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Improving data identification and tagging for more effective decision making in agriculture

Code: 9781786767264
Pascal Neveu and Romain David, MISTEA, INRAE, Montpellier SupAgro, University of Montpellier, France; and Clement Jonquet, LIRMM, CNRS and University of Montpellier, France

Chapter synopsis: Data integration, data analytics and decision support methods can help to rise agriculture challenges such as climate change adaptation or food security. In this context, smart data acquisition systems, interoperable Information Systems and frameworks for data structuring are required. In this chapter we describe methods for data identification and we provide some recommendations. We also describles how to enrich data with semantics and a way to tags data with relevant ontology. We illustrate proposed approach in a use case of high throughput plant phenotyping.

DOI: 10.19103/AS.2020.0069.04
Table of contents 1 Introduction 2 Structuring the data 3 Case study: plant phenotyping 4 Conclusion and future trends 5 Where to look for further information 6 Acknowledgements 7 References

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