A Capability Maturity Model for Research Data Management
CMM for RDM » 1. Data Management in General » 1.2 Ability to Perform

Changes for document 1.2 Ability to Perform

Last modified by Arden Kirkland on 2014/05/18 11:56
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edited by Arden Kirkland
on 2014/03/14 10:36
To version 50.1
edited by Arden Kirkland
on 2014/03/14 17:02
Change comment: link to DATAPASS

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22 22 == 1.2.2 Staffing for data management ==
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24 -Staffing for data management refers to identifying the levels and types of expertise needed for achieving immediate and/or near-term data management objectives. A data management lifecycle involves different tasks at different stages that demand a combination of varying levels and types of expertise and skills. For example, the Data Preservation Alliance for the Social Sciences (DATA-PASS) is a broad-based partnership of data archives for acquiring, cataloging, and preserving social sciences data. The partnership involves existing data repositories, academic institutions, and government agencies. As such the communications among partners, technical system architecture, and policies are inherently complicated. Having a capable staff will be extremely important to meet the constantly shifting data curation activities ([[Walters & Skinner, 2011>>||anchor="Walters"]]).
24 +Staffing for data management refers to identifying the levels and types of expertise needed for achieving immediate and/or near-term data management objectives. A data management lifecycle involves different tasks at different stages that demand a combination of varying levels and types of expertise and skills. For example, the Data Preservation Alliance for the Social Sciences (DATA-PASS at [[http:~~/~~/www.data-pass.org>>url:http://www.data-pass.org||rel="__blank"]]) is a broad-based partnership of data archives for acquiring, cataloging, and preserving social sciences data. The partnership involves existing data repositories, academic institutions, and government agencies. As such the communications among partners, technical system architecture, and policies are inherently complicated. Having a capable staff will be extremely important to meet the constantly shifting data curation activities ([[Walters & Skinner, 2011>>||anchor="Walters"]]).
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26 26 Staffing needs should be reviewed carefully and each role/position’s responsibilities specified clearly. This is not only important for hiring the right personnel but also important for developing a suitable training program “to ensure that the staff and managers have the knowledge and skills required to fulfill their assigned roles” ([[Paulk et al., 1993, p. 12>>||anchor="Paulk"]]).
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