Introduction Agroecological studies dealing with genotype by environment by management interactions generate heterogeneous datasets difficult to gather, store, share and analyse. Modelling is an essential tool for designing and evaluating innovative sustainable cropping systems. Data integration, sharing and reusing for crop modelling need a good data management. CIRAD has developed the AEGIS (AgroEcological Global Information System) platform, which aims to sustain the data value chain {Curry, 2015) for agroecological studies. This paper present the platform overall organisation and the approach used to ensure the data-model continuum. Materials and Methods Good data management is based on two key principles. The first is Data Lifecycle Management (DLM), which consists of managing data throughout its life cycle from production to use. The second is the FAIR data principles that aim to make data findable, freely accessible, interoperable and increase data reuse. Compliant with these standards, the AEGIS platform is organized into four pilars that focus on the steps of data acquisition, processing, sharing and enhancement. Data acquisition is a process of gathering, describing and harmonizing data. AEGIS integrates a generic ®ECOFI database (Auzoux et al., 2017) using metadata technology that allows any type of data to be easily imported according to a collection process and uses a variable dictionary to facilitate the annotation of data making them understandable to all. Data processing is about making the raw data acquired easily usable for analysis and modelling. Through integrated dashboards, AEGIS offers a real-time overview of all stored data, ranging from raw data to indicators for assessing the sustainability and performance of agroecosystems. It provides homogeneous datasets for crops models simulations and capitalizes processed data, which can be simulation parameters and outputs, analysis results and performance indicators. AEGIS proposes data visualisatio