A Reusable Scientific workflow for Conservation Planning

Guru, S, Dwyer, R, Watts, M, Dinh, M, Abramson, D, Nguyen, H, Campbell, H, Franklin, C, Clancy, T and Possingham, H 2015, 'A Reusable Scientific workflow for Conservation Planning', in Weber, T., McPhee, M.J. and Anderssen, R.S. (ed.) Proceedings of the 21st International Congress on Modelling and Simulation (MODSIM 2015), Gold Coast, Queensland, Australia, 29 November - 4 December 2015, pp. 1441-1447.


Document type: Conference Paper
Collection: Conference Papers

Title A Reusable Scientific workflow for Conservation Planning
Author(s) Guru, S
Dwyer, R
Watts, M
Dinh, M
Abramson, D
Nguyen, H
Campbell, H
Franklin, C
Clancy, T
Possingham, H
Year 2015
Conference name MODSIM 2015: Partnering with industry and the community for innovation and impact through modelling
Conference location Gold Coast, Queensland, Australia
Conference dates 29 November - 4 December 2015
Proceedings title Proceedings of the 21st International Congress on Modelling and Simulation (MODSIM 2015)
Editor(s) Weber, T., McPhee, M.J. and Anderssen, R.S.
Publisher Modelling and Simulation Society of Australia and New Zealand
Place of publication Perth, Australia
Start page 1441
End page 1447
Total pages 7
Abstract In order to perform complex scientific data analysis, multiple software and skillsets are generally required. These analyses can involve collaborations between scientific and technical communities, with expertise in problem formulation and the use of tools and programming languages. While such collaborations are useful for solving a given problem, transferability and productivity of the approach is low and requires considerable assistance from the original tool developers. Any complex scientific data analysis involves accessing and refining large volumes of data, running simulations and algorithms, and visualising results. These steps can incorporate a variety of tools and programming languages, and can be constructed as a series of activities to achieve a desired outcome. This is where scientific workflows are very useful. Scientific workflows abstract complex analyses into a series of inter-dependent computational steps that lead to a solution for a scientific problem. Once constructed, the workflow can be executed repeatedly and the results reproduced with minimal assistance from the original tool developers. This improves transferability, repeatability and productivity, and reduces costs by reusing workflow components for similar problems but using different datasets. Kepler is a popular open-source scientific workflow tool for designing, executing, archiving and sharing workflows. It has the ability to couple disparate execution environments on a single platform. For example, users can run analysis steps written in Python, R and Matlab on a single platform as part of a single analysis and synthesis experiment. Kepler provides a wide variety of reusable components that perform various tasks, including data access from databases, remote system, file system and web services, and data servers, and executes these processes in a local or distributed environment. Together these functionalities provide greater flexibility for researchers to undertake complex scientific
Subjects Biological Sciences not elsewhere classified
Information and Computing Sciences not elsewhere classified
Keyword(s) Conservation planning
scientific workflow
Marxan
optimisation
Copyright notice Copyright © 2015 Authors and Modelling and Simulation Society of Australia and New Zealand Inc. All rights reserved. Creative Commons Attribution 4.0 International CC BY License
ISBN 9780987214355
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Access Statistics: 15 Abstract Views  -  Detailed Statistics
Created: Wed, 23 Oct 2019, 08:59:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us