913 resultados para Open Research Data


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In 2008, the 50th anniversary of the IGY (International Geophysical Year), WDCMARE presents with this CD publication 3632 data sets in Open Access as part of the most important results from 73 cruises of the research vessel METEOR between 1964 and 1985. The archive is a coherent organized collection of published and unpublished data sets produced by scientists of all marine research disciplines who participated in Meteor expeditions, measured environmental parameters during cruises and investigated sample material post cruise in the labs of the participating institutions. In most cases, the data was gathered from the Meteor Forschungsergebnisse, published by the Deutsche Forschungsgemeinschaft (DFG). A second important data source are time series and radiosonde ascensions of more than 20 years of ships weather observations, which were provided by the Deutscher Wetterdienst, Hamburg. The final inclusion of all data into the PANGAEA information system ensures secure archiving, future updates, widespread distribution in electronic, machine-readable form with longterm access via the Internet. To produce this publication, all data sets with metadata were extracted from PANGAEA and organized in a directory structure on a CD together with a search capability.

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The Linked Data initiative offers a straight method to publish structured data in the World Wide Web and link it to other data, resulting in a world wide network of semantically codified data known as the Linked Open Data cloud. The size of the Linked Open Data cloud, i.e. the amount of data published using Linked Data principles, is growing exponentially, including life sciences data. However, key information for biological research is still missing in the Linked Open Data cloud. For example, the relation between orthologs genes and genetic diseases is absent, even though such information can be used for hypothesis generation regarding human diseases. The OGOLOD system, an extension of the OGO Knowledge Base, publishes orthologs/diseases information using Linked Data. This gives the scientists the ability to query the structured information in connection with other Linked Data and to discover new information related to orthologs and human diseases in the cloud.

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La web ha sufrido una drástica transformación en los últimos años, debido principalmente a su popularización y a la enorme cantidad de información que alberga. Debido a estos factores se ha dado el salto de la denominada Web de Documentos, a la Web Semántica, donde toda la información está relacionada con otra. Las principales ventajas de la información enlazada estriban en la facilidad de reutilización, accesibilidad y disponibilidad para ser encontrada por el usuario. En este trabajo se pretende poner de manifiesto la utilidad de los datos enlazados aplicados al ámbito geográfico y mostrar como pueden ser empleados hoy en día. Para ello se han explotado datos enlazados de carácter espacial provenientes de diferentes fuentes, a través de servidores externos o endpoints SPARQL. Además de eso se ha trabajado con un servidor privado capaz de proporcionar información enlazada almacenada en un equipo personal. La explotación de información enlazada se ha implementado en una aplicación web en lenguaje JavaScript, tratando de abstraer totalmente al usuario del tratamiento de los datos a nivel interno de la aplicación. Esta aplicación cuenta además con algunos módulos y opciones capaces de interactuar con las consultas realizadas a los servidores, consiguiendo un entorno más intuitivo y agradable para el usuario. ABSTRACT: In recent years the web has suffered a drastic transformation because of the popularization and the huge amount of stored information. Due to these factors it has gone from Documents web to Semantic web, where the data are linked. The main advantages of Linked Data lie in the ease of his reuse, accessibility and availability to be located by users. The aim of this research is to highlight the usefulness of the geographic linked data and show how can be used at present time. To get this, the spatial linked data coming from several sources have been managed through external servers or also called endpoints. Besides, it has been worked with a private server able to provide linked data stored in a personal computer. The use of linked data has been implemented in a JavaScript web application, trying completely to abstract the internally data treatment of the application to make the user ignore it. This application has some modules and options that are able to interact with the queries made to the servers, getting a more intuitive and kind environment for users.

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Carbon (C) and nitrogen (N) process-based models are important tools for estimating and reporting greenhouse gas emissions and changes in soil C stocks. There is a need for continuous evaluation, development and adaptation of these models to improve scientific understanding, national inventories and assessment of mitigation options across the world. To date, much of the information needed to describe different processes like transpiration, photosynthesis, plant growth and maintenance, above and below ground carbon dynamics, decomposition and nitrogen mineralization. In ecosystem models remains inaccessible to the wider community, being stored within model computer source code, or held internally by modelling teams. Here we describe the Global Research Alliance Modelling Platform (GRAMP), a web-based modelling platform to link researchers with appropriate datasets, models and training material. It will provide access to model source code and an interactive platform for researchers to form a consensus on existing methods, and to synthesize new ideas, which will help to advance progress in this area. The platform will eventually support a variety of models, but to trial the platform and test the architecture and functionality, it was piloted with variants of the DNDC model. The intention is to form a worldwide collaborative network (a virtual laboratory) via an interactive website with access to models and best practice guidelines; appropriate datasets for testing, calibrating and evaluating models; on-line tutorials and links to modelling and data provider research groups, and their associated publications. A graphical user interface has been designed to view the model development tree and access all of the above functions.

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The paper presents in brief the “2nd Generation Open Access Infrastructure for Research in Europe” project (http://www.openaire.eu/) and what is done in Bulgaria during the last year in the area of open access to scientific information and data.

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This work was supported in part by the EU „2nd Generation Open Access Infrastructure for Research in Europe" (OpenAIRE+). The autumn training school Development and Promotion of Open Access to Scientific Information and Research is organized in the frame of the Fourth International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage—DiPP2014 (September 18–21, 2014, Veliko Tarnovo, Bulgaria, http://dipp2014.math.bas.bg/), organized under the UNESCO patronage. The main organiser is the Institute of Mathematics and Informatics, Bulgarian Academy of Sciences with the support of EU project FOSTER (http://www.fosteropenscience.eu/) and the P. R. Slaveykov Regional Public Library in Veliko Tarnovo, Bulgaria.

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Permanent water bodies not only store dissolved CO2 but are essential for the maintenance of wetlands in their proximity. From the viewpoint of greenhouse gas (GHG) accounting wetland functions comprise sequestration of carbon under anaerobic conditions and methane release. The investigated area in central Siberia covers boreal and sub-arctic environments. Small inundated basins are abundant on the sub-arctic Taymir lowlands but also in parts of severe boreal climate where permafrost ice content is high and feature important freshwater ecosystems. Satellite radar imagery (ENVISAT ScanSAR), acquired in summer 2003 and 2004, has been used to derive open water surfaces with 150 m resolution, covering an area of approximately 3 Mkm**2. The open water surface maps were derived using a simple threshold-based classification method. The results were assessed with Russian forest inventory data, which includes detailed information about water bodies. The resulting classification has been further used to estimate the extent of tundra wetlands and to determine their importance for methane emissions. Tundra wetlands cover 7% (400,000 km**2) of the study region and methane emissions from hydromorphic soils are estimated to be 45,000 t/d for the Taymir peninsula.

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Smart cities, cities that are supported by an extensive digital infrastructure of sensors, databases and intelligent applications, have become a major area of academic, governmental and public interest. Simultaneously, there has been a growing interest in open data, the unrestricted use of organizational data for public viewing and use. Drawing on Science and Technology Studies (STS), Urban Studies and Political Economy, this thesis examines how digital processes, open data and the physical world can be combined in smart city development, through the qualitative interview-based case study of a Southern Ontario Municipality, Anytown. The thesis asks what are the challenges associated with smart city development and open data proliferation, is open data complimentary to smart urban development; and how is expertise constructed in these fields? The thesis concludes that smart city development in Anytown is a complex process, involving a variety of visions, programs and components. Although smart city and open data initiatives exist in Anytown, and some are even overlapping and complementary, smart city development is in its infancy. However, expert informants remained optimistic, faithful to a technologically sublime vision of what a smart city would bring. The thesis also questions the notion of expertise within the context of smart city and open data projects, concluding that assertions of expertise need to be treated with caution and scepticism when considering how knowledge is received, generated, interpreted and circulates, within organizations.

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Abstract: Decision support systems have been widely used for years in companies to gain insights from internal data, thus making successful decisions. Lately, thanks to the increasing availability of open data, these systems are also integrating open data to enrich decision making process with external data. On the other hand, within an open-data scenario, decision support systems can be also useful to decide which data should be opened, not only by considering technical or legal constraints, but other requirements, such as "reusing potential" of data. In this talk, we focus on both issues: (i) open data for decision making, and (ii) decision making for opening data. We will first briefly comment some research problems regarding using open data for decision making. Then, we will give an outline of a novel decision-making approach (based on how open data is being actually used in open-source projects hosted in Github) for supporting open data publication. Bio of the speaker: Jose-Norberto Mazón holds a PhD from the University of Alicante (Spain). He is head of the "Cátedra Telefónica" on Big Data and coordinator of the Computing degree at the University of Alicante. He is also member of the WaKe research group at the University of Alicante. His research work focuses on open data management, data integration and business intelligence within "big data" scenarios, and their application to the tourism domain (smart tourism destinations). He has published his research in international journals, such as Decision Support Systems, Information Sciences, Data & Knowledge Engineering or ACM Transaction on the Web. Finally, he is involved in the open data project in the University of Alicante, including its open data portal at http://datos.ua.es