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2 Framework Foundation: Data States and Associated Activities
Pages 24-32

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From page 24...
... The committee calls these environments "data states" and recognizes that the data may move from one state to another in a nonlinear manner. These data states were conceptualized by the committee to communicate the characteristics of different environments with different purposes, and different data storage and preservation costs.
From page 25...
... Where data are complex, confidential, or very large, it may be a platform for controlling access and may also provide support for analyzing and processing data. ●  tate 3: A long-term preservation platform in which content is preserved across changes in gov S ernance, assessment of data value, and technology.
From page 26...
... STATE 1: THE PRIMARY RESEARCH AND DATA MANAGEMENT ENVIRONMENT The first state is the form that the data take in the primary research environment. The data are actively captured in this environment as they are created -- for example, as digital sampling of electrical current, image and voice signals, text, or binary data.
From page 27...
... Transform data and algorithms as necessary in line manager, software engineer, with repository/archive submission requirements. data wrangler, research domain curator STATE 2: THE ACTIVE REPOSITORY AND PLATFORM The second state is the active repository and platform.
From page 28...
... Provide a sandbox for researchers to test data sets for Research domain curator, Processes involved in supporting compliance with repository standards. research domain project the researcher in ensuring 2.
From page 29...
... If applicable, confirm identity or eligibility of user Software engineer, IT security Services and functions for making as a qualified user (e.g., IRB approval, Collaborative specialist, IT project manager, the data available to users Institutional Training Initiative training)
From page 30...
... Those managing a State 2 information resource may make decisions related to a State 3 resource, and the movement from State 2 to State 3 could potentially be seamless. Following good archival practice, State 2 resource managers may automatically create preservation copies of the data as they are accessioned, or those data may be stored in a preservation format.
From page 31...
... and experience of individual committee members, personnel salaries often account for the largest expenditures in data preservation, curation, and access. Appendix C provides data drawn from occupational employment statistics for the relative salary levels shown in Table 2.4.
From page 32...
... 32 LIFE-CYCLE DECISIONS FOR BIOMEDICAL DATA TABLE 2.4  Personnel Categories with Definitions and Relative Salary Levels Relative Salary Personnel Definition Level Administrative staff Provides a variety of support functions for a project or program M Communication specialist Trained in effective methods for publicizing and disseminating information to a M broad audience Curator Often an archivist, trained in methods to describe and add value to data M Data librarian Trained in the technical aspects of data management M Data scientist Trained in quantitative methods for collecting, analyzing, and interpreting data H Data wrangler Trained in methods for transforming data from one format into another and data H cleansing for improved data interpretation Education specialist Trained in design, modification, and implementation of training materials relevant M to data management and use Facilities manager Oversees and handles matters relating to the physical environment M Informatician Trained in biology, medicine, or other health-related field and in quantitative VH methods for collecting, analyzing, and interpreting data in those fields IT project manager Responsible for planning, executing, and overseeing a project; trained IT H specialist IT security specialist Trained in methods to protect IT systems against inadvertent or malicious attacks VH IT systems engineer Trained in implementing, monitoring, and maintaining IT systems VH Metadata librarian Trained in the technical aspects of data standards M Policy specialist Trained in relevant ethical, legal, and regulatory requirements H Project manager Responsible for planning, executing, and overseeing a project M Records management specialist Often an archivist, trained in managing data throughout the data life cycle M Research domain curator Domain expert trained in methods to describe and add value to data H Research domain project manager Domain expert responsible for planning, executing, and overseeing a project H Researcher An individual who generates potentially shareable data while conducting research H Senior staff Has a supervisory and decision-making role within an organization or program VH Software engineer Trained in the design, implementation, testing, evaluation, operation, and VH maintenance of computer programs or databases NOTE: H, high; M, medium; VH, very high.


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