RT Journal Article
SR Electronic
T1 Scientific modelling can be accessible, interoperable and user friendly: An example for pasture and livestock modelling
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.02.23.432363
DO 10.1101/2021.02.23.432363
A1 Alba Marquez Torres
A1 Stefano Balbi
A1 Ferdinando Villa
YR 2022
UL http://biorxiv.org/content/early/2022/02/01/2021.02.23.432363.abstract
AB This article describes the adaptation of a non-spatial model of pastureland dynamics, including vegetation life cycle, livestock management and nitrogen cycle, for use in a spatially explicit and modular modelling platform (k.LAB) dedicated to make data and models more interoperable. The aim is to deliver an existing, locally successful monolithic model, into a more modular, transparent and accessible approach to potential end users, regional managers, farmers and other stakeholders. This allows better usability and adaptability of the model beyond its originally intended geographical scope (the Cantabrian Region in the North of Spain). The original model, named Puerto, is developed in the R language and includes 1,491 lines of code divided into 13 script files and linked to 19 input tables. The spatiotemporal rewrite is structured around a set of 10 namespaces called PaL (Pasture and Livestock), which includes 198 interoperable but independent models. The end user chooses the spatial and temporal context of the analysis through an intuitive web-based user interface called k.Explorer. Each model can be called individually or in conjunction with the others, by querying any PaL-related concepts in a search bar. A scientific workflow is built as a response, which is run to produce result datasets and a report with information on the data sources and modelling processes used, delivering results with full transparency. We argue that this work demonstrates key steps needed to create more Findable, Accessible, Interoperable and Reusable (FAIR) models. This is particularly essential in environments as complex as agricultural systems, where multidisciplinary knowledge needs to be integrated across diverse spatial and temporal scales in order to understand complex and changing problems.Competing Interest StatementThe authors have declared no competing interest.