Harmonization and translation of crop modeling data to ensure interoperability
The Agricultural Model Intercomparison and Improvement Project (AgMIP) seeks to improve the capability of ecophysiological and economic models to describe the potential impacts of climate change on agricultural systems. AgMIP protocols emphasize the use of multiple models; consequently, data harmoni...
Gespeichert in:
Veröffentlicht in: | Environmental modelling & software : with environment data news 2014-12, Vol.62, p.495-508 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The Agricultural Model Intercomparison and Improvement Project (AgMIP) seeks to improve the capability of ecophysiological and economic models to describe the potential impacts of climate change on agricultural systems. AgMIP protocols emphasize the use of multiple models; consequently, data harmonization is essential. This interoperability was achieved by establishing a data exchange mechanism with variables defined in accordance with international standards; implementing a flexibly structured data schema to store experimental data; and designing a method to fill gaps in model-required input data. Researchers and modelers are able to use these tools to run an ensemble of models on a single, harmonized dataset. This allows them to compare models directly, leading ultimately to model improvements. An important outcome is the development of a platform that facilitates researcher collaboration from many organizations, across many countries. This would have been very difficult to achieve without the AgMIP data interoperability standards described in this paper.
•Heterogeneous data can be harmonized and translated to multiple model formats.•The ICASA data standards provide an extensible data structure and ontology.•JSON structures provide a flexible, efficient means of handling heterogeneous data.•DOME functions enable a consistent means of providing missing or inadequate data.•Data provenance is maintained from data sources through simulated model outputs. |
---|---|
ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2014.09.004 |