D4Science provides researchers with on-demand access to scalable computing resources, enabling them to perform complex analyses and simulations without the need for costly local infrastructure.
Challenge to solve
She has developed a sophisticated model in R that simulates crop growth under various conditions. Dr. Evans wants to share this model with colleagues at other research institutions to enable them to apply it to their specific crops and regions.
How D4Science supports the user story
D4Science provides Dr. Evans with a platform to easily share and collaborate on her model, fostering scientific exchange and accelerating research progress.
- She can use the Cloud Computing Platform (CCP) to encapsulate her R model, defining the required inputs and outputs. The CCP’s support for multiple programming languages ensures flexibility for researchers using diverse tools.
- Dr. Evans can publish her model as a web service through the D4Science Catalogue, making it readily discoverable and accessible to her colleagues. The catalogue’s detailed metadata descriptions and support for open standards ensure that researchers can easily understand and integrate the model into their own workflows.
- Her colleagues can then utilise the model within their own D4Science VREs, applying it to their local datasets and comparing their findings with Dr. Evans’ original results. The CCP’s provenance tracking allows for detailed comparisons of model executions across different datasets and time periods, facilitating rigorous scientific validation and the identification of potential regional variations.
- Through the VRE’s workspace and social networking tools, Dr. Evans and her colleagues can engage in discussions, share insights, and refine the model collaboratively. This iterative process of development and validation contributes to the continuous improvement of the model and its applicability to a broader range of agricultural contexts.
