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Building data expertise into research institutions: Preliminary results
Author(s) -
Thompson Cheryl A.
Publication year - 2015
Publication title -
proceedings of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.193
H-Index - 14
ISSN - 2373-9231
DOI - 10.1002/pra2.2015.1450520100137
Subject(s) - key (lock) , knowledge management , data management , computer science , service (business) , data center , research data , data science , workforce , center (category theory) , data as a service , business , data curation , database , political science , operating system , chemistry , crystallography , computer security , marketing , law
Data‐intensive research promises advancements in scientific knowledge and brings with it new demands for staff that can manage large and complex data, design user services, and facilitate open access. Research institutions are extending their services to scientific data management. As more organizations extend their operations to research data, an understanding of how to build data expertise into staff and service models is needed. Understanding the unique expertise required and various data roles is key to providing a well‐trained workforce that can support data‐intensive science. This study examines how an exemplar data center, the National Center for Atmospheric Research, develops and supports their data expertise. This poster reports preliminary results.