1. What is PyCrop2ML?

PyCrop2ML is a free, open-source library for defining and exchanging CropML models.It is used to generate components of modeling and simulation platforms from the CropML specification and allow component exchange between different platform.
It allows to parse the models described in CropML format and automatically generate the equivalent executable Python, java, C#, C++ components and packages usable from existing crop simulation platform.

2. What is Crop2ML ?

CropML is a XML-(JSON-)based language used to represent different biological processes involved in the crop models.
CropML project aims to provide common framework for defining and exchanging descriptions of crop growth models between crop simulation frameworks.

2.1. Objectives

Our main objectives are:

  • define a declarative language to describe either an atomic model or a composition of models
  • add semantic dimension to CropML language by annotation of the models to allow the composition of components of different platforms by using the standards of the semantic web
  • develop a library to allow the transformation and the exchange of CropML model between different Crop modelling and simulation platform
  • provide a web repository enabling registration, search and discovery of CropML Models
  • facilitate Agricultural Model Exchange Initiative

2.2. Context

Nowadays, we observe the emergence of plant growth models which are built in different platforms. Although standard platform development initiatives are emerged, there is a lack of transparency, reusability, and exchange code between platforms due to the high diversity of modeling languages leading to a lack of benchmarking between the different platforms.
This project aims to gather developers and plant growth modelers to define a standard framework based on the development of declarative language and libraries to improve exchange model components between platforms.

2.3. Motivation

Our motivation is to:
  • Strengthen the synergy between crop modelers, users and scientific researchers
  • Facilitate model intercomparison (at the process level) and model improvement through the exchange of model components (algorithms) and code reuse between platforms/models.
  • Bridge the gap between ecophysiologists who develop models at the process level with crop modelers and model users and facilitate the integration in crop models of new knowledge in plant science (i.e. we are seeking the exchange of knowledge rather than black box models).
  • Increase capabilities and responsiveness to stakeholder’ needs.
  • Propose a solution to the AgMIP community for NexGen crop modeling tools.

2.4. Vision

  • Facilitate the development of complex models
  • Use modular modelling to share knowledge and rapidly develop operational tools.
  • Reuse model parts to leverage the expertise of third parties;
  • Renovate legacy code.
  • Realize the benefit of sharing and complementing different expertise.
  • Promote model sharing and reuse