ISO25012 Sub-characteristic | Data Metrics |
Accuracy | · Data Error Rate: Percentage of data records that contain errors relative to the total number of data records. · Percentage of correct values: Percentage of data records that contain correct values relative to the total number of data records. · Total Data Loss Rate: Percentage of lost or unrecorded data records relative to the total number of data records. · Average Deviation: The average amount of deviation between the data values and the correct values. |
Comprehension | · Simplicity of data structure: This can be measured as the percentage of data elements that are straightforwardly understood without additional explanation or interpretation. · Data consistency: Data consistency refers to the extent to which related pieces of data are coherent and consistent. · Quality of documentation: This can be assessed by the completeness, accuracy and comprehensibility of the documentation accompanying the data. · Clarity of tags and metadata: This can be assessed based on how easily one can understand the meaning of the data based on the tags and metadata that accompany it. · Clarity of units of measurement: This refers to the ease with which users can understand the units of measurement used for the data. |
Consistency | · Inconsistency rate: This can be measured as the percentage of data that is not consistent or does not follow the rules or specifications that have been set. · Deviation from the norm: This can be calculated as the average deviation of the data from a certain norm or standard. · Number of Duplicates: The number of repeated entries in the data set. · Value Variance: The variance of the values of the data provided, which may indicate inconsistency if the values deviate greatly from the expected value. |
Acceptability | · User satisfaction rate: This can be measured using questionnaires, ratings or reviews conducted with users of the data. · Task execution success rate: Percentage of tasks that can be completed successfully using the data. · Data rejection rate: Percentage of data that is rejected or not used by users due to insufficiency, inaccuracy, or other quality issues. · Rate of data quality reports: Percentage of reports made about data quality, such as errors, inconsistencies, or other problems. |
Reliability | · Validity Rate: It can be calculated as the percentage of data that meets the validity criteria set. For example, the validity of email addresses or phone numbers. · Percentage of Missing Values: It can be calculated as the percentage of missing or unavailable data. · Deviation from the predicted variance: This can be calculated as the deviation of the observed data from the predicted variance based on the estimates or predictions. · Retry Failures: Number of times data is not reliably retried under different conditions or to different users. |
Efficiency | · Return on Investment (ROI): This can be calculated based on the value or return achieved from using the data compared to the cost of accessing, processing, maintaining, and analyzing the data. · Performance Rate: It can be measured as the percentage of successful tasks performed using the data relative to the total number of tasks. · Processing Time: The time required to process or analyze the data. · Response Time: The time it takes to get results or information from the data. |