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Presentation

Transparency: An Architecture Principle for Socio-Technical Ecosystems

  • May 2014
  • By Felix Bachmann, Linda M. Northrop
  • Presentation at SATURN 2014. The authors report efforts to increase productivity in a collaboration environment by increasing transparency using automated support.
  • Publisher: Software Engineering Institute
  • This presentation was created for a conference series or symposium and does not necessarily reflect the positions and views of the Software Engineering Institute.
  • Abstract

    The Extreme Science and Engineering Discovery Environment (XSEDE) Project is a large multi-institution effort to help scientists in multiple disciplines access and share a network of supercomputer resources, code, and data. XSEDE is a socio-technical ecosystem; it provides a computational infrastructure that helps scientists access many different supercomputing sites that have different policies and software infrastructures; the users come from different scientific and university communities with different priorities; and the developers and architects come from different institutions and subcommunities with local priorities. An SEI team has worked with XSEDE to establish sound architecture-centric engineering practices across the distributed architecture and development teams. However, productivity is not yet acceptable. An underlying cause is lack of transparency into the process and artifacts. Three factors contribute to transparency deficiencies:

    1. Many groups do things differently, using different tools. That makes information disappear or appear when it crosses the boundary to other groups.
    2. People desire to keep unfinished changes private, allowing them to become externally visible only when they reach a publishable state.
    3. The sheer volume of concurrent activities and artifacts requires more time for reviews and decisions.

    We report on efforts to increase transparency using automated support from collaborative development environments, online deliberation, information flow analysis, and machine learning tools.

  • Slides

Part of a Collection

SATURN 2014 Presentations