can, respectively, interoperate and be combined and integrated. Accordingly, several hypotheses had to be supported (or rejected) by the development of the OntoTag model and OntoTagger (its implementation). The hypotheses underlying OntoTag are surveyed below. Only one of the hypotheses (H.6) was rejected; the other five could be confirmed. H.1 The annotations of different levels (or layers) can be integrated into a sort of overall, comprehensive, multilayer and multilevel annotation, so that their elements can complement and refer to each other. • CONFIRMED by the development of: o OntoTag’s annotation scheme, o OntoTag’s annotation architecture, o OntoTagger’s (XML, RDF, OWL) annotation schemas, o OntoTagger’s configuration. H.2 Tool-dependent annotations can be mapped onto a sort of tool-independent annotations and, thus, can be standardised. • CONFIRMED by means of the standardisation phase incorporated into OntoTag and OntoTagger for the annotations yielded by the tools. H.3 Standardisation should ease: H.3.1: The interoperation of linguistic tools. H.3.2: The comparison, combination (at the same level and layer) and integration (at different levels or layers) of annotations. • H.3 was CONFIRMED by means of the development of OntoTagger’s ontology-based configuration: o Interoperation, comparison, combination and integration of the annotations of three different linguistic tools (Connexor’s FDG, Bitext’s DataLexica and LACELL’s tagger); o Integration of EuroWordNet-based, domain-ontology-based and named entity annotations at the semantic level. o Integration of morphosyntactic, syntactic and semantic annotations. H.4 Ontologies and Semantic Web technologies (can) play a crucial role in the standardisation of linguistic annotations, by providing consensual vocabularies and standardised formats for annotation (e.g., RDF triples). • CONFIRMED by means of the development of OntoTagger’s RDF-triple-based annotation schemas. H.5 The rate of errors introduced by a linguistic tool at a given level, when annotating, can be reduced automatically by contrasting and combining its results with the ones coming from other tools, operating at the same level. However, these other tools might be built following a different technological (stochastic vs. rule-based, for example) or theoretical (dependency vs. HPS-grammar-based, for instance) approach. • CONFIRMED by the results yielded by the evaluation of OntoTagger. H.6 Each linguistic level can be managed and annotated independently. • REJECTED: OntoTagger’s experiments and the dependencies observed among the morphosyntactic annotations, and between them and the syntactic annotations. In fact, Hypothesis H.6 was already rejected when OntoTag’s ontologies were developed. We observed then that several linguistic units stand on an interface between levels, belonging thereby to both of them (such as morphosyntactic units, which belong to both the morphological level and the syntactic level). Therefore, the annotations of these levels overlap and cannot be handled independently when merged into a unique multileveled annotation. 4. OTHER MAIN RESULTS AND CONTRIBUTIONS First, interoperability is a hot topic for both the linguistic annotation community and the whole Computer Science field. The specification (and implementation) of OntoTag’s architecture for the combination and integration of linguistic (annotation) tools and annotations by means of ontologies shows a way to make these different linguistic annotation tools and annotations interoperate in practice. Second, as mentioned above, the elements involved in linguistic annotation were formalised in a set (or network) of ontologies (OntoTag’s linguistic ontologies). • On the one hand, OntoTag’s network of ontologies consists of − The Linguistic Unit Ontology (LUO), which includes a mostly hierarchical formalisation of the different types of linguistic elements (i.e., units) identifiable in a written text; − The Linguistic Attribute Ontology (LAO), which includes also a mostly hierarchical formalisation of the different types of features that characterise the linguistic units included in the LUO; − The Linguistic Value Ontology (LVO), which includes the corresponding formalisation of the different values that the attributes in the LAO can take; − The OIO (OntoTag’s Integration Ontology), which  Includes the knowledge required to link, combine and unite the knowledge represented in the LUO, the LAO and the LVO;  Can be viewed as a knowledge representation ontology that describes the most elementary vocabulary used in the area of annotation. • On the other hand, OntoTag’s ontologies incorporate the knowledge included in the different standards and recommendations for linguistic annotation released so far, such as those developed within the EAGLES and the SIMPLE European projects or by the ISO/TC 37 committee: − As far as morphosyntactic annotations are concerned, OntoTag’s ontologies formalise the terms in the EAGLES (1996a) recommendations and their corresponding terms within the ISO Morphosyntactic Annotation Framework (ISO/MAF, 2008) standard; − As for syntactic annotations, OntoTag’s ontologies incorporate the terms in the EAGLES (1996b) recommendations and their corresponding terms within the ISO Syntactic Annotation Framework (ISO/SynAF, 2010) standard draft; − Regarding semantic annotations, OntoTag’s ontologies generalise and extend the recommendations in EAGLES (1996a; 1996b) and, since no stable standards or standard drafts have been released for semantic annotation by ISO/TC 37 yet, they incorporate the terms in SIMPLE (2000) instead; − The terms coming from all these recommendations and standards were supplemented by those within the ISO Data Category Registry (ISO/DCR, 2008) and also of the ISO Linguistic Annotation Framework (ISO/LAF, 2009) standard draft when developing OntoTag’s ontologies. Third, we showed that the combination of the results of tools annotating at the same level can yield better results (both in precision and in recall) than each tool separately. In particular, 1. OntoTagger clearly outperformed two of the tools integrated into its configuration, namely DataLexica and FDG in all the combination sub-phases in which they overlapped (i.e. POS tagging, lemma annotation and morphological feature annotation). As far as the remaining tool is concerned, i.e. LACELL’s tagger, it was also outperformed by OntoTagger in POS tagging and lemma annotation, and it did not behave better than OntoTagger in the morphological feature annotation layer. 2. As an immediate result, this implies that a) This type of combination architecture configurations can be applied in order to improve significantly the accuracy of linguistic annotations; and b) Concerning the morphosyntactic level, this could be regarded as a way of constructing more robust and more accurate POS tagging systems. Fourth, Semantic Web annotations are usually performed by humans or else by machine learning systems. Both of them leave much to be desired: the former, with respect to their annotation rate; the latter, with respect to their (average) precision and recall. In this work, we showed how linguistic tools can be wrapped in order to annotate automatically Semantic Web pages using ontologies. This entails their fast, robust and accurate semantic annotation. As a way of example, as mentioned in Sub-goal 5.5, we developed a particular OntoTagger module for the recognition, classification and labelling of named entities, according to the MUC and ACE tagsets (Chinchor, 1997; Doddington et al., 2004). These tagsets were further specified by means of a domain ontology, namely the Cinema Named Entities Ontology (CNEO). This module was applied to the automatic annotation of ten different web pages containing cinema reviews (that is, around 5000 words). In addition, the named entities annotated with this module were also labelled as instances (or individuals) of the classes included in the CNEO and, then, were used to populate this domain ontology. • The statistical results obtained from the evaluation of this particular module of OntoTagger can be summarised as follows. On the one hand, as far as recall (R) is concerned, (R.1) the lowest value was 76,40% (for file 7); (R.2) the highest value was 97, 50% (for file 3); and (R.3) the average value was 88,73%. On the other hand, as far as the precision rate (P) is concerned, (P.1) its minimum was 93,75% (for file 4); (R.2) its maximum was 100% (for files 1, 5, 7, 8, 9, and 10); and (R.3) its average value was 98,99%. • These results, which apply to the tasks of named entity annotation and ontology population, are extraordinary good for both of them. They can be explained on the basis of the high accuracy of the annotations provided by OntoTagger at the lower levels (mainly at the morphosyntactic level). However, they should be conveniently qualified, since they might be too domain- and/or language-dependent. It should be further experimented how our approach works in a different domain or a different language, such as French, English, or German. • In any case, the results of this application of Human Language Technologies to Ontology Population (and, accordingly, to Ontological Engineering) seem very promising and encouraging in order for these two areas to collaborate and complement each other in the area of semantic annotation. Fifth, as shown in the State of the Art of this work, there are different approaches and models for the semantic annotation of texts, but all of them focus on a particular view of the semantic level. Clearly, all these approaches and models should be integrated in order to bear a coherent and joint semantic annotation level. OntoTag shows how (i) these semantic annotation layers could be integrated together; and (ii) they could be integrated with the annotations associated to other annotation levels. Sixth, we identified some recommendations, best practices and lessons learned for annotation standardisation, interoperation and merge. They show how standardisation (via ontologies, in this case) enables the combination, integration and interoperation of different linguistic tools and their annotations into a multilayered (or multileveled) linguistic annotation, which is one of the hot topics in the area of Linguistic Annotation. And last but not least, OntoTag’s annotation scheme and OntoTagger’s annotation schemas show a way to formalise and annotate coherently and uniformly the different units and features associated to the different levels and layers of linguistic annotation. This is a great scientific step ahead towards the global standardisation of this area, which is the aim of ISO/TC 37 (in particular, Subcommittee 4, dealing with the standardisation of linguistic annotations and resources).