Explore the words cloud of the BigDataGrapes project. It provides you a very rough idea of what is the project "BigDataGrapes" about.
The following table provides information about the project.
|Coordinator Country||Greece [EL]|
|Total cost||4˙441˙500 €|
|EC max contribution||4˙441˙500 € (100%)|
1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
|Duration (year-month-day)||from 2018-01-01 to 2020-12-31|
Take a look of project's partnership.
|1||AGROKNOW IKE||EL (MAROUSI)||coordinator||936˙250.00|
|2||CONSIGLIO NAZIONALE DELLE RICERCHE||IT (ROMA)||participant||620˙000.00|
|3||ONTOTEXT AD||BG (SOFIA)||participant||545˙625.00|
|4||INSTITUT NATIONAL DE RECHERCHE POUR L'AGRICULTURE, L'ALIMENTATION ET L'ENVIRONNEMENT||FR (PARIS CEDEX 07)||participant||540˙250.00|
|5||GEOPONIKO PANEPISTIMION ATHINON||EL (ATHINA)||participant||528˙125.00|
|6||KATHOLIEKE UNIVERSITEIT LEUVEN||BE (LEUVEN)||participant||443˙125.00|
|7||ABACO SPA||IT (MANTOVA)||participant||316˙250.00|
|8||GEOCLEDIAN GMBH||DE (LANDSHUT)||participant||315˙000.00|
|9||SYMBEEOSIS LONG LIVE LIFE SA||EL (PAIANIA)||participant||196˙875.00|
Big data is becoming a hype that is going to completely redefine industries within very traditional sectors like agriculture, food and beauty. The emergence of niche big data companies like Enolytics (“bringing big data insights to the wine industry”) is threatening to disrupt these industries against the interests of the EU. BigDataGrapes wants to build upon the rich historical, cultural and artisan heritage of Europe in order to change this picture. It aims to support all European companies active in two key industries powered by grapevines: the wine industry and the natural cosmetics one. It will help them respond to the significant opportunity that big data is creating in their relevant markets, by pursuing two ambitious goals: a. To develop and demonstrate powerful, rigorously tested, cross-sector data processing technologies that go beyond-the-state-of-the-art towards increasing the efficiency of companies that need to take important business decisions dependent on access to vast and complex amounts of data, and assess them in challenges informed by the grapevine-powered industries. b. To create a large-scale, mulifaceted marketplace for grapevine-related data assets, increasing the competitive advantage of companies that serve with IT solutions these sectors and helping companies and organisations evolve methods, standards and processes to help them achieve free, interoperable and secure flow of their data. BigDataGrapes is targeting technology challenges of the grapevine-powered data economy as its business problems and decisions requires processing, analysis and visualisation of data with rapidly increasing volume, velocity and variety: satellite and weather data, environmental and geological data, phenotypic and genetic plant data, food supply chain data, economic and financial data and more. It therefore makes a perfectly suitable cross-sector and cross-country combination of industries that are of high European significance and value.
|Interactive Visualization Components||Demonstrators, pilots, prototypes||2020-04-24 05:05:00|
|Integrated Software Stack and APIs||Demonstrators, pilots, prototypes||2020-04-24 05:05:00|
|Dissemination and Awareness Report||Documents, reports||2020-04-24 05:05:00|
|Website and Social Media Presence||Websites, patent fillings, videos etc.||2020-04-24 05:05:00|
|Data Management Plan & Support Pack||Documents, reports||2020-04-24 05:05:00|
Take a look to the deliverables list in detail: detailed list of BigDataGrapes deliverables.
|year||authors and title||journal||last update|
Ermanno Pibiri, Giulio; Venturini, Rossano
Handling Massive N-Gram Datasets Efficiently
published pages: , ISSN: 1046-8188, DOI: 10.5281/zenodo.3257995
|ACM Transactions on Information Systems 25||2020-04-24|
GutiÃ©rrez, Francisco; Htun, Nyi-Nyi; Schlenz, Florian; Kasimati, Aikaterini; Verbert, Katrien
A Review of Visualisations in Agricultural Decision Support Systems: an HCI Perspective
published pages: , ISSN: 0168-1699, DOI: 10.5281/zenodo.3267196
|Computers and Electronics in Agriculture 15||2020-04-24|
GutiÃ©rrez, Francisco; Verbert, Katrien; Seipp, Karsten; Ochoa, Xavier
Towards a visual guide for communicating uncertainty in Visual Analyticsâ˜†
published pages: , ISSN: 2590-1184, DOI: 10.5281/zenodo.3258001
|Journal of Computer Languages 19||2020-04-24|
Tonellotto, Nicola; Macdonald, Craig; Ounis, Iadh
Efficient Query Processing for Scalable Web Search
published pages: 319-500, ISSN: 1554-0677, DOI: 10.5281/zenodo.3268359
|Foundations and TrendsÂ® in Information Retrieval 37||2020-04-24|
Lucchese, Claudio; Nardini, Franco Maria; Orlando, Salvatore; Perego, Raffaele; Silvestri, Fabrizio; Trani, Salvatore
X-CLEaVER: Learning Ranking Ensembles by Growing and Pruning Trees
published pages: , ISSN: 2157-6904, DOI: 10.5281/zenodo.2668361
|ACM Transactions on Intelligent Systems and Technology (TIST) 8||2020-04-24|
Francesco Lettich, Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini
Parallel Traversal of Large Ensembles of Decision Trees
published pages: 1-1, ISSN: 1045-9219, DOI: 10.1109/tpds.2018.2860982
|IEEE Transactions on Parallel and Distributed Systems||2020-04-24|
Are you the coordinator (or a participant) of this project? Plaese send me more information about the "BIGDATAGRAPES" project.
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The information about "BIGDATAGRAPES" are provided by the European Opendata Portal: CORDIS opendata.
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