SeedMe News

Presentation |
2018-04-06 to 2018-04-07

Building a data sharing cloud on Drupal 8 for researchers

Amit Chourasia
Presented at the Stanford Drupal Camp 2018, Stanford, CA, Apr 6-7, 2018

Researchers and academic websites often need to handle data, while Drupal is a compelling content management systems, its file handling capabilities are very limited. In this session we will present an overview and demonstration of a new set of modules that enable data sharing and file management for a variety of use cases for researchers. The new modules create and manage a secure virtual file system of nested folders and uploaded files of any type. Access controls enable users to share their content with selected friends and colleagues, or with the public at large. In addition, plugin content viewers support the presentation of files of different types, as well as automatic light-weight visualizations of table, tree, and graph data. While initially focused to support data collected and shared during scientific research, the project’s modules support additional use cases for other domains and general file sharing. The modules provide APIs, user interfaces, and a plugin structure to add features and adapt the modules to site-specific needs.


Paper | 2016-07-21

SeedMe: A scientific data sharing and collaboration platform.

Amit Chourasia, Mona Wong, Dmitry Mishin, David R. Nadeau, and Michael Norman. 2016. SeedMe: A scientific data sharing and collaboration platform. In Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale (XSEDE16). ACM, New York, NY, USA, , Article 48 , 6 pages. DOI=10.1145/2949550.2949590

Preprint PDF

Poster | 2016-07-20

SeedMe: Data sharing building blocks

Amit Chourasia, David R. Nadeau, John Moreland, Dmitry Mishin and Michael L. Norman
Presented at the XSEDE 2016 conference. Miami, FL Jul 17-21, 2016.
Download poster

Tutorial | 2016-07-18

Data sharing tutorial @ XSEDE 2016

Introduction to Scientific Visualization and Data Sharing. Presented at the XSEDE 2016 Conference, Miami, FL, Jul 17-21 2016

Presenter: Amit Chourasia, San Diego Supercomputer Center, UC San Diego

Webinar | 2016-06-21

Overview of SeedMe @ XSEDE Campus Champions Teleconference

In this talk we introduce the SeedMe platform which provides a web-based cyberinfrastructure to enable easy sharing and streaming of transient data and preliminary results directly from computing resources to a variety of platforms, from mobile devices to workstations. The SeedMe platform is open to all researchers and provides web browser based as well scriptable tools for easy integration with ad hoc computation workflows.

Webinar | 2016-06-21

SeedMe platform: Enabling scriptable data sharing @ XSEDE ECSS Symposium

Release | 2016-06-09

SeedMe has been upgraded to version 1.4, with several new improvements:

Presentation | 2016-05-17

Presented at the Best Practices in Data Infrastructure Workshop at the Pittsburg Supercomputer Center. Discuss the lessons learned and provide an overview of new and modular SeedMe platform under development. [Slides]

Presenter: Amit Chourasia, San Diego Supercomputer Center, UC San Diego

Release | 2015-12-15
SeedMe has been upgraded to version 1.3, with several new improvements.
  • Web services will support deletion of content, ownership transfer for collection and streamlined server response for query and messages.
  • Enhancements to existing features. Images now open in web browser instead of being downloaded
  • Several bug fixes.
  • Updated Python module and windows command line client to version 1.2.0. Download here.
  • Java client (To be released shortly)
Tutorial | 2015-11-15

Publish visualization results to SeedMe.org from VisIt

To be presented at the the Effective HPC visualization and data analysis using VisIt tutorial at SC15. Austin, TX, Nov 15, 2015

Instructor: Amit Chourasia, San Diego Supercomputer Center, UC San Diego

TutorialWebinar | 2015-11-04

Research projects involving scientific computing are now increasingly collaborative and performed on high performance clusters. These clusters offer significant computing capacity and capability to carry out several computation and analysis in parallel or distributed manner. However, the tools and policies on clusters are single user centric and impose restrictions on how processed data and computed results can be accessed and shared with research team. Furthermore, the tools and policies vary on different clusters making the sharing process non-portable and laborious.

Pages