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.

A Restriction-Centered Theory of Reasoning and Computation to materialize a Web 3.0

Researchers suggest that personalization on the Semantic Web adds up to a Web 3.0 eventually. In this Web, personalized agents process and thus generate the biggest share of information rather than humans. In the sense of emergent semantics, which supplements traditional formal semantics of the Semantic Web, this is well conceivable. An emergent Semantic Web underlying fuzzy grassroots ontology can be accomplished through inducing knowledge from users' common parlance in mutual Web 2.0 interactions [1]. These ontologies can also be matched against existing Semantic Web ontologies, to create comprehensive top-level ontologies. On the Web, if augmented with information in the form of restrictions andassociated reliability (Z-numbers) [2], this collection of fuzzy ontologies constitutes an important basis for an implementation of Zadeh's restriction-centered theory of reasoning and computation (RRC) [3]. By considering real world's fuzziness, RRC differs from traditional approaches because it can handle restrictions described in natural language. A restriction is an answer to a question of the value of a variable such as the duration of an appointment. In addition to mathematically well-defined answers, RRC can likewise deal with unprecisiated answers as "about one hour." Inspired by mental functions, it constitutes an important basis to leverage present-day Web efforts to a natural Web 3.0. Based on natural language information, RRC may be accomplished with Z-number calculation to achieve a personalized Web reasoning and computation. Finally, through Web agents' understanding of natural language, they can react to humans more intuitively and thus generate and process information.

The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases

This chapter presents fuzzy cognitive maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. The corresponding Web KnowARR framework incorporates findings from fuzzy logic. To this end, a first emphasis is particularly on the Web KnowARR framework along with a stakeholder management use case to illustrate the framework’s usefulness as a second focal point. This management form is to help projects to acceptance and assertiveness where claims for company decisions are actively involved in the management process. Stakeholder maps visually (re-) present these claims. On one hand, they resort to non-public content and on the other they resort to content that is available to the public (mostly on the Web). The Semantic Web offers opportunities not only to present public content descriptively but also to show relationships. The proposed framework can serve as the basis for the public content of stakeholder maps.

The state of semantic technology today - overview of the first SEALS evaluation campaigns

This paper describes the first five SEALS Evaluation Campaigns over the semantic technologies covered by the SEALS project (ontology engineering tools, ontology reasoning tools, ontology matching tools, semantic search tools, and semantic web service tools). It presents the evaluations and test data used in these campaigns and the tools that participated in them along with a comparative analysis of their results. It also presents some lessons learnt after the execution of the evaluation campaigns and draws some final conclusions.

Style Guidelines for Naming and Labeling Ontologies in the Multilingual Web

In the context of the Semantic Web, natural language descriptions associated with ontologies have proven to be of major importance not only to support ontology developers and adopters, but also to assist in tasks such as ontology mapping, information extraction, or natural language generation. In the state-of-the-art we find some attempts to provide guidelines for URI local names in English, and also some disagreement on the use of URIs for describing ontology elements. When trying to extrapolate these ideas to a multilingual scenario, some of these approaches fail to provide a valid solution. On the basis of some real experiences in the translation of ontologies from English into Spanish, we provide a preliminary set of guidelines for naming and labeling ontologies in a multilingual scenario.

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.

Cross-lingual Linking on the Multilingual Web of Data (position statement)

Recently, the Semantic Web has experienced signi�cant advancements in standards and techniques, as well as in the amount of semantic information available online. Even so, mechanisms are still needed to automatically reconcile semantic information when it is expressed in di�erent natural languages, so that access to Web information across language barriers can be improved. That requires developing techniques for discovering and representing cross-lingual links on the Web of Data. In this paper we explore the different dimensions of such a problem and reflect on possible avenues of research on that topic.

Challenges for the Multilingual Web of Data

The Web has witnessed an enormous growth in the amount of semantic information published in recent years. This growth has been stimulated to a large extent by the emergence of Linked Data. Although this brings us a big step closer to the vision of a Semantic Web, it also raises new issues such as the need for dealing with information expressed in different natural languages. Indeed, although the Web of Data can contain any kind of information in any language, it still lacks explicit mechanisms to automatically reconcile such information when it is expressed in different languages. This leads to situations in which data expressed in a certain language is not easily accessible to speakers of other languages. The Web of Data shows the potential for being extended to a truly multilingual web as vocabularies and data can be published in a language-independent fashion, while associated language-dependent (linguistic) information supporting the access across languages can be stored separately. In this sense, the multilingual Web of Data can be realized in our view as a layer of services and resources on top of the existing Linked Data infrastructure adding i) linguistic information for data and vocabularies in different languages, ii) mappings between data with labels in different languages, and iii) services to dynamically access and traverse Linked Data across different languages. In this article we present this vision of a multilingual Web of Data. We discuss challenges that need to be addressed to make this vision come true and discuss the role that techniques such as ontology localization, ontology mapping, and cross-lingual ontology-based information access and presentation will play in achieving this. Further, we propose an initial architecture and describe a roadmap that can provide a basis for the implementation of this vision.

What is the current state of the Multilingual Web of Data?

The Semantic Web is growing at a fast pace, recently boosted by the creation of the Linked Data initiative and principles. Methods, standards, techniques and the state of technology are becoming more mature and therefore are easing the task of publication and consumption of semantic information on the Web.

Semantic evaluation at large scale (SEALS)

This paper describes the main goals and outcomes of the EU-funded Framework 7 project entitled Semantic Evaluation at Large Scale (SEALS). The growth and success of the Semantic Web is built upon a wide range of Semantic technologies from ontology engineering tools through to semantic web service discovery and semantic search. The evaluation of such technologies ? and, indeed, assessments of their mutual compatibility ? is critical for their sustained improvement and adoption. The SEALS project is creating an open and sustainable platform on which all aspects of an evaluation can be hosted and executed and has been designed to accommodate most technology types. It is envisaged that the platform will become the de facto repository of test datasets and will allow anyone to organise, execute and store the results of technology evaluations free of charge and without corporate bias. The demonstration will show how individual tools can be prepared for evaluation, uploaded to the platform, evaluated according to some criteria and the subsequent results viewed. In addition, the demonstration will show the flexibility and power of the SEALS Platform for evaluation organisers by highlighting some of the key technologies used.

Enabling Language Resources to expose translations as linked data on the web

Language resources, such as multilingual lexica and multilingual electronic dictionaries, contain collections of lexical entries in several languages. Having access to the corresponding explicit or implicit translation relations between such entries might be of great interest for many NLP-based applications. By using Semantic Web-based techniques, translations can be available on the Web to be consumed by other (semantic enabled) resources in a direct manner, not relying on application-specific formats. To that end, in this paper we propose a model for representing translations as linked data, as an extension of the lemon model. Our translation module represents some core information associated to term translations and does not commit to specific views or translation theories. As a proof of concept, we have extracted the translations of the terms contained in Terminesp, a multilingual terminological database, and represented them as linked data. We have made them accessible on the Web both for humans (via a Web interface) and software agents (with a SPARQL endpoint).

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 Semantic Workflow Mechanism to Realize Experimental Goals and Constraints

Postprint

Semantic Support for Computational Land-Use Modelling

Postprint

Estudio de fiabilidad y viabilidad de la Web 2.0 y la Web semántica para enriquecer lexicones en el dominio farmacológico

Los actuales sistemas de Reconocimiento de Entidades en el dominio farmacológico, necesarios como apoyo para el personal sanitario en el proceso de prescripción de un tratamiento farmacológico, sufren limitaciones relacionadas con la falta de cobertura de las bases de datos oficiales. Parece por tanto necesario analizar la fiabilidad de los recursos actuales existentes, tanto en la Web Semántica como en la Web 2.0, y determinar si es o no viable utilizar dichos recursos como fuentes de información complementarias que permitan generar y/o enriquecer lexicones empleados por sistemas de Reconocimiento de Entidades. Por ello, en este trabajo se analizan las principales fuentes de información relativas al dominio farmacológico disponibles en Internet. Este análisis permite concluir que existe información fiable y que dicha información permitiría enriquecer los lexicones existentes con sinónimos y otras variaciones léxicas o incluso con información histórica no recogida ni mantenida en las bases de datos oficiales.