Background and Terminology for the Institute
ARL/DLF E-Science Institute http://www.arl.org/rtl/eresearch/escien/escieninstitute/index.shtml
Purpose of the Institute
The purpose of the E-Science Institute is to help your library develop a sound strategic agenda to frame your support for e-research in general and e-science in particular. A strategic agenda articulates the priorities and ambitions, opportunities and partnerships, challenges and weaknesses of your e-research support program, but stops short of being a detailed strategic plan. After the Institute, your strategic agenda will enable you to develop a program or set of services to address the key areas in your agenda. Developing your strategic agenda requires that you develop a deeper understanding of your institutional environment for e-science/e-research. The activities are designed to help you examine your local e-research landscape, to consider the relationship between your institution as a whole and your library in terms of e-research, to identify key players in e-science and e-research at your institution, and to conduct interviews of some of them to better understand their roles.
Our working definitions of “e-science” and “e-research”
E-Science typically refers to a type of scientific research that uses large-scale computing infrastructure to process very large data sets. It’s considered a new scientific paradigm (see readings) enabled by the internet, advances in data mining techniques, etc. E-research refers more generally as the concept of research using digital technology (e.g., computing, networks, and digital data) in fields including science, social science, and the humanities. Despite its title, the ARL E-Science Institute is more focused on e-research as defined above, but will also explore e-science and other key concepts in modern, network and computer-enabled research.
E-Science is computationally intensive science carried out in highly distributed network environments, such as science that uses immense data sets requiring grid computing or High Performance Computing to process. The term sometimes includes technologies that enable distributed collaboration, such as the Access Grid, and is sometimes used as an alternative term for Cyberinfrastructure (e.g. e-Science is the preferred term in the UK). Examples of e-Science research include data mining, and statistical exploration of genome and other –omic structures.
The term e-Research here refers to the use of information technology to support existing and new forms of scholarly research in all academic disciplines, including the humanities and social sciences. E-research encompasses computational and e-science, cyberinfrastructure and data curation. E-Research projects often make use of grid computing or other advanced technologies, and are usually data intensive, but the concept also includes research performed digitally at any scale. E-research is useful here as a way to bridge the concept of e-science to other fields such as social science and the humanities. Just as e-science applies large-scale computing to processing vast amounts of scientific research data, e-research could include studies of large linguistic corpuses in the humanities, or integrated social policy analyses in the social sciences.
Required Reading for the Baseline Module
Required and Recommended Readings for Building Blocks Module
- Association of Research Libraries, "Chapter 4: Applying the Scenarios to Create Strategy" in , (2010) pp. 41-46.
- H. Frank Cervone, “Strategic analysis for digital library development,” OCLC Systems & Services: International digital library perspectives Vol. 25 No. 1, (2009), pp. 16-19. (access requires subscription)
- (access requires subscription)
- Melissa H. Cragin, Carole L. Palmer, Jacob R. Carlson, and Michael Witt, Data Sharing, Small Science, and Institutional Repositories ()
- Collection Management, Vol 36, No 1, (2011). (access requires subscription)
- ", Ariadne, No 64 (July 2010).