A task-centered framework for computationally-grounded science collaborations

Yolanda Gil, Felix Michel, Varun Ratnakar, Matheus Hauder, Christopher Duffy, Hilary Dugan, Paul Hanson

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

4 Scopus citations

Abstract

Collaboration is ubiquitous in today's science, yet there is limited support for coordinating scientific work. The general-purpose tools that are typically used (e.g., email, shared document editing, social coding sites), have still not replaced in-person meetings, phone calls, and extensive emails needed to coordinate and track collaborative activities. Scientists with diverse knowledge and skills around the globe could collaborate by opening scientific processes that expose all tasks and activities publicly to achieve a shared scientific question. This paper describes the Organic Data Science framework to support scientific collaborations that revolve around complex science questions that require significant coordination, entice contributors to remain engaged for extended periods of time, and enable continuous growth to accommodate new contributors as the work evolves over time. We discuss how the design of this framework incorporates principles followed by successful on-line communities. We present initial results to date of several communities that are collaborating using this framework.

Original languageEnglish (US)
Title of host publicationProceedings - 11th IEEE International Conference on eScience, eScience 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages352-361
Number of pages10
ISBN (Electronic)9781467393256
DOIs
StatePublished - Oct 22 2015
Event11th IEEE International Conference on eScience, eScience 2015 - Munich, Germany
Duration: Aug 31 2015Sep 4 2015

Publication series

NameProceedings - 11th IEEE International Conference on eScience, eScience 2015

Other

Other11th IEEE International Conference on eScience, eScience 2015
Country/TerritoryGermany
CityMunich
Period8/31/159/4/15

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Management Science and Operations Research

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