Deriving semantic sensor metadata from raw measurements

Sensor network deployments have become a primary source of big data about the real world that surrounds us, measuring a wide range of physical properties in real time. With such large amounts of heterogeneous data, a key challenge is to describe and annotate sensor data with high-level metadata, using and extending models, for instance with ontologies. However, to automate this task there is a need for enriching the sensor metadata using the actual observed measurements and extracting useful meta-information from them. This paper proposes a novel approach of characterization and extraction of semantic metadata through the analysis of sensor data raw observations. This approach consists in using approximations to represent the raw sensor measurements, based on distributions of the observation slopes, building a classi?cation scheme to automatically infer sensor metadata like the type of observed property, integrating the semantic analysis results with existing sensor networks metadata.

Workflow-centric research objects: First class citizens in scholarly discourse.

A workflow-centric research object bundles a workflow, the provenance of the results obtained by its enactment, other digital objects that are relevant for the experiment (papers, datasets, etc.), and annotations that semantically describe all these objects. In this paper, we propose a model to specify workflow-centric research objects, and show how the model can be grounded using semantic technologies and existing vocabularies, in particular the Object Reuse and Exchange (ORE) model and the Annotation Ontology (AO).We describe the life-cycle of a research object, which resembles the life-cycle of a scienti?c experiment.

A Recommendation Framework Based on the Analytic Network Process and its Application in the Semantic Technology Domain

When users face a certain problem needing a product, service, or action to solve it, selecting the best alternative among them can be a dicult task due to the uncertainty of their quality. This is especially the case in the domains where users do not have an expertise, like for example in Software Engineering. Multiple criteria decision making (MCDM) methods are methods that help making better decisions when facing the complex problem of selecting the best solution among a group of alternatives that can be compared according to different conflicting criteria. In MCDM problems, alternatives represent concrete products, services or actions that will help in achieving a goal, while criteria represent the characteristics of these alternatives that are important for making a decision.

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.

Influence of the semantic content of urban sounds in the identity of outer spaces

This paper shows the influence of the semantic content of urban sounds in the subjective evaluation of outer spaces. The study is based on the analysis conducted in three neighboring and integrated urban spaces with a different form of social ownership in the city of Cordoba, Argentina. It shows that the type of sound source present at each site influence, by its semantic content, in the user´s identification and permanence in the place. The noise present in a soundscape is able to have a high semantic content, and therefore the sound has a particular meaning for the perceiver. Every particular social group influences the production of their own sounds and how they perceive them. This allows to consider the sound as one of the factors that define the sense of "place" or "no place" of a certain urban space. Evidently the sounds, and their ability to evoke and characterize the environment, cannot be ignored in the construction and recovery of anthropological sites. This urban culture is unique and specific to every society. Thepublic spaces, with their soundscape, are part of the construction of the urban identity of a city. It is shown that for identical general sound levels present in each of the spaces, the level of annoyance or discomfort, in relation to the subjective acoustic quality, is different. This is the result of the influence of semantic content of the sounds present in each urban space. Coinciding with other similar research, the level of discomfort or annoyance decreases as the presence of natural sounds such as water, the wind in the trees or the birds singing increases, even when the objective values of noise level of natural sounds are higher.

Integration of temporal and semantic components into the Geographic Information. Part II: Methodology

The overall objective of this research project is to enrich geographic data with temporal and semantic components in order to significantly improve spatio-temporal analysis of geographic phenomena. To achieve this goal, we intend to establish and incorporate three new layers (structures) into the core of the Geographic Information by using mark-up languages as well as defining a set of methods and tools for enriching the system to make it able to retrieve and exploit such layers (semantic-temporal, geosemantic, and incremental spatio-temporal). Besides these layers, we also propose a set of models (temporal and spatial) and two semantic engines that make the most of the enriched geographic data. The roots of the project and its definition have been previously presented in Siabato & Manso-Callejo 2011. In this new position paper, we extend such work by delineating clearly the methodology and the foundations on which we will base to define the main components of this research: the spatial model, the temporal model, the semantic layers, and the semantic engines. By putting together the former paper and this new work we try to present a comprehensive description of the whole process, from pinpointing the basic problem to describing and assessing the solution. In this new article we just mention the methods and the background to describe how we intend to define the components and integrate them into the GI.

Collaborative semantic editing of linked data lexica.

The creation of language resources is a time-consuming process requiring the efforts of many people. The use of resources collaboratively created by non-linguists can potentially ameliorate this situation. However, such resources often contain more errors compared to resources created by experts. For the particular case of lexica, we analyse the case of Wiktionary, a resource created along wiki principles and argue that through the use of a principled lexicon model, namely lemon, the resulting data could be better understandable to machines. We then present a platform called lemon source that supports the creation of linked lexical data along the lemon model. This tool builds on the concept of a semantic wiki to enable collaborative editing of the resources by many users concurrently. In this paper, we describe the model, the tool and present an evaluation of its usability based on a small group of users.

Methodology for developing a Speech into Sign Language Translation System in a New Semantic Domain

This paper proposes a methodology for developing a speech into sign language translation system considering a user-centered strategy. This method-ology consists of four main steps: analysis of technical and user requirements, data collection, technology adaptation to the new domain, and finally, evalua-tion of the system. The two most demanding tasks are the sign generation and the translation rules generation. Many other aspects can be updated automatical-ly from a parallel corpus that includes sentences (in Spanish and LSE: Lengua de Signos Española) related to the application domain. In this paper, we explain how to apply this methodology in order to develop two translation systems in two specific domains: bus transport information and hotel reception.

Semantic Interoperability: Perspectives and Technology Evaluation

Interoperability between semantic technologies is a must because they need to be in communication to interchange ontologies and use them in the distributed and open environment of the SemanticWeb. However, such interoperability is not straightforward due to the high heterogeneity in such technologies. This chapter describes the problem of semantic technology interoperability from two different perspectives. First, from a theoretical perspective by presenting an overview of the different factors that affect interoperability and, second, from a practical perspective by reusing evaluation methods and applying them to six current semantic technologies in order to assess their interoperability.

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application.

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

Implementation of a building automation system based on semantic modeling

This paper presents an Ontology-Based multi-technology platform designed to avoid some issues of Building Automation Systems. The platform allows the integration of several building automation protocols, eases the development and implementation of different kinds of services and allows sharing information related to the infrastructure and facilities within a building. The system has been implemented and tested in the Energy Efficiency Research Facility at CeDInt-UPM.

Semantic neology in the domain of videogames in Spanish

The aim of this paper is to discuss the meaning of five neologisms in the domain of videogames in Spanish: título, aventura, personaje, plataforma, and rol. Our study focuses on a special type of neologism since the Spanish terms we deal with here are not strictly new words; they are what have been called sense neologisms or neosemanticisms, that is, old words taking a new sense in a different domain. These words were identified as new concepts after a process of analysis based on contextual evidence. This study of neology is based on the analysis of a corpus of press articles evaluating videogames published by the Spanish newspaper El País from 1998 to 2008. The analysis of the instances of use of domain specific terms in the corpus revealed that they acquired new senses different to those they have in other domains where they are also used. The paper explains the process of discovering the specialized meaning these words have developed in the domain of videogames and how the analysis of collocational behavior helps in the process of discovering the new sense and in the design of the definition provided.

SMArc: a proposal for a smart, semantic middleware architecture focused on Smart City energy management

Among the main features that are intended to become part of what can be expected from the Smart City, one of them should be an improved energy management system, in order to benefit from a healthier relation with the environment, minimize energy expenses, and offer dynamic market opportunities. A Smart Grid seems like a very suitable infrastructure for this objective, as it guarantees a two-way information flow that will provide the means for energy management enhancement. However, to obtain all the required information, another entity must care about all the devices required to gather the data. What is more, this entity must consider the lifespan of the devices within the Smart Grid—when they are turned on and off or when new appliances are added—along with the services that devices are able to provide. This paper puts forward SMArc—an acronym for semantic middleware architecture—as a middleware proposal for the Smart Grid, so as to process the collected data and use it to insulate applications from the complexity of the metering facilities and guarantee that any change that may happen at these lower levels will be updated for future actions in the system.

A Semantic-Based Approach to Attain Reproducibility of Computational Environments in Scientic Work ows: A Case Study

Reproducible research in scientic work ows is often addressed by tracking the provenance of the produced results. While this approach allows inspecting intermediate and nal results, improves understanding, and permits replaying a work ow execution, it does not ensure that the computational environment is available for subsequent executions to reproduce the experiment. In this work, we propose describing the resources involved in the execution of an experiment using a set of semantic vocabularies, so as to conserve the computational environment. We dene a process for documenting the work ow application, management system, and their dependencies based on 4 domain ontologies. We then conduct an experimental evaluation sing a real work ow application on an academic and a public Cloud platform. Results show that our approach can reproduce an equivalent execution environment of a predened virtual machine image on both computing platforms.

Herramienta basada en vistas para la generación automática de anotaciones de fuentes RDF

Durante los últimos años, el imparable crecimiento de fuentes de datos biomédicas, propiciado por el desarrollo de técnicas de generación de datos masivos (principalmente en el campo de la genómica) y la expansión de tecnologías para la comunicación y compartición de información ha propiciado que la investigación biomédica haya pasado a basarse de forma casi exclusiva en el análisis distribuido de información y en la búsqueda de relaciones entre diferentes fuentes de datos. Esto resulta una tarea compleja debido a la heterogeneidad entre las fuentes de datos empleadas (ya sea por el uso de diferentes formatos, tecnologías, o modelizaciones de dominios). Existen trabajos que tienen como objetivo la homogeneización de estas con el fin de conseguir que la información se muestre de forma integrada, como si fuera una única base de datos. Sin embargo no existe ningún trabajo que automatice de forma completa este proceso de integración semántica. Existen dos enfoques principales para dar solución al problema de integración de fuentes heterogéneas de datos: Centralizado y Distribuido. Ambos enfoques requieren de una traducción de datos de un modelo a otro. Para realizar esta tarea se emplean formalizaciones de las relaciones semánticas entre los modelos subyacentes y el modelo central. Estas formalizaciones se denominan comúnmente anotaciones. Las anotaciones de bases de datos, en el contexto de la integración semántica de la información, consisten en definir relaciones entre términos de igual significado, para posibilitar la traducción automática de la información. Dependiendo del problema en el que se esté trabajando, estas relaciones serán entre conceptos individuales o entre conjuntos enteros de conceptos (vistas). El trabajo aquí expuesto se centra en estas últimas. El proyecto europeo p-medicine (FP7-ICT-2009-270089) se basa en el enfoque centralizado y hace uso de anotaciones basadas en vistas y cuyas bases de datos están modeladas en RDF. Los datos extraídos de las diferentes fuentes son traducidos e integrados en un Data Warehouse. Dentro de la plataforma de p-medicine, el Grupo de Informática Biomédica (GIB) de la Universidad Politécnica de Madrid, en el cuál realicé mi trabajo, proporciona una herramienta para la generación de las necesarias anotaciones de las bases de datos RDF. Esta herramienta, denominada Ontology Annotator ofrece la posibilidad de generar de manera manual anotaciones basadas en vistas. Sin embargo, aunque esta herramienta muestra las fuentes de datos a anotar de manera gráfica, la gran mayoría de usuarios encuentran difícil el manejo de la herramienta , y pierden demasiado tiempo en el proceso de anotación. Es por ello que surge la necesidad de desarrollar una herramienta más avanzada, que sea capaz de asistir al usuario en el proceso de anotar bases de datos en p-medicine. El objetivo es automatizar los procesos más complejos de la anotación y presentar de forma natural y entendible la información relativa a las anotaciones de bases de datos RDF. Esta herramienta ha sido denominada Ontology Annotator Assistant, y el trabajo aquí expuesto describe el proceso de diseño y desarrollo, así como algunos algoritmos innovadores que han sido creados por el autor del trabajo para su correcto funcionamiento. Esta herramienta ofrece funcionalidades no existentes previamente en ninguna otra herramienta del área de la anotación automática e integración semántica de bases de datos. ---ABSTRACT---Over the last years, the unstoppable growth of biomedical data sources, mainly thanks to the development of massive data generation techniques (specially in the genomics field) and the rise of the communication and information sharing technologies, lead to the fact that biomedical research has come to rely almost exclusively on the analysis of distributed information and in finding relationships between different data sources. This is a complex task due to the heterogeneity of the sources used (either by the use of different formats, technologies or domain modeling). There are some research proyects that aim homogenization of these sources in order to retrieve information in an integrated way, as if it were a single database. However there is still now work to automate completely this process of semantic integration. There are two main approaches with the purpouse of integrating heterogeneous data sources: Centralized and Distributed. Both approches involve making translation from one model to another. To perform this task there is a need of using formalization of the semantic relationships between the underlying models and the main model. These formalizations are also calles annotations. In the context of semantic integration of the information, data base annotations consist on defining relations between concepts or words with the same meaning, so the automatic translation can be performed. Depending on the task, the ralationships can be between individuals or between whole sets of concepts (views). This paper focuses on the latter. The European project p-medicine (FP7-ICT-2009-270089) is based on the centralized approach. It uses view based annotations and RDF modeled databases. The data retireved from different data sources is translated and joined into a Data Warehouse. Within the p-medicine platform, the Biomedical Informatics Group (GIB) of the Polytechnic University of Madrid, in which I worked, provides a software to create annotations for the RDF sources. This tool, called Ontology Annotator, is used to create annotations manually. However, although Ontology Annotator displays the data sources graphically, most of the users find it difficult to use this software, thus they spend too much time to complete the task. For this reason there is a need to develop a more advanced tool, which would be able to help the user in the task of annotating p-medicine databases. The aim is automating the most complex processes of the annotation and display the information clearly and easy understanding. This software is called Ontology Annotater Assistant and this book describes the process of design and development of it. as well as some innovative algorithms that were designed by the author of the work. This tool provides features that no other software in the field of automatic annotation can provide.