982 resultados para research data management


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The CERTS database is now online! Our efforts bear finally fruit! It is possible to visit our database on the web now in French, in English and in about ten European languages in the forthcoming months. Your turn! Connect you to the following address: www.certs-europe.com/database

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Data management and sharing are relatively new concepts in the health and life sciences fields. This presentation will cover some basic policies as well as the impediments to data sharing unique to health and life sciences data.

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These Data Management Plans are more comprehensive and complex than in the past. Libraries around the nation are trying to put together tools to help researchers write plans that conform to the new requirements. This session will look at some of these tools.

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Work on distributed data management commenced shortly after the introduction of the relational model in the mid-1970's. 1970's and 1980's were very active periods for the development of distributed relational database technology, and claims were made that in the following ten years centralized databases will be an “antique curiosity” and most organizations will move toward distributed database managers [1]. That prediction has certainly become true, and all commercial DBMSs today are distributed.

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The manipulation and handling of an ever increasing volume of data by current data-intensive applications require novel techniques for e?cient data management. Despite recent advances in every aspect of data management (storage, access, querying, analysis, mining), future applications are expected to scale to even higher degrees, not only in terms of volumes of data handled but also in terms of users and resources, often making use of multiple, pre-existing autonomous, distributed or heterogeneous resources.

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The electrical power distribution and commercialization scenario is evolving worldwide, and electricity companies, faced with the challenge of new information requirements, are demanding IT solutions to deal with the smart monitoring of power networks. Two main challenges arise from data management and smart monitoring of power networks: real-time data acquisition and big data processing over short time periods. We present a solution in the form of a system architecture that conveys real time issues and has the capacity for big data management.

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In this paper we approximate to the understanding of the hybrid city as a context of changes, produced in the perception and in the modes of inhabiting and coexisting in cities through new technologies of information and communication.

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© The Author(s) 2014. Acknowledgements We thank the Information Services Division, Scotland, who provided the SMR01 data, and NHS Grampian, who provided the biochemistry data. We also thank the University of Aberdeen’s Data Management Team. Funding This work was supported by the Chief Scientists Office for Scotland (grant no. CZH/4/656).

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Il lavoro svolto si concentra sullo studio e lo sviluppo dei sistemi software per la gestione dei big data. Inizialmente sono stati analizzati i settori nei quali i big data si stanno diffondendo maggiormente per poi studiare l'ingegnerizzazione e lo sviluppo dei sistemi in grado di gestire questo tipo di dati. Sono state studiate tutte le fasi del processo di realizzazione del software e i rischi e i problemi che si possono incontrare. Infine è stato presentato un software di analisi di big data: Google BigQuery.

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Includes bibliographical references.

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Thesis (M.S.)--University of Illinois at Urbana-Champaign.