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Challenges in the Research Data Ecosystem

Challenges in the Research Data Ecosystem. Implications for DDI. Chuck Humphrey University of Alberta October 2012. Our design paradox. Complexity. Simplicity. IPY Projects. Data infrastructure. Solution spaces.

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Challenges in the Research Data Ecosystem

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  1. Challenges in the Research Data Ecosystem Implications for DDI Chuck Humphrey University of Alberta October 2012

  2. Our design paradox Complexity • Simplicity

  3. IPY Projects

  4. Data infrastructure Solution spaces Paul Edwards, Steven Jackson, Geoffrey Bowker, and Cory Knobel. Understanding Infrastructure: Dynamics, Tensions, and Design (January 2007)

  5. Long tail of data Measured in Petabytes Numbers of Datasets in 100k

  6. Long tail of data Volume Velocity Variety

  7. Data Ecosystem

  8. Data ecosystem Interoperability • Enabling reuse = Impact • Data integration • Data exchange • Coping with variety is a very broad yet characterizing aspect of interoperability. [Pasquale Pagano]

  9. Context for remarks • International Polar Year (IPY), 2007-2012 • DataONE (NSF DataNet) 2010- • OECD Global Science Forum on Data and Research Infrastructure for the Social Sciences, (OECD GSF) 2010-2012 • Global Research Data Infrastructure 2020 (GRDI2020) 2010-2012 • Data Web Forum (DWF) 2012-2012Data Access and Interoperability Task Force (DAITF) 2012-2012Research Data Alliance 2012-

  10. Readings • Edwards, Paul, Steven Jackson, Geoffrey Bowker, and Cory Knobel. Understanding Infrastructure: Dynamics, Tensions, and Design (January 2007) • GRDI2020 Final Roadmap Report. Global Research Data Infrastructures: The Big Data Challenges. http://tinyurl.com/8lcehcy • Pagano, Pasquale . Data Interoperability. http://tinyurl.com/8brx7xw • Parsons, Mark, et.al., “A Conceptual Framework for Managing Very Diverse Data for Complex, Interdisciplinary Science,” Journal of Information Science (2011, pp. 555-569)

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