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

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7 7 = 1.2.1 Develop and implement a budget =
8 8
9 9 Effective data management incurs costs ([[Hale et al, 2003>>||anchor="Hale"]]). Budgeting for data management helps ensure allotment of sufficient financial resources to support data management activities.
10 -Budget considerations vary with the type, scope, scale, and timeframe of the data management context. Those who collect data need adequate financial resources to manage local data during the life cycle of the project ([[DataOne, n.d.-a>>||anchor="DataONE-a"]]; [[Hale et al., 2003>>||anchor="Hale"]]). Local data management costs might include data management personnel, database systems, servers, networks, and security for project data that is shared over a network ([[Hale et al., 2003>>||anchor="Hale"]]).
10 +Budget considerations vary with the type, scope, scale, and timeframe of the data management context. Those who collect data need adequate financial resources to manage local data during the life cycle of the project ([[DataOne, 2011a>>||anchor="DataONE-a"]]; [[Hale et al., 2003>>||anchor="Hale"]]). Local data management costs might include data management personnel, database systems, servers, networks, and security for project data that is shared over a network ([[Hale et al., 2003>>||anchor="Hale"]]).
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12 12 Another type of data management cost is synthesis and integration of data, and collaboration necessary to support this synthesis ([[Hale et al., 2003>>||anchor="Hale"]]). The creation of metadata using a standardized metadata format is a cost for data that is publically shared beyond the scope of a research project.
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47 47
48 48 Tools for RDM include off-the-shelf kind, such as data repository management systems and metadata editors created for specific standards, and the those developed in-house. Before deciding whether to adopt an off-the-shelf tool or develop one in-house, a comprehensive analysis should be conducted to understand not only the local requirements but also the need for links to community data management infrastructure and standards. This means that tools adopted or developed should consider key functions for immediate data management needs such as storage, annotation, organization, and discovery and at the same time the "staging" functions for effective data deposition and dissemination in community, national, and international data repositories.
49 49
50 -More often than not software tools for RDM have been developed ([[Michener, 2006>>||anchor="Michener"]]). Adoption of such tools means adopting the mechanisms to systematically capture the integration process ([[DataONE, n.d.-b>>||anchor="DataONE-b"]]). RDM projects vary in scope and nature as the data they deal with change from discipline to discipline and from project to project. Whether tools are adopted or developed for ad hoc or long-term needs, support for researchers to use these tools should be an integral part of the tool adoption/development process ([[Mayernik et al., 2011>>||anchor="Mayernik"]]).
50 +More often than not software tools for RDM have been developed ([[Michener, 2006>>||anchor="Michener"]]). Adoption of such tools means adopting the mechanisms to systematically capture the integration process ([[DataONE, 2011b>>||anchor="DataONE-b"]]). RDM projects vary in scope and nature as the data they deal with change from discipline to discipline and from project to project. Whether tools are adopted or developed for ad hoc or long-term needs, support for researchers to use these tools should be an integral part of the tool adoption/development process ([[Mayernik et al., 2011>>||anchor="Mayernik"]]).
51 51
52 52 = 1.2.6 Establish a data management plan =
53 53
54 -A data management plan (DMP) documents the definitions, procedures, methods, and best practices for a project or organization to maintain a consistent practice of RDM. Careful planning for data management before you begin your research and throughout the data's life cycle is essential ([[DataONE, n.d.-c>>||anchor="DataONE-c"]]) because it can increase project efficiency and optimize the reliability of the data that are collected by minimizing errors.
54 +A data management plan (DMP) documents the definitions, procedures, methods, and best practices for a project or organization to maintain a consistent practice of RDM. Careful planning for data management before you begin your research and throughout the data's life cycle is essential ([[DataONE, 2011c>>||anchor="DataONE-c"]]) because it can increase project efficiency and optimize the reliability of the data that are collected by minimizing errors.
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56 56 The most common DMPs are the kind prepared as part of a grant proposal because of the mandate from funding agencies such as the (% style="font-size: 14px; line-height: normal;" %)U.S.(% style="font-size: 14px;" %)National Science Foundation (NSF) and the Institute for Museum and Library Services (IMLS). Examples of this type of DMPs can be found from funding agencies' websites as well as many research universities' websites, e.g., the Research Cyberinfrastructure (RCI) at UC San Diego provides a list of DMP samples for major NSF disciplinaries ([[http:~~/~~/rci.ucsd.edu/dmp/examples.html>>url:http://rci.ucsd.edu/dmp/examples.html||rel="__blank"]]).
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66 66 Brown, D.A, Brady, P.R., Dietz, A., Cao, J., Johnson, B., & McNabb, J. (2006). A case study on the use of workflow technologies for scientific analysis: Gravitationalwave data analysis, in I.J. Taylor, E. Deelman, D. Gannon, and M.S. Shields(Eds.), Workflows for e-Science, chapter 5, pp. 41–61. Berlin: Springer-Verlag.
67 67
68 68 {{id name="DataONE-a"/}}
69 -DataONE. (n.d.-a). Define roles and assign responsibilities for data management. Retrieved from [[https:~~/~~/www.dataone.org/best-practices/define-roles-and-assign-responsibilities-data-management>>url:https://www.dataone.org/best-practices/define-roles-and-assign-responsibilities-data-management||rel="__blank"]]
69 +DataONE. (2011a). Define roles and assign responsibilities for data management. Retrieved from [[https:~~/~~/www.dataone.org/best-practices/define-roles-and-assign-responsibilities-data-management>>url:https://www.dataone.org/best-practices/define-roles-and-assign-responsibilities-data-management||rel="__blank"]]
70 70
71 71 {{id name="DataONE-b"/}}
72 -DataONE. (n.d.-b). Document the integration of multiple datasets. Retrieved from [[https:~~/~~/www.dataone.org/best-practices/document-integration-multiple-datasets>>url:https://www.dataone.org/best-practices/document-integration-multiple-datasets||rel="__blank"]]
72 +DataONE. (2011b). Document the integration of multiple datasets. Retrieved from [[https:~~/~~/www.dataone.org/best-practices/document-integration-multiple-datasets>>url:https://www.dataone.org/best-practices/document-integration-multiple-datasets||rel="__blank"]]
73 73
74 74 {{id name="DataONE-c"/}}
75 -DataONE. (n.d.-c). Plan data management early in your project. Retrieved from [[https:~~/~~/www.dataone.org/best-practices/plan-data-management-early-your-project>>url:https://www.dataone.org/best-practices/plan-data-management-early-your-project||rel="__blank"]]
75 +DataONE. (2011c). Plan data management early in your project. Retrieved from [[https:~~/~~/www.dataone.org/best-practices/plan-data-management-early-your-project>>url:https://www.dataone.org/best-practices/plan-data-management-early-your-project||rel="__blank"]]
76 76
77 77 {{id name="Hale"/}}
78 78 Hale, S. S., Miglarese, A. H., Bradley, M. P., Belton, T. J., Cooper, L. D., Frame, M. T., … Peterjohn, B. G. (2003). Managing Troubled Data: Coastal Data Partnerships Smooth Data Integration. //Environmental Monitoring and Assessment//, //81//(1-3), 133–148. doi:10.1023/A:1021372923589. Retrieved from [[http:~~/~~/link.springer.com/article/10.1023%2FA%3A1021372923589>>url:http://link.springer.com/article/10.1023%2FA%3A1021372923589||rel="__blank"]]

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