Improved Prediction of Heuristic Configuration for Queue Priority on FaCt++ Semantic Reasoner

With the adoption of the semantic web, interest in technologies and theory about formalizing the representation of knowledge, and automated reasoning has increased. Ontologies are concrete instances of knowledge representation and logical reasoners play an important role during the creation of ontologies, since they can find logical errors during design. One of these logical reasoners is FaCt++, which implements an optimized analytical tableaux algorithm. The specific implementation of tableaux in FaCt++ includes a set of priority queues to handle and expand the different operators that can be found during reasoning, these queues have an order for applying the different operators, which in this work will be referred as priority configurations. It was proved by the authors of FaCt++ that there is not a single priority configuration that has the best performance for all types of ontologies. Recently it was suggested that machine learning models can be successfully applied to find the best heuristic for every specific ontology. In this work is presented the process to build a machine learning model to find the best priority configuration for every ontology in detail. The model proposed in this work uses fewer features than the one shown previously and creates a simpler model with similar or better accuracy on the resulting classification.ITESO, A. C

Semantic Web Services Provisioning

Semantic Web Services constitute an important research area, where vari ous underlying frameworks, such as WSMO and OWL-S, define Semantic Web ontologies to describe Web services, so they can be automatically discovered, composed, and invoked. Service discovery has been traditionally interpreted as a functional filter in current Semantic Web Services frameworks, frequently performed by Description Logics reasoners. However, semantic provisioning has to be performed taking Quality-of-Service (QOS) into account, defining user preferences that enable QOS-aware Semantic Web Service selection. Nowadays, the research focus is actually on QOS-aware processes, so cur rent proposals are developing the field by providing QOS support to semantic provisioning, especially in selection processes. These processes lead to opti mization problems, where the best service among a set of services has to be selected, so Description Logics cannot be used in this context. Furthermore, user preferences has to be semantically defined so they can be used within selection processes. There are several proposals that extend Semantic Web Services frameworks allowing QOS-aware semantic provisioning. However, proposed selection techniques are very coupled with their proposed extensions, most of them being implemented ad hoc. Thus, there is a semantic gap between functional descriptions (usually using WSMO or OWL-S) and user preferences, which are specific for each proposal, using different ontologies or even non-semantic de scriptions, and depending on its corresponding ad hoc selection technique. In this report, we give an overview of most important Semantic Web Ser vices frameworks, showing a comparison between them. Then, a thorough analysis of state-of-the art proposals on QOS-aware semantic provisioning and user preferences descriptions is presented, discussing about their applicabil ity, advantages, and defects. Results from this analysis motivate our research work, which has been already materialized in two early contributions.Los servicios web semánticos constituyen un importante campo de inves tigación, en el cual distintos frameworks, como por ejemplo WSMO y OWL-S, definen ontologías de la web semántica para describir servicios web, de for ma que estos puedan ser descubiertos, compuestos e invocados de manera automática. El descubrimiento de servicios ha sido interpretado tradicional mente como un filtro funcional en los frameworks actuales de servicios web semánticos, usando para ello razonadores de lógica descriptiva. Sin embargo, las tareas de aprovisionamiento semántico deberían tener en cuenta la calidad del servicio, definiendo para ello preferencias de usuario de manera que sea posible realizar una selección de servicios web semánticos sensible a la cali dad. Actualmente, el foco de la investigación está en procesos sensibles a la ca lidad, por lo que las propuestas actuales están trabajando en este campo intro duciendo el soporte adecuado a la calidad del servicio dentro del aprovisio namiento semántico, y principalmente en las tareas de selección. Estas tareas desembocan en problemas de optimización, donde el mejor servicio de entre un concjunto debe ser seleccionado, por lo que las lógicas descriptivas no pue den ser usadas en este contexto. Además, las preferencias de usuario deben ser definidas semánticamente, de forma que puedan ser usadas en las tareas de selección. Existen bastantes propuestas que extienden los frameworks de servicios web semánticos para habilitar el aprovisionamiento sensible a la calidad. Sin embargo, las técnicas de selección propuestas están altamente acopladas con dichas extensiones, donde la mayoría de ellas implementan algoritmos ad hoc. Por tanto, existe un salto semántico entre las descripciones funcionales (nor malmente usando WSMO o OWL-S) y las preferencias de usuario, las cuales son definidas específicamente por cada propuesta, usando ontologías distin tas o incluso descripciones no semánticas que dependen de la correspondiente técnica de selección ad hoc

Managing Uncertainty and Vagueness in Semantic Web

Ο Σημασιολογικός Ιστός στοχεύει στην διεκπεραίωση εργασιών σε υπολογιστικά συστήματα χωρίς την ανθρώπινη παρέμβαση. Προκειμένου να επιτευχθεί ο στόχος αυτός, εισάγεται η έννοια της πληροφορίας που είναι επεξεργάσιμη από μηχανές. Στα περισσότερα προβλήματα, η έννοια της πληροφορίας είναι συνυφασμένη με την έννοια της αβεβαιότητας και της ασάφειας. Και οι δύο έννοιες περιγράφονται με την κοινή ονομασία ατελής πληροφορία. Δεδομένου ότι ο Σημασιολογικός Ιστός απαρτίζεται από ένα σύνολο τεχνολογιών και των θεωριών που τις διέπουν, οποιαδήποτε μέθοδος αναπαράστασης θα πρέπει να βρίσκεται σε συμφωνία με άλλες υπάρχουσες. Συγκεκριμένα, το θεωρητικό πλαίσιο πρέπει να εντάσσεται ομαλά στη θεωρία που εφαρμόζεται στο Σημασιολογικό Ιστό. Η δε υλοποίησή του, ιδανικό είναι, να υποστηριχθεί με χρήση μεθόδων του Σημασιολογικού Ιστού, στις οποίες κυριαρχεί εκείνη των οντολογιών. Στη διατριβή μας, ορίσαμε μία μέθοδο αναπαράστασης της αβεβαιότητας και της ασάφειας μέσω ενός ενιαίου πλαισίου. Το μοντέλο Dempster-Shafer χρησιμοποιήθηκε για την αναπαράσταση της αβεβαιότητας και το μοντέλο Ασαφούς Λογικής και Ασαφών Συνόλων για την αναπαράσταση της ασάφειας. Για το λόγο αυτό, ορίσαμε το θεωρητικό πλαίσιο, στοχεύοντας σε ένα συνδυασμό ALC Λογικών Περιγραφών (Description Logics) με το μοντέλο Dempster-Shafer. Κατά τη διάρκεια της έρευνάς μας υλοποιήσαμε μεταοντολογίες για την αναπαράσταση της αβεβαιότητας και της ασάφειας και στη συνέχεια μελετήσαμε την συμπεριφορά τους σε πραγματικές εφαρμογές.Semantic Web has been designed for processing tasks without human intervention. In this context, the term machine processable information has been introduced. In most Semantic Web tasks, we come across information incompleteness issues, aka uncertainty and vagueness. For this reason, a method that represents uncertainty and vagueness under a common framework has to be defined. Semantic Web technologies are defined through a Semantic Web Stack and are based on a clear formal foundation. Therefore, any representation scheme should be aligned with these technologies and be formally defined. As the concept of ontologies is significant in the Semantic Web for representing knowledge, any framework is desirable to be built upon it. In our work, we have defined an approach for representing uncertainty and vagueness under a common framework. Uncertainty is represented through Dempster-Shafer model, whereas vagueness has been represented through Fuzzy Logic and Fuzzy Sets. For this reason, we have defined our theoretical framework, aimed at a combination of the classical crisp DL ALC with a Dempster-Shafer module. As a next step, we added fuzziness to this model. Throughout our work, we have implemented metaontologies in order to represent uncertain and vague concepts and, next, we have tested our methodology in real-world applications

Visual Design of Ontologies for Semantic Web

Tato práce popisuje návrh a implementaci vizuálního editoru ontologií pro Sémanticý web, založený na RDF modelu, soustředící se na přehlednou kompaktní vizualizaci ontologií, jejich selektivní zobrazení z různých aspektů, a jejich tvorbu s rozšířítelností v nabídce ontologických jazyků.This thesis describes design and implementation of a visual ontology editor for the Semantic Web, based on the RDF model, focusing on compact ontology visualization, selective views of them from various aspects and their creation supporting extensible number of ontology languages.

Foundations of Fuzzy Logic and Semantic Web Languages

This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic

Semantic technologies: from niche to the mainstream of Web 3? A comprehensive framework for web Information modelling and semantic annotation

Context: Web information technologies developed and applied in the last decade have considerably changed the way web applications operate and have revolutionised information management and knowledge discovery. Social technologies, user-generated classification schemes and formal semantics have a far-reaching sphere of influence. They promote collective intelligence, support interoperability, enhance sustainability and instigate innovation. Contribution: The research carried out and consequent publications follow the various paradigms of semantic technologies, assess each approach, evaluate its efficiency, identify the challenges involved and propose a comprehensive framework for web information modelling and semantic annotation, which is the thesis’ original contribution to knowledge. The proposed framework assists web information modelling, facilitates semantic annotation and information retrieval, enables system interoperability and enhances information quality. Implications: Semantic technologies coupled with social media and end-user involvement can instigate innovative influence with wide organisational implications that can benefit a considerable range of industries. The scalable and sustainable business models of social computing and the collective intelligence of organisational social media can be resourcefully paired with internal research and knowledge from interoperable information repositories, back-end databases and legacy systems. Semantified information assets can free human resources so that they can be used to better serve business development, support innovation and increase productivity

Providing packages of relevant ATM information: An ontology-based approach

ATM information providers publish reports and notifications of different types using standardized information exchange models. For a typical information user, e.g., an aircraft pilot, only a fraction of the published information is relevant for a particular task. Filtering out irrelevant information from different information sources is in itself a challenging task, yet it is only a first step in providing relevant information, the challenges concerning maintenance, auditability, availability, integration, comprehensibility, and traceability. This paper presents the Semantic Container approach, which employs ontology-based faceted information filtering and allows for the packaging of filtered information and associated metadata in semantic containers, thus facilitating reuse of filtered information at different levels. The paper formally defines an abstract model of ontology-based information filtering and the structure of semantic containers, their composition, versioning, discovery, and replicated physical allocation. The paper further discusses different usage scenarios, the role of semantic containers in SWIM, an architecture for a semantic container management system, as well as a proof-of-concept prototype. Finally the paper discusses a blockchain-based notary service to realize tamper-proof version histories for semantic containers.acceptedVersio

Forum Session at the First International Conference on Service Oriented Computing (ICSOC03)

The First International Conference on Service Oriented Computing (ICSOC) was held in Trento, December 15-18, 2003. The focus of the conference ---Service Oriented Computing (SOC)--- is the new emerging paradigm for distributed computing and e-business processing that has evolved from object-oriented and component computing to enable building agile networks of collaborating business applications distributed within and across organizational boundaries. Of the 181 papers submitted to the ICSOC conference, 10 were selected for the forum session which took place on December the 16th, 2003. The papers were chosen based on their technical quality, originality, relevance to SOC and for their nature of being best suited for a poster presentation or a demonstration. This technical report contains the 10 papers presented during the forum session at the ICSOC conference. In particular, the last two papers in the report ere submitted as industrial papers

Enabling Complex Semantic Queries to Bioinformatics Databases through Intuitive Search Over Data

Data integration promises to be one of the main catalysts in enabling new insights to be drawn from the wealth of biological data already available publicly. However, the heterogene- ity of the existing data sources still poses significant challenges for achieving interoperability among biological databases. Furthermore, merely solving the technical challenges of data in- tegration, for example through the use of common data representation formats, leaves open the larger problem. Namely, the steep learning curve required for understanding the data models of each public source, as well as the technical language through which the sources can be queried and joined. As a consequence, most of the available biological data remain practically unexplored today. In this thesis, we address these problems jointly, by first introducing an ontology-based data integration solution in order to mitigate the data source heterogeneity problem. We illustrate through the concrete example of Bgee, a gene expression data source, how relational databases can be exposed as virtual Resource Description Framework (RDF) graphs, through relational-to-RDF mappings. This has the important advantage that the original data source can remain unmodified, while still becoming interoperable with external RDF sources. We complement our methods with applied case studies designed to guide domain experts in formulating expressive federated queries targeting the integrated data across the domains of evolutionary relationships and gene expression. More precisely, we introduce two com- parative analyses, first within the same domain (using orthology data from multiple, inter- operable, data sources) and second across domains, in order to study the relation between expression change and evolution rate following a duplication event. Finally, in order to bridge the semantic gap between users and data, we design and im- plement Bio-SODA, a question answering system over domain knowledge graphs, that does not require training data for translating user questions to SPARQL. Bio-SODA uses a novel ranking approach that combines syntactic and semantic similarity, while also incorporating node centrality metrics to rank candidate matches for a given user question. Our results in testing Bio-SODA across several real-world databases that span multiple domains (both within and outside bioinformatics) show that it can answer complex, multi-fact queries, be- yond the current state-of-the-art in the more well-studied open-domain question answering. -- L’intégration des données promet d’être l’un des principaux catalyseurs permettant d’extraire des nouveaux aperçus de la richesse des données biologiques déjà disponibles publiquement. Cependant, l’hétérogénéité des sources de données existantes pose encore des défis importants pour parvenir à l’interopérabilité des bases de données biologiques. De plus, en surmontant seulement les défis techniques de l’intégration des données, par exemple grâce à l’utilisation de formats standard de représentation de données, on laisse ouvert un problème encore plus grand. À savoir, la courbe d’apprentissage abrupte nécessaire pour comprendre la modéli- sation des données choisie par chaque source publique, ainsi que le langage technique par lequel les sources peuvent être interrogés et jointes. Par conséquent, la plupart des données biologiques publiquement disponibles restent pratiquement inexplorés aujourd’hui. Dans cette thèse, nous abordons l’ensemble des deux problèmes, en introduisant d’abord une solution d’intégration de données basée sur ontologies, afin d’atténuer le problème d’hété- rogénéité des sources de données. Nous montrons, à travers l’exemple de Bgee, une base de données d’expression de gènes, une approche permettant les bases de données relationnelles d’être publiés sous forme de graphes RDF (Resource Description Framework) virtuels, via des correspondances relationnel-vers-RDF (« relational-to-RDF mappings »). Cela présente l’important avantage que la source de données d’origine peut rester inchangé, tout en de- venant interopérable avec les sources RDF externes. Nous complétons nos méthodes avec des études de cas appliquées, conçues pour guider les experts du domaine dans la formulation de requêtes fédérées expressives, ciblant les don- nées intégrées dans les domaines des relations évolutionnaires et de l’expression des gènes. Plus précisément, nous introduisons deux analyses comparatives, d’abord dans le même do- maine (en utilisant des données d’orthologie provenant de plusieurs sources de données in- teropérables) et ensuite à travers des domaines interconnectés, afin d’étudier la relation entre le changement d’expression et le taux d’évolution suite à une duplication de gène. Enfin, afin de mitiger le décalage sémantique entre les utilisateurs et les données, nous concevons et implémentons Bio-SODA, un système de réponse aux questions sur des graphes de connaissances domaine-spécifique, qui ne nécessite pas de données de formation pour traduire les questions des utilisateurs vers SPARQL. Bio-SODA utilise une nouvelle ap- proche de classement qui combine la similarité syntactique et sémantique, tout en incorporant des métriques de centralité des nœuds, pour classer les possibles candidats en réponse à une question utilisateur donnée. Nos résultats suite aux tests effectués en utilisant Bio-SODA sur plusieurs bases de données à travers plusieurs domaines (tantôt liés à la bioinformatique qu’extérieurs) montrent que Bio-SODA réussit à répondre à des questions complexes, en- gendrant multiples entités, au-delà de l’état actuel de la technique en matière de systèmes de réponses aux questions sur les données structures, en particulier graphes de connaissances

Foundations of Fuzzy Logic and Semantic Web Languages

This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and fuzzy logic experts. It also helps researchers of non-Semantic Web languages get a better understanding of the theoretical fundamentals of Semantic Web languages. The first part of the book covers all the theoretical and logical aspects of classical (two-valued) Semantic Web languages. The second part explains how to generalize these languages to cope with fuzzy set theory and fuzzy logic