Implementations of fine-grained automated data provenance to support transparent environmental modelling
Authors:
- Raphael SpiekermannRSRaphael Spiekermann
- Ben JollyBJBen Jolly
- Alexander HerzigAHAlexander Herzig
- Tom BurleighTBTom Burleigh
- David Medyckyj-ScottDMDavid Medyckyj-Scott
- 1 August 2019
- journal article
- research article
- Published by Elsevier in Environmental Modelling & Software
- Vol. 118, 134-145
Abstract
No abstract availableKeywords
Funding Information
- New Zealand Ministry of Business, Innovation and Employment (MBIE) research project “Innovative Data Analysis”
This publication has 40 references indexed in Scilit:
- ReproducibilityScience, 2014
- Promoting Transparency in Social Science ResearchScience, 2014
- Evaluation of Filesystem Provenance Visualization ToolsIEEE Transactions on Visualization and Computer Graphics, 2013
- Assessment of multiple ecosystem services in New Zealand at the catchment scaleEnvironmental Modelling & Software, 2013
- Modeling water and soil quality environmental impacts associated with bioenergy crop production and biomass removal in the Midwest USAEcological Modelling, 2011
- The Foundations for Provenance on the WebFoundations and Trends® in Web Science, 2010
- Special Issue: The First Provenance ChallengeConcurrency and Computation: Practice and Experience, 2007
- Comparing modelling frameworks – A workshop approachEnvironmental Modelling & Software, 2006
- Ten iterative steps in development and evaluation of environmental modelsEnvironmental Modelling & Software, 2006
- Knowing sufficient and applying more: challenges in hazards managementEnvironmental Hazards, 2002