Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...
This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.
This resource contains content types with files that need to be updated to match with metadata changes. Show content type files that need updating.
| Authors: |
|
|
|---|---|---|
| Owners: |
|
This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource. |
| Type: | Resource | |
| Storage: | The size of this resource is 4.4 MB | |
| Created: | Jul 18, 2017 at 7:33 p.m. | |
| Last updated: | Jul 25, 2017 at 3:27 p.m. | |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
|---|---|
| Views: | 2069 |
| Downloads: | 59 |
| +1 Votes: | Be the first one to this. |
| Comments: | No comments (yet) |
Abstract
Jupyter notebooks are becoming popular among the geoscience community for there ability to clearly present, disseminate, and describe scientific findings in a transparent and reproducible manner. This also makes them a desirable mechanism for sharing and collaborating scientific data and workflows with colleagues during the research process, especially when addressing large-scale cross-disciplinary geoscience issues. This work extends Jupyter notebooks to operate in a pre-configured cloud environment that is integrated with HydroShare for its data sharing and collaboration functionality, and notebooks are executed on the Resourcing Open Geospatial Education and Research (ROGER) supercomputer hosted in the CyberGIS center. This design enables researchers to address problems that are often larger in scale than can be done on a typical desktop computer. Additionally, the integration of these technologies enables researchers to collaborate on notebook workflows that execute in the cloud and are shared through the HydroShare platform. The goals of this work are to establish an open source platform for domain scientists to (1) conduct data intensive and computationally intensive collaborative research, and (2) organize data driven educational material via classroom modules, workshops, or training courses. This presentation will discuss recent efforts towards achieving these goals, and describe the architectural design of the notebook server in an effort to support collaborative and reproducible science.
Subject Keywords
Content
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
There are currently no comments
New Comment