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Brian von Konsky 20
Data Management (Semester 2 2020 – INT[1]) Rubrics Edit Rubric Edit Mode is: •ON ?
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* Name Description
Report on Data Management Plan (S2/2020)
Character count 0
RUBRIC DETAIL
The Rubric Grid lists Criteria (rows) for measuring Levels of Achievement (columns)
Add Row Add Column Rubric Type: Percentage Range Levels of Achievement
Show Criteria Weight
Criteria Below Below Expectations (Fail) Meets Expectations (Pass) Meets Expectations (Credit) Exceeds Expectations (Distinction)
Exceeds Expectations (High Distinction)
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Criteria 1. Approach
Criteria 2. Data Volume, Velocity, Veracity
Criteria 3. Data lifecycle: acquisition, cleaning, integration, storage, publishing, retirement
Levels of Achievement
Below Below Expectations (Fail)
Meets Expectations (Pass)
Meets Expectations (Credit)
Exceeds Expectations (Distinction)
Exceeds Expectations (High Distinction)
Per cent 0.00 to 49.00
Per cent 70.00
The approach to address the scenario is missing or insufficient.
The approach demonstrates an understanding of data management issues but is not specific to the given scenario.
The approach is likely to address the given scenario.
The approach includes novel insights that were not included in the description of the original scenario.
The approach to the data management scenario is of a high professional standard.
Per cent 0.00
Per cent 70.00
No significant demonstration of data volume, velocity, or veracity issues in the given scenario.
Data volume, velocity, and veracity issues are mentioned but not in the context of the given scenario.
Data volume, velocity, and veracity issues are discussed in the context of the given scenario.
Data volume, velocity, and veracity is measured, simulated, or estimated and used in the context of the data management plan.
The treatment of data volume, velocity, and veracity exceeds expectations and is of a high professional standard.
Per cent 0.00
Per cent 70.00
No significant demonstration of data lifecycle issues.
Data lifecycle issues are discussed in general but not in the context of the given scenario.
Data lifecycle issues are discussed in the context of the given scenario.
Data lifecycle issues are thoroughly addressed for the given scenario as part of a comprehensive data management plan.
The management of lifecycle issues is of a high professional standard.
Criteria 4. Data quality, security, privacy considerations, including
structral and descriptive metadata
20.00 % Criteria 5.
Written report
Levels of Achievement
Below Below Expectations (Fail)
Meets Expectations (Pass)
Meets Expectations (Credit)
Exceeds Expectations (Distinction)
Exceeds Expectations (High Distinction)
Per cent 0.00 to 49.00
No significant consideration of data quality, security, or privacy considerations.
Data quality, security and privacy considerations are discussed in general but not in the context of the given scenario.
Data quality, security, and privacy are discussed in the context of the given scenario.
Data quality, security, and privacy are thoroughly addressed for the given scenario as part of a comprehensive data management plan.
The management of data quality, security, and privacy issues is of a high high professional standard.
Per cent 0.00
Did not use language that conveys meaning to readers with sufficient clarity and includes numerous errors.
Uses language sufficiently well to convey basic meaning although errors reduce effectiveness of communication.
Uses language that generally conveys meaning to readers with clarity although writing may include some errors.
Uses language that effectively conveys meaning to readers with clarity. Any errors which occur do not reduce the effectiveness of communication.
Uses language that skilfully and effectively communicates meaning to readers with clarity and fluency, and is virtually error free.
Total Weight: 100.00% Balance Weights
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