Data Services for Long Tail Science at the Integrated Earth Data Applications (IEDA) Data Facility
- Data Services for Long Tail Science at the Integrated Earth Data Applications (IEDA) Data Facility
- Hsu, Leslie
Lehnert, Kerstin A.
Carbotte, Suzanne M.
Ferrini, Vicki Lynn
O'Hara, Suzanne H.
Walker, J. Douglas
Arko, Robert A.
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- Presented on February 27, 2013 at Research Data Symposium, Columbia University, New York, NY.
- IEDA (Integrated Earth Data Applications) is a US-based data facility funded through a contract with the US National Science Foundation to operate data systems and data services for solid earth geoscience data. IEDA has developed a comprehensive suite of data services that are designed to address the concerns and needs of investigators, especially researchers working in the 'Long Tail of Science' (Heidorn 2008). IEDA provides a data publication service, registering datasets with DOI to ensure their proper citation and attribution. IEDA works with publishers on advanced linkages between datasets in the IEDA repository and scientific online articles to facilitate access to the data, enhance their visibility, and augment their use and citation. IEDA also developed a comprehensive investigator support that includes tools, tutorials, and virtual or face-to-face workshops that guide and assist investigators with data management planning, data submission, and data documentation. A critical aspect of IEDA's concept has been the disciplinary expertise within the team and its strong liaison with the science community, as well as a community-based governance. These have been fundamental to gain the trust and support of the scientists and have lead to significantly improved data preservation and access in the communities served by IEDA.
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- Suggested Citation:
- Leslie Hsu, Kerstin A. Lehnert, Suzanne M. Carbotte, Vicki Lynn Ferrini, Suzanne H. O'Hara, J. Douglas Walker, Robert A. Arko, 2013, Data Services for Long Tail Science at the Integrated Earth Data Applications (IEDA) Data Facility, Columbia University Academic Commons, https://doi.org/10.7916/D85X2J99.