Cyberinfrastructure (or CI) describes research environments that support advanced data acquisition, data storage, data management, data integration, data mining, data visualization and other computing and information processing services distributed over the Internet beyond the scope of a single institution. In scientific usage, cyberinfrastructure is a technological strategy for efficiently connecting laboratories, data, computers, and people with the goal of enabling novel scientific theories and knowledge. The term “cyberinfrastructure” was coined in the U.S. and other countries may have different terms for this type of technological infrastructure. Cyberinfrastructure now often includes systems for managing, archiving and preserving data, in addition to data processing, and so can include digital libraries and archives and the software and hardware to support them. For example, an institutional repository could be considered a “piece” of cyberinfrastructure in that it can support the storage, management, and processing of research data.

Further Resources


Gold A. (2007). Cyberinfrastructure, Data, and Libraries, Part 1: A Cyberinfrastructure Primer for Librarians. D-Lib Magazine, 13(9/10).

Gold A. (2007). Cyberinfrastructure, Data, and Libraries, Part 2: Libraries and the Data Challenge: Roles and Actions for Libraries. D-Lib Magazine, 13(9/10).

Berman F and Brady H. (2005). Final Report: NSF SBE-CISE Workshop on Cyberinfrastructure and the Social Sciences.

Treloar A. (2014). The Research Data Alliance: Globally Coordinated Action against Barriers to Data Publishing and Sharing. Learned Publishing, 27(5), 9–13.


Allard S. (2012). DataONE: Facilitating eScience through Collaboration. Journal of eScience Librarianship, 1(1):4–17.

Borgman CL. What can studies of e-Learning teach us about Collaboration in e-Research? Some findings from digital library studies. Journal of Computer Supported Cooperative Work, 15(4):359–83.

Crowston K. (2015). “Personas” to Support Development of Cyberinfrastructure for Scientific Data Sharing. Journal of eScience Librarianship, 4(2), e1082.

Heath AP, Greenway M, Powell R, Spring J, Suarez R, Hanley D, … Grossman RL. (2014). Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets. Journal of the American Medical Informatics Association, 21(6), 969–975.

Lecarpentier D, Wittenburg P, Elbers W, Michelini A, Kanso R, Coveney P, & Baxter R. (2013). EUDAT: A New Cross-Disciplinary Data Infrastructure for Science. International Journal of Digital Curation, 8(1), 279–287.

LeDuc R, Vaughn M, Fonner JM, Sullivan M, Williams JG, Blood PD, … Barnett W. (2014). Leveraging the national cyberinfrastructure for biomedical research. Journal of the American Medical Informatics Association, 21(2), 195–199.

Parsons MA. (2013). The Research Data Alliance: Implementing the Technology, Practice and Connections of a Data Infrastructure. Bulletin of the American Society for Information Science and Technology2, 39(6), 33–36.

Steinhart G, Saylor J, Albert P, Alpi K, Baxter P, Brown E, et al. (2008). Digital research data curation: Overview of issues, current activities, and opportunities for the Cornell University LibraryeCommons@Cornell.

Youngseek K, Addom BK, Stanton JM. Education for eScience Professionals : Integrating Data Curation and Cyberinfrastructure. International Journal of Digital Curation [Internet]. 2011;6(1):125–38.

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