R3.5 Request for Comment (Consistency: Temportal Consistency)

R3.5 Request for Comment
Existing Dimension: Consistency
New Underlying Concept: Temporal Consistency

With the work by D. Myers and B. Blake (2017), it has become apparent that the Consistency Dimension should include an additional Underlying Concept to measure the aspects of uniformity of values over time.

As a result of researching Reasonability, Myers and Blake created the following table (Appendix D, Authors Citing Believability and Related Dimensions). (Table only includes rows from two authors citing related concepts, and perinate cells are highlighted in green. To access the full table, see Myers/Blake 2017)

Drawing on Prat and Madnick (2008) and Loshin (2011), the following support for this new Underlying Concept is as follows:

• Prat and Madnick (2008)- In Prat and Madnick's definition of Believability, Reasonableness of data, they included a metric "Consistency" defined as, "The extent to which a data value is consistent with other values of the same data" and included two sub-types, 'Consistency over sources: a data value is possible' and 'Consistency over time: the data value is consistent with past data values'. (Table 1, Page 4).
• Loshin (2011)- Loshin identified the Reasonableness dimension and the concept of "Temporal Reasonability" defined as "New values are consistent with expectations based on previous values." (Table 8.10, Page 143). We believe that the term Consistency here is proxy to his description of the underlying consistency of the value- which drives what he calls Believability.

Therefore, the new Underlying Concept added to the Conformed Dimensions as of Release 3.5 will be:

Your input is valued and appreciated. Please direct comments to Dan Myers (dan[at]dqmatters[dot]com) or the LinkedIn group for the Conformed Dimensions of Data Quality.

References:

1. Loshin, The Practitioner’s Guide to Data Quality Improvement, Elsevier 2011.
2. Myers, Dan and Blake, Brian. “An Evaluation of the Conformed Dimensions of Data Quality in Application to an Existing Information Quality-Privacy-Trust Research Framework” in Proceedings of International Conference of Information Quality, Little Rock, AR, 2017.
3. Prat, Nicolas and Madnick, Stuart. “Measuring Data Believability: A Provenance Approach” in Proceedings of the 41^st Annual Hawaii International Conference on System Sciences, Waikoloa, HI. 2008.