A Capability Maturity Model for Research Data Management
CMM for RDM » 2. Data acquisition, processing and quality assurance
Last modified by Arden Kirkland on 2014/05/11 15:33
From version 34.1
edited by Arden Kirkland
on 2013/11/06 07:21
To version 35.1
edited by Arden Kirkland
on 2013/11/06 07:48
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3 3 //Goal: Reliably capture scientific data in a way that facilitates use, preservation and reuse.//
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5 -(% style="font-size: 13.63636302947998px;" %)The first stage in the data lifecycle is to collect the data along with data documentation. (% style="font-size: 14px;" %)Data collection is the process of capturing observations of the world—physical, biological, behavioural or social—in a form that can be used for analysis. Observations are of some property or properties (e.g., presence or absence, mass, behaviour, attitude) of one or more units of observation (e.g., an organism, sample, group or organization). Data documentation means the description created by the scientist of how the data were collected (e.g., conditions, parameters, techniques, etc.), the initial processing of the data and of the data themselves (e.g., formats, units, etc.). An important subgoal of this stage is to ensure the quality of the data and the data documentation as they are captured and processed.
5 +The first stage in the data lifecycle is to collect the data along with data documentation. Data collection is the process of capturing observations of the world—physical, biological, behavioural or social—in a form that can be used for analysis. Observations are of some property or properties (e.g., presence or absence, mass, behaviour, attitude) of one or more units of observation (e.g., an organism, sample, group or organization). Data documentation means the description created by the scientist of how the data were collected (e.g., conditions, parameters, techniques, etc.), the initial processing of the data and of the data themselves (e.g., formats, units, etc.). An important subgoal of this stage is to ensure the quality of the data and the data documentation as they are captured and processed.
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7 7 Given a phenomenon of interest, it may be possible to measure the properties of all of the relevant observational units (e.g., the single case being studied in depth or all of the organisms in an experiment). However, as the scale and number of units in the study increases, it may be infeasible to measure more than a fraction of the units, requiring some process for sampling, i.e., for choosing which units to measure. Temporally, measurements may be one-off, i.e., at a single point in time, or repeated at more or less regular intervals, with greater or finer temporal spacing. Finally, measurement might be made simultaneously of multiple properties of each unit of observation, or of only a few.
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