Big Data in Agricultural and Food Research : Challenges and Opportunities of an Integrated Big Data E-infrastructure
| Autor: | Nikos Manouselis, Panagiotis Zervas, Matthias Filter, George Kakaletris, Rob Lokers, Leonardo Candela, Pascal Neveu, Maritina Stavrakaki, Pythagoras Karampiperis, Odile Hologne |
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| Přispěvatelé: | Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), DIST Délégation Information Scientifique et Technique (DV-IST), Institut National de la Recherche Agronomique (INRA), Greek Research and Technology Network, Centre for Research & Technology Hellas (CERTH), Agroknow [Athens], Wageningen Environmental Research, Wageningen University and Research [Wageningen] (WUR), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), National and Kapodistrian University of Athens (NKUA), Pisa Research Area - National Research Council [Pise] (Italian National Research Council ) (CNR - Pisa), Bundesinstitut für Risikobewertung - Federal Institute for Risk Assessment (BfR), Emrouznejad Ali, Charles Vincent, Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences Earth Observation and Environmental Informatics Computer science media_common.quotation_subject Big data Context (language use) Food safety risk assessment 01 natural sciences Food safety Presentation Aardobservatie en omgevingsinformatica e-infrastructure agro-climatic economic modelling food security plant phenotyping food safety risk assessment [INFO]Computer Science [cs] Virtual Research Environment media_common Risk assessment 2. Zero hunger Food security business.industry 04 agricultural and veterinary sciences 15. Life on land Data science Agriculture Analytics Scalability 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Agro-climatic E-infrastructure Economic modelling business Plant phenotyping Agro-climatic Modelling 010606 plant biology & botany |
| Zdroj: | Big Data for the Greater Good. Springer Big Data for the Greater Good Big Data for the Greater Good, pp.129-150, 2019, ⟨10.1007/978-3-319-93061-9_6⟩ Emrouznejad Ali; Charles Vincent. Big Data for the Greater Good, 42, Springer, Cham, 204 p., 2019, Studies in Big Data, 978-3-319-93060-2. ⟨10.1007/978-3-319-93061-9_6⟩ Big Data for the Greater Good. Studies in Big Data Studies in Big Data ISBN: 9783319930602 ZENODO Big Data for the Greater Good, edited by Ali Emrouznejad, Vincent Charles, pp. 129–150, 2018 info:cnr-pdr/source/autori:Karampiperis P; Lokers B.; Neveu P.; Hologne O.; Kakaletris G.; Candela L.; Filter M.; Manouselis N.; Stavrakaki M.; Zervas P./titolo:Big data in agricultural and food research: challenges and opportunities of an integrated big data e-infrastructure/titolo_volume:Big Data for the Greater Good/curatori_volume:Ali Emrouznejad, Vincent Charles/editore:/anno:2018 |
| Popis: | Agricultural and food research are increasingly becoming fields where data acquisition, processing, and analytics play a major role in the provision and application of novel methods in the general context of agri-food practices. The chapter focuses on the presentation of an innovative, holistic e-infrastructure solution that aims to enable researches for distinct but interconnected domains to share data, algorithms and results in a scalable and efficient fashion. It furthermore discusses on the potentially significant impact that such infrastructures can have on agriculture and food management and policy making, by applying the proposed solution in variegating agri-food related domains. |
| Databáze: | OpenAIRE |
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