966 resultados para PDF,estrazione,Linked Open Data,dataset RDF
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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.
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In parallel to the effort of creating Open Linked Data for the World Wide Web there is a number of projects aimed for developing the same technologies but in the context of their usage in closed environments such as private enterprises. In the paper, we present results of research on interlinking structured data for use in Idea Management Systems - a still rare breed of knowledge management systems dedicated to innovation management. In our study, we show the process of extending an ontology that initially covers only the Idea Management System structure towards the concept of linking with distributed enterprise data and public data using Semantic Web technologies. Furthermore we point out how the established links can help to solve the key problems of contemporary Idea Management Systems
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In spite of the increasing presence of Semantic Web Facilities, only a limited amount of the available resources in the Internet provide a semantic access. Recent initiatives such as the emerging Linked Data Web are providing semantic access to available data by porting existing resources to the semantic web using different technologies, such as database-semantic mapping and scraping. Nevertheless, existing scraping solutions are based on ad-hoc solutions complemented with graphical interfaces for speeding up the scraper development. This article proposes a generic framework for web scraping based on semantic technologies. This framework is structured in three levels: scraping services, semantic scraping model and syntactic scraping. The first level provides an interface to generic applications or intelligent agents for gathering information from the web at a high level. The second level defines a semantic RDF model of the scraping process, in order to provide a declarative approach to the scraping task. Finally, the third level provides an implementation of the RDF scraping model for specific technologies. The work has been validated in a scenario that illustrates its application to mashup technologies
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Linked data offers a promising setting to encode, publish and share metadata of resources. As the matter of fact, it is already adopted by data producers such as European Environment Agency, US and some EU Governs, whose first ambition is to share (meta)data making their processes more effective and transparent. Such as an increasing interest and involvement of data providers surely represents a genuine witness of the web of data success, but in a longer perspective, frameworks supporting linked data consumers in their decision making processes will be a compelling need. In this respect, the talk is introducing SSONDE, a framework enabling in detailed comparison, ranking and selection of linked data resources through the analysis of their RDF ontology driven metadata. SSONDE implements an instance similarity especially designed to support in resource selection, namely the process stakeholders engage to choose a set of resources suitable for a given analysis purpose: (i) it deploys an asymmetric similarity assessment to emphasize information about gains and losses the stakeholders get adopting a resource in place of another; (ii) it relies on an explicit formalization of contexts to tailor the similarity assessment with respect to specific user-defined selection goals. The talk aims at providing an insight on SSONDE instance similarity and it will briefly describe some examples of SSONDE deployment in the context of linked data consumption.
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This paper describes the process followed in order to make some of the public meterological data from the Agencia Estatal de Meteorología (AEMET, Spanish Meteorological Office) available as Linked Data. The method followed has been already used to publish geographical, statistical, and leisure data. The data selected for publication are generated every ten minutes by the 250 automatic stations that belong to AEMET and that are deployed across Spain. These data are available as spreadsheets in the AEMET data catalog, and contain more than twenty types of measurements per station. Spreadsheets are retrieved from the website, processed with Python scripts, transformed to RDF according to an ontology network about meteorology that reuses the W3C SSN Ontology, published in a triple store and visualized in maps with Map4rdf.
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The use of semantic and Linked Data technologies for Enterprise Application Integration (EAI) is increasing in recent years. Linked Data and Semantic Web technologies such as the Resource Description Framework (RDF) data model provide several key advantages over the current de-facto Web Service and XML based integration approaches. The flexibility provided by representing the data in a more versatile RDF model using ontologies enables avoiding complex schema transformations and makes data more accessible using Web standards, preventing the formation of data silos. These three benefits represent an edge for Linked Data-based EAI. However, work still has to be performed so that these technologies can cope with the particularities of the EAI scenarios in different terms, such as data control, ownership, consistency, or accuracy. The first part of the paper provides an introduction to Enterprise Application Integration using Linked Data and the requirements imposed by EAI to Linked Data technologies focusing on one of the problems that arise in this scenario, the coreference problem, and presents a coreference service that supports the use of Linked Data in EAI systems. The proposed solution introduces the use of a context that aggregates a set of related identities and mappings from the identities to different resources that reside in distinct applications and provide different views or aspects of the same entity. A detailed architecture of the Coreference Service is presented explaining how it can be used to manage the contexts, identities, resources, and applications which they relate to. The paper shows how the proposed service can be utilized in an EAI scenario using an example involving a dashboard that integrates data from different systems and the proposed workflow for registering and resolving identities. As most enterprise applications are driven by business processes and involve legacy data, the proposed approach can be easily incorporated into enterprise applications.
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In this paper we describe the specification of amodel for the semantically interoperable representation of language resources for sentiment analysis. The model integrates "lemon", an RDF-based model for the specification of ontology-lexica (Buitelaar et al. 2009), which is used increasinglyfor the representation of language resources asLinked Data, with Marl, an RDF-based model for the representation of sentiment annotations (West-erski et al., 2011; Sánchez-Rada et al., 2013)
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Enterprises are increasingly using a wide range of heterogeneous information systems for executing and governing their business activities. Even if the adoption of service orientation has improved loose coupling and reusability, applications are still isolated data silos whose integration requires complex transformations and mediations. However, by leveraging Linked Data principles those data silos can now be seamlessly integrated, and this opens the door to new data-driven approaches for Enterprise Application Integration (EAI). In this paper we present LDP4j, an open souce Java-based framework for the development of interoperable read-write Linked Data applications, based on the W3C Linked Data Platform (LDP) specification.
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The W3C Linked Data Platform (LDP) candidate recom- mendation defines a standard HTTP-based protocol for read/write Linked Data. The W3C R2RML recommendation defines a language to map re- lational databases (RDBs) and RDF. This paper presents morph-LDP, a novel system that combines these two W3C standardization initiatives to expose relational data as read/write Linked Data for LDP-aware ap- plications, whilst allowing legacy applications to continue using their relational databases.
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Extracting opinions and emotions from text is becoming increasingly important, especially since the advent of micro-blogging and social networking. Opinion mining is particularly popular and now gathers many public services, datasets and lexical resources. Unfortunately, there are few available lexical and semantic resources for emotion recognition that could foster the development of new emotion aware services and applications. The diversity of theories of emotion and the absence of a common vocabulary are two of the main barriers to the development of such resources. This situation motivated the creation of Onyx, a semantic vocabulary of emotions with a focus on lexical resources and emotion analysis services. It follows a linguistic Linked Data approach, it is aligned with the Provenance Ontology, and it has been integrated with the Lexicon Model for Ontologies (lemon), a popular RDF model for representing lexical entries. This approach also means a new and interesting way to work with different theories of emotion. As part of this work, Onyx has been aligned with EmotionML and WordNet-Affect.
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We present El Viajero, an application for exploiting, managing and organizing Linked Data in the domain of news and blogs about travelling. El Viajero makes use of several heterogeneous datasets to help users to plan future trips, and relies on the Open Provenance Model for modeling the provenance information of the resources
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Dissertation presented to obtain the Ph.D degree in Bioinformatics
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Report for the scientific sojourn at the Simon Fraser University, Canada, from July to September 2007. General context: landscape change during the last years is having significant impacts on biodiversity in many Mediterranean areas. Land abandonment, urbanisation and specially fire are profoundly transforming large areas in the Western Mediterranean basin and we know little on how these changes influence species distribution and in particular how these species will respond to further change in a context of global change including climate. General objectives: integrate landscape and population dynamics models in a platform allowing capturing species distribution responses to landscape changes and assessing impact on species distribution of different scenarios of further change. Specific objective 1: develop a landscape dynamic model capturing fire and forest succession dynamics in Catalonia and linked to a stochastic landscape occupancy (SLOM) (or spatially explicit population, SEPM) model for the Ortolan bunting, a species strongly linked to fire related habitat in the region. Predictions from the occupancy or spatially explicit population Ortolan bunting model (SEPM) should be evaluated using data from the DINDIS database. This database tracks bird colonisation of recently burnt big areas (&50 ha). Through a number of different SEPM scenarios with different values for a number of parameter, we should be able to assess different hypothesis in factors driving bird colonisation in new burnt patches. These factors to be mainly, landscape context (i.e. difficulty to reach the patch, and potential presence of coloniser sources), dispersal constraints, type of regenerating vegetation after fire, and species characteristics (niche breadth, etc).
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The remit of the Institute of Public Health in Ireland (IPH) is to promote cooperation for public health between Northern Ireland and the Republic of Ireland in the areas of research and information, capacity building and policy advice. Our approach is to support Departments of Health and their agencies in both jurisdictions, and maximise the benefits of all-island cooperation to achieve practical benefits for people in Northern Ireland and the Republic of Ireland. IPH have previously responded to consultations to the Department of Health’s Discussion Paper on the Proposed Health Information Bill (June 2008), the Health Information and Quality Authority on their Corporate Plan (Oct 2007), and the Road Safety Authority of Ireland Road Safety Strategy (Jul 2012). IPH supports the development of a national standard demographic dataset for use within the health and social care services. Provided necessary safeguards are put in place (such as ethics and data protection) and the purpose of collecting the information is fully explained to subjects, mandatory provision of a minimum demographic dataset is usually the best way to achieve the necessary coverage and data quality. Demographic information is needed in several forms to support the public health function: Detailed aggregated information for comparison to population counts in order to assess equity of access to healthcare as well as examining population patterns and trends in morbidity and mortality Accurate demographic information for the surveillance of infectious disease outbreaks, monitoring vaccination programmes, setting priorities for public health interventions Linked to other data outside of health and social care such as population data, survey data, and longitudinal studies for research and analysis purposes. Identify and address public health issues to tackle health inequalities, and to monitor the success of such efforts to tackle them.
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Working conditions are important determinants of health. The aims of this article are to 1) identify working conditions and work characteristics that are associated with workers' perceptions that their work is harmful to their health and 2) identify with what symptoms these working conditions are associated.We used the Swiss dataset from the 2005 edition of the European Working Conditions Survey. The dependent variable was based on the question "Does your work affect your health?". Logistic regression was used to identify a set of variables collectively associated with self-reported work-related adverse health effects.A total of 330 (32%) participants reported having their health affected by work. The most frequent symptoms included backache (17.1%), muscular pains (13.1%), stress (18.3%) and overall fatigue (11.7%). Scores for self-reported exposure to physicochemical risks, postural and physical risks, high work demand, and low social support were all significantly associated with workers' perceptions that their work is harmful to their health, regardless of gender or age. A high level of education was associated with stress symptoms, and reports that health was affected by work was associated with low job satisfaction.Many workers believe that their work affects their health. Health specialists should pay attention to the potential association between work and their patients' health complaints. This is particularly relevant when patients mention symptoms such as muscular pains, backache, overall fatigue, and stress. Specific attention should be given to complaints of stress in highly educated workers.