K-span: Open and reproducible spatial analytics using scientific workflows

Frontiers in Earth Science

Earth Science

Abdur Forkan¹  Hamish Anderson²  Alan Both³  Chris Bellman⁴  Nenad Radosevic⁴  Matt Duckham⁴ 

[1] Department of Computing Technologies, Swinburne University of Technology, Melbourne, VIC, Australia;Geoscience Australia, Canberra, ACT, Australia;School of Global, Urban and Social Studies, RMIT, Melbourne, VIC, Australia;School of Science, RMIT University, Melbourne, VIC, Australia;

关键词: scientific workflows;    KNIME;    reproducibility;    open source;    geospatial analysis;    Digital Elevation Model;   

DOI  :  10.3389/feart.2023.1130262

 received in 2022-12-23, accepted in 2023-02-10,  发布年份 2023

来源: Frontiers

【 摘 要 】

This paper describes the design, development, and testing of a general-purpose scientific-workflows tool for spatial analytics. Spatial analytics processes are frequently complex, both conceptually and computationally. Adaptation, documention, and reproduction of bespoke spatial analytics procedures represents a growing challenge today, particularly in this era of big spatial data. Scientific workflow systems hold the promise of increased openness and transparency with improved automation of spatial analytics processes. In this work, we built and implemented a KNIME spatial analytics (“K-span”) software tool, an extension to the general-purpose open-source KNIME scientific workflow platform. The tool augments KNIME with new spatial analytics nodes by linking to and integrating a range of existing open-source spatial software and libraries. The implementation of the K-span system is demonstrated and evaluated with a case study associated with the original process of construction of the Australian national DEM (Digital Elevation Model) in the Greater Brisbane area of Queensland, Australia by Geoscience Australia (GA). The outcomes of translating example spatial analytics process into a an open, transparent, documented, automated, and reproducible scientific workflow highlights the benefits of using our system and our general approach. These benefits may help in increasing users’ assurance and confidence in spatial data products and in understanding of the provenance of foundational spatial data sets across diverse uses and user groups.

【 授权许可】

Unknown   
Copyright © 2023 Forkan, Both, Bellman, Duckham, Anderson and Radosevic.