A Grid for Multidimensional and Multivariate Spatial Representation and Data Processing

Researchers use 2D and 3D spatial models of multivariate data of differing resolutions and formats. It can be challenging to work with multiple datasets, and it is time consuming to set up a robust, performant grid to handle such spatial models. We share ‘agrid’, a Python module which provides a fra...

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Bibliographic Details
Main Authors: Tobias Stål, Anya M. Reading
Format: Article
Language:English
Published: Ubiquity Press 2020-01-01
Series:Journal of Open Research Software
Subjects:
Online Access:https://openresearchsoftware.metajnl.com/articles/287
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spelling doaj-03987efe97c743989f5c03f95cefa9162020-11-25T03:08:36ZengUbiquity PressJournal of Open Research Software2049-96472020-01-018110.5334/jors.287203A Grid for Multidimensional and Multivariate Spatial Representation and Data ProcessingTobias Stål0Anya M. Reading1School of Natural Sciences and Institute for Marine and Antarctic Studies, University of Tasmania, HobartSchool of Natural Sciences and Institute for Marine and Antarctic Studies, University of Tasmania, HobartResearchers use 2D and 3D spatial models of multivariate data of differing resolutions and formats. It can be challenging to work with multiple datasets, and it is time consuming to set up a robust, performant grid to handle such spatial models. We share ‘agrid’, a Python module which provides a framework for containing multidimensional data and functionality to work with those data. The module provides methods for defining the grid, data import, visualisation, processing capability and export. To facilitate reproducibility, the grid can point to original data sources and provides support for structured metadata. The module is written in an intelligible high level programming language, and uses well documented libraries as numpy, xarray, dask and rasterio.   Funding statement: This research was supported under Australian Research Council’s Special Research Initiative for Antarctic Gateway Partnership (Project ID SR140300001).https://openresearchsoftware.metajnl.com/articles/287spatial modelmultivariate processingpythonregular grid
collection DOAJ
language English
format Article
sources DOAJ
author Tobias Stål
Anya M. Reading
spellingShingle Tobias Stål
Anya M. Reading
A Grid for Multidimensional and Multivariate Spatial Representation and Data Processing
Journal of Open Research Software
spatial model
multivariate processing
python
regular grid
author_facet Tobias Stål
Anya M. Reading
author_sort Tobias Stål
title A Grid for Multidimensional and Multivariate Spatial Representation and Data Processing
title_short A Grid for Multidimensional and Multivariate Spatial Representation and Data Processing
title_full A Grid for Multidimensional and Multivariate Spatial Representation and Data Processing
title_fullStr A Grid for Multidimensional and Multivariate Spatial Representation and Data Processing
title_full_unstemmed A Grid for Multidimensional and Multivariate Spatial Representation and Data Processing
title_sort grid for multidimensional and multivariate spatial representation and data processing
publisher Ubiquity Press
series Journal of Open Research Software
issn 2049-9647
publishDate 2020-01-01
description Researchers use 2D and 3D spatial models of multivariate data of differing resolutions and formats. It can be challenging to work with multiple datasets, and it is time consuming to set up a robust, performant grid to handle such spatial models. We share ‘agrid’, a Python module which provides a framework for containing multidimensional data and functionality to work with those data. The module provides methods for defining the grid, data import, visualisation, processing capability and export. To facilitate reproducibility, the grid can point to original data sources and provides support for structured metadata. The module is written in an intelligible high level programming language, and uses well documented libraries as numpy, xarray, dask and rasterio.   Funding statement: This research was supported under Australian Research Council’s Special Research Initiative for Antarctic Gateway Partnership (Project ID SR140300001).
topic spatial model
multivariate processing
python
regular grid
url https://openresearchsoftware.metajnl.com/articles/287
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