CrowdLabs: Social analysis and visualization for the sciences

Phillip Mates, Emanuele Santos, Juliana Freire, Cláudio T. Silva

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Managing and understanding the growing volumes of scientific data is one of the most challenging issues scientists face today. As analyses get more complex and large interdisciplinary groups need to work together, knowledge sharing becomes essential to support effective scientific data exploration. While science portals and visualization Web sites have provided a first step towards this goal, by aggregating data from different sources and providing a set of pre-designed analyses and visualizations, they have important limitations. Often, these sites are built manually and are not flexible enough to support the vast heterogeneity of data sources, analysis techniques, data products, and the needs of different user communities. In this paper we describe CrowdLabs, a system that adopts the model used by social Web sites, allowing users to share not only data but also computational pipelines. The shared repository opens up many new opportunities for knowledge sharing and re-use, exposing scientists to tasks that provide examples of sophisticated uses of algorithms they would not have access to otherwise. CrowdLabs combines a set of usable tools and a scalable infrastructure to provide a rich collaborative environment for scientists, taking into account the requirements of computational scientists, such as accessing high-performance computers and manipulating large amounts of data.

Original languageEnglish (US)
Title of host publicationScientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings
Number of pages10
StatePublished - 2011
Event23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011 - Portland, OR, United States
Duration: Jul 20 2011Jul 22 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6809 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011
Country/TerritoryUnited States
CityPortland, OR


  • Computational Sciences
  • Cyberinfrastructure
  • Visualization

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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