Analysis of Big Data technologies for use in agro-environmental science
| Autor: | Sander Janssen, Rob Knapen, Yke van Randen, Jacques Jansen, Rob Lokers |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Big Data
Earth Observation and Environmental Informatics Environmental Engineering Computer science Big data Cloud computing 010501 environmental sciences Interdisciplinary research computer.software_genre 01 natural sciences Domain (software engineering) Environmental Science(all) Aardobservatie en omgevingsinformatica 0105 earth and related environmental sciences Structure (mathematical logic) business.industry Ecological Modeling Frame (networking) Agriculture Forestry 04 agricultural and veterinary sciences Data science Semantics Variety (cybernetics) Ecological Modelling Open data 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Data integration business computer Software |
| Zdroj: | Environmental Modelling & Software 84 (2016) Environmental Modelling & Software, 84, 494-504 |
| ISSN: | 1364-8152 |
| DOI: | 10.1016/j.envsoft.2016.07.017 |
| Popis: | Recent developments like the movements of open access and open data and the unprecedented growth of data, which has come forward as Big Data, have shifted focus to methods to effectively handle such data for use in agro-environmental research. Big Data technologies, together with the increased use of cloud based and high performance computing, create new opportunities for data intensive science in the multi-disciplinary agro-environmental domain. A theoretical framework is presented to structure and analyse data-intensive cases and is applied to three case studies, together covering a broad range of technologies and aspects related to Big Data usage. The case studies indicate that most persistent issues in the area of data-intensive research evolve around capturing the huge heterogeneity of interdisciplinary data and around creating trust between data providers and data users. It is therefore recommended that efforts from the agro-environmental domain concentrate on the issues of variety and veracity. A theoretical framework is presented to frame and analyse Big Data use cases.Three case studies related to agro-environmental modelling, covering the range of Big Data characteristics are analysed.Most persistent issues in agro-environmental science concern variety and veracity.Approaches to deal with variety and veracity issues are presented. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect