Binata Roy

University of Virginia

 Recent Activity

ABSTRACT:

Sciunit (https://sciunit.run/) is a tool that encapsulates a set of executions into an isolated, independent container. It allows computational scientists to create research objects, which can be reused and transferred to other computational environments for reproducibility. Sciunit containerizes a program by capturing the trace of its execution using system utilities. It stores the sequence of instructions to run the program and the input and output data content used by that program. Programs in this self-contained sandbox are reproduced on the system or transported to another system for re-execution.

In this resource, users can show how to reproduce a Sciunit Container that encapsulates MODFLOW-NWT Use Case in the James River watershed upstream of Richmond, VA, USA

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ABSTRACT:

This HydroShare resource has the results of performance tests that are computational_time.csv, size.csv, and complexity.csv.
Using Jupyter notebook, we created four performance plots in the manuscript of "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" in Environmental Modeling and Software.

Figure 9. The total scores of complexity on reproducible approaches for developer and user work
Figure 10 Comparison of the size for reproducible artifacts in five local reproducible approaches
Figure 11 Comparison of computational time in five local reproducible approaches
Figure 12 Comparison of computational time in six remote reproducible approaches

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ABSTRACT:

This is a collection resource for "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" manuscript in Environmental Modeling and Software.

HS-1: Collection Resource for Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems

For SUMMA simulation, we created two SUMMA model instances.
HS-2. Model Instance for the Impact of Stomatal Resistance Parameterizations on ET of SUMMA Model in Aspen stand at Reynolds Mountain East
HS-3. Model Instance for the Impact of Lateral Flow Parameterizations on Runoff of SUMMA Model at Reynolds Mountain East

For SUMMA simulation, we created a SUMMA model program
HS-4: Remote Approach-11: Using HPC Cluster (Rivanna: HPC at University of Virginia) for the reproducibility of SUMMA modeling

There are five HS resources for reproducible approaches.
HS-5. A Virtual Box image that includes five local approaches:
- Approach-1 Compiling the core model software
- Approach-2 Containerizing the core model software only with Docker
- Approach-3 Containerizing all software with Docker
- Approach-4 Containerizing all software with Singularity
- Approach-5 Containerizing all software and modeling workflows with Sciunit
HS-6. Approach-6 Using CUAHSI JupyterHub
HS-7. Approach-7 Using CyberGIS-Jupyter for water
HS-8. Approach-8 Using Sciunit in CUAHSI JupyterHub
HS-9. Approach-9 Using Sciunit in CyberGIS-Jupyter for water

Lastly, we created a notebook for performance tests using the different reproducible approaches.
HS-10. Jupyter notebook for performance test using the different reproducible approaches

In addition, there are three GitHub repositories for reproducible approaches in related resources in the reference section.
Git-1. Approach-10 Using Binder (https://github.com/uva-hydroinformatics/SUMMA_Binder.git)
Git-2. Description of Approach-3 to show how to create Docker environments (https://github.com/uva-hydroinformatics/SUMMA_Docker_Training.git)
Git-3. Description of Approach-4 and 11 to show how to use a Singularity image in HPC (https://github.com/uva-hydroinformatics/SUMMA_Singularity_In_Rivanna.git)

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ABSTRACT:

This HydroShare resource provides the Jupyter Notebooks for the reproducibility of SUMMA modeling using Sciunit in CUAHSI JupyterHub in the manuscript of "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" in Environmental Modeling and Software.

To find out the instructions on how to run Jupyter Notebooks, please refer to the README file which is provided in this resource.

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ABSTRACT:

This HydroShare resource provides the Jupyter Notebooks for the reproducibility of SUMMA modeling using Sciunit in CyberGIS-Jupyter for water in the manuscript of "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" in Environmental Modeling and Software.

To find out the instructions on how to run Jupyter Notebooks, please refer to the README file which is provided in this resource.

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Composite Resource 0
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MODFLOW Model Instance Resource 0
Multidimensional (NetCDF) 0
Script Resource 0
SWAT Model Instance 0
Time Series 0
Web App 0
Model Program Resource Model Program Resource

ABSTRACT:

This HydroShare resource provides a Singularity image for Remote Approach 11: Using an HPC Cluster in the manuscript of "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" in Environmental Modeling and Software.

For more detailed information, please see this GitHub
https://github.com/DavidChoi76/Using_Singularity_in_Local_Approach_4_and_HPC_Cluster_Approach_11_for_the_reproducibility_of_SUMMA

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Composite Resource Composite Resource

ABSTRACT:

This HydroShare resource provides the Jupyter Notebooks for the reproducibility of SUMMA modeling using CyberGIS-Jupyter for water in the manuscript of "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" in Environmental Modeling and Software.

To find out the instructions on how to run Jupyter Notebooks, please refer to the README file which is provided in this resource.

Show More
Composite Resource Composite Resource

ABSTRACT:

This HydroShare resource provides the Jupyter Notebooks for the reproducibility of SUMMA modeling using CUAHSI JupyterHub in the manuscript of "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" in Environmental Modeling and Software.

To find out the instructions on how to run Jupyter Notebooks, please refer to the README file which is provided in this resource.

Show More
Composite Resource Composite Resource

ABSTRACT:

This HydroShare resource provides the Jupyter Notebooks for the reproducibility of SUMMA modeling using Sciunit in CyberGIS-Jupyter for water in the manuscript of "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" in Environmental Modeling and Software.

To find out the instructions on how to run Jupyter Notebooks, please refer to the README file which is provided in this resource.

Show More
Composite Resource Composite Resource

ABSTRACT:

This HydroShare resource provides the Jupyter Notebooks for the reproducibility of SUMMA modeling using Sciunit in CUAHSI JupyterHub in the manuscript of "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" in Environmental Modeling and Software.

To find out the instructions on how to run Jupyter Notebooks, please refer to the README file which is provided in this resource.

Show More
Collection Resource Collection Resource

ABSTRACT:

This is a collection resource for "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" manuscript in Environmental Modeling and Software.

HS-1: Collection Resource for Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems

For SUMMA simulation, we created two SUMMA model instances.
HS-2. Model Instance for the Impact of Stomatal Resistance Parameterizations on ET of SUMMA Model in Aspen stand at Reynolds Mountain East
HS-3. Model Instance for the Impact of Lateral Flow Parameterizations on Runoff of SUMMA Model at Reynolds Mountain East

For SUMMA simulation, we created a SUMMA model program
HS-4: Remote Approach-11: Using HPC Cluster (Rivanna: HPC at University of Virginia) for the reproducibility of SUMMA modeling

There are five HS resources for reproducible approaches.
HS-5. A Virtual Box image that includes five local approaches:
- Approach-1 Compiling the core model software
- Approach-2 Containerizing the core model software only with Docker
- Approach-3 Containerizing all software with Docker
- Approach-4 Containerizing all software with Singularity
- Approach-5 Containerizing all software and modeling workflows with Sciunit
HS-6. Approach-6 Using CUAHSI JupyterHub
HS-7. Approach-7 Using CyberGIS-Jupyter for water
HS-8. Approach-8 Using Sciunit in CUAHSI JupyterHub
HS-9. Approach-9 Using Sciunit in CyberGIS-Jupyter for water

Lastly, we created a notebook for performance tests using the different reproducible approaches.
HS-10. Jupyter notebook for performance test using the different reproducible approaches

In addition, there are three GitHub repositories for reproducible approaches in related resources in the reference section.
Git-1. Approach-10 Using Binder (https://github.com/uva-hydroinformatics/SUMMA_Binder.git)
Git-2. Description of Approach-3 to show how to create Docker environments (https://github.com/uva-hydroinformatics/SUMMA_Docker_Training.git)
Git-3. Description of Approach-4 and 11 to show how to use a Singularity image in HPC (https://github.com/uva-hydroinformatics/SUMMA_Singularity_In_Rivanna.git)

Show More
Composite Resource Composite Resource

ABSTRACT:

This HydroShare resource has the results of performance tests that are computational_time.csv, size.csv, and complexity.csv.
Using Jupyter notebook, we created four performance plots in the manuscript of "Comparing Approaches to Achieve Reproducible Computational Modeling for Hydrological and Environmental Systems" in Environmental Modeling and Software.

Figure 9. The total scores of complexity on reproducible approaches for developer and user work
Figure 10 Comparison of the size for reproducible artifacts in five local reproducible approaches
Figure 11 Comparison of computational time in five local reproducible approaches
Figure 12 Comparison of computational time in six remote reproducible approaches

Show More
Composite Resource Composite Resource

ABSTRACT:

Sciunit (https://sciunit.run/) is a tool that encapsulates a set of executions into an isolated, independent container. It allows computational scientists to create research objects, which can be reused and transferred to other computational environments for reproducibility. Sciunit containerizes a program by capturing the trace of its execution using system utilities. It stores the sequence of instructions to run the program and the input and output data content used by that program. Programs in this self-contained sandbox are reproduced on the system or transported to another system for re-execution.

In this resource, users can show how to reproduce a Sciunit Container that encapsulates MODFLOW-NWT Use Case in the James River watershed upstream of Richmond, VA, USA

Show More