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Combining semantic web and modelling to organise phenotypic data acquired at different scales of plant organisation

Abstract

Recent developments in the field of plant phenomena have allowed the acquisition of massive amounts of valuable data in different contexts (e.g. fields vs. controlled platforms) and different scales of organisation (e.g. organ, plant, canopy). The re-use and re-analysis of these data is confronted with problems related to the multi-origin and multi-scale characteristics of the data and the difficulty of developing information systems capable of organising this mass of information. In this context, we hypothesise that the use of equations from modelling can improve alignment processes to link concepts and variables at different scales of organisation. The main objective of this thesis will be to combine culture modelling and semantic web techniques to facilitate the alignment of these concepts. This will allow the development of a conceptual framework to facilitate the organisation of data sets acquired in field conditions and in phenotyping platforms and to link concepts at different scales of organisation while creating dynamic links. Finally, we hope that the conceptual framework developed during this thesis will facilitate the assembly of future datasets allowing their reuse and re-analysis in order to generate new knowledge.