Objetivo The SMARTER (A Scalable and Elastic Platform for Near-Realtime Analytics for The Graph of EveryThing) project aims to build a platform that provide the ability to derive actionable information from enormous amount of data generated by the Internet of Everything to leverage data-driven strategies to innovate, compete, and capture value from deep web and real-time information. The project targets innovative research outcomes by addressing Big Dynamic Data Analytic requirements from three relevant aspects: variety and velocity and volume. The project introduces the concept, “Graph of Everything” (GoT), to deal with the issue of data variety in data analytics for Internet of Things (IoT) data. The Graph of Everything extends Linked Data model (RDF ), that has been widely used for representing deep web data, to connect dynamic data from data streams generated from IoT, e.g. sensor readings, with any knowledgebase to create a single graph as an integrated database serving any analytical queries on a set of nodes/edges of the graph, so called, analytical lens of everything. The dynamic data represented as Linked Data Model, called Linked Stream Data, may contain valuable, but perishable insights which are only valuable if it can be detected to act on them right at the right time. Moreover, to derive such insights, the dynamic data needs to be correlated with various large datasets. Therefore, SMARTER has to deal both the velocity requirements together volume requirements of analysing GoT to make the platform able support near-realtime analytical operations with the elastically scalability. Ámbito científico natural sciencescomputer and information sciencesinternetinternet of thingsnatural sciencescomputer and information sciencesdata sciencebig datanatural sciencescomputer and information sciencesartificial intelligencemachine learningnatural sciencescomputer and information sciencesdata sciencedata processingnatural sciencescomputer and information sciencesdatabasesrelational databases Palabras clave Data analytics Internet of Things Linked Data Programa(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Tema(s) MSCA-IF-2014-EF - Marie Skłodowska-Curie Individual Fellowships (IF-EF) Convocatoria de propuestas H2020-MSCA-IF-2014 Consulte otros proyectos de esta convocatoria Régimen de financiación MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinador TECHNISCHE UNIVERSITAT BERLIN Aportación neta de la UEn € 171 460,80 Dirección STRASSE DES 17 JUNI 135 10623 Berlin Alemania Ver en el mapa Región Berlin Berlin Berlin Tipo de actividad Higher or Secondary Education Establishments Enlaces Contactar con la organización Opens in new window Sitio web Opens in new window Participación en los programas de I+D de la UE Opens in new window Red de colaboración de HORIZON Opens in new window Coste total € 171 460,80 Participantes (1) Ordenar alfabéticamente Ordenar por aportación neta de la UE Ampliar todo Contraer todo FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANGEWANDTEN FORSCHUNG EV La participación finalizó Alemania Aportación neta de la UEn € 0,00 Dirección HANSASTRASSE 27C 80686 Munchen Ver en el mapa Región Bayern Oberbayern München, Kreisfreie Stadt Tipo de actividad Research Organisations Enlaces Contactar con la organización Opens in new window Sitio web Opens in new window Participación en los programas de I+D de la UE Opens in new window Red de colaboración de HORIZON Opens in new window Coste total Sin datos
