About SeedMeLab

SeedMeLab (formerly SeedMe2) is built as a set of modular web-based building blocks to enable users to quickly share, visualize, and discuss the results of experiments, simulations and analyses with context.

SeedMe = Stream, Encode, Explore and Disseminate My Experiments


SeedMeLab was developed as powerful data management and data sharing software suite. It enables research teams to manage, share, search, visualize, and present their data in a web-based environment using an access-controlled, branded, and customizable website they own and control. It supports storing and viewing data in a familiar tree hierarchy but also supports formatted annotations, lightweight visualizations, and threaded comments on any file/folder. The system can be easily extended and customized to support metadata, job parameters, and other domain and project-specific contextual items. The software is open source and available as an extension to the popular Drupal content management system


SeedMeLab is developed and maintained by the San Diego Supercomputer Center at the University of California at San Diego.


  • Undergrad interns:  Stephen Cheung, Subhash Ramesh; CSE/UCSD

Alumni members

  • Michael Dwyer, Database administrator
  • Dmitry Mishin, Application developer
  • Master's intern: Jiaping Luo CSE/UCSD
  • Undergraduate interns: Mingxuan Fan, Connie Guan, Jeremy Park, Jonathan Wong, Kyle Sung, Sayan Chatterjee, Sayan Ray Chaudhuri
  • High school interns: Aniruddha Alawani,  Ashwanth Muruhathasn, Austin Chen, Casey Holden, Lisa Sun, Rahul Kulkarni, Ryan Wei


Grant Awards: This work was supported by the National Science Foundation under Grant No. 1443083. "Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation."

SGCI support: We would like acknowledge the Science Gateways Community Institute for providing support in help with guidance on outreach material and website usability study. 

Collaborators & Users: Our sincere thanks to collaborators and early users for their continued support and feedback that helped in defining and refining features.