Hi Koray, Don't you think that "Null" is not a singularity (I mean an isolated point), but the extreme value of a linear cursor we could name "validity" or "confidence".
To give a matter of fact example, I could say that : I can provide a value without any comment : I am confident in the quality level of the measurement process I can provide a value saying that an average (or poor) level of quality must be noticed when using this information I can decide not to provide a value and explain why This is close from error bars in scientific papers ; I don't mean you must provide a calculated accuracy level (it is usually not possible), but that when an information was not obtained with the usual level of precision, it should always be noticed. For example, some calculated values use measured value power 3 - you can imagine how errors are raised at a high level. So, maybe we should always provide room for a validity indicator (that would become the list of reasons for null when "flavours of null" replace the asked value). Cheers, Philippe >So my proposal in short is: >1) Examine the possible data values to be expected in a particular field: If >can be solved with a simple True/False then assign a bit. >2) If not then employ the "Essential Flavours of Null" which should appear >as a separate Data Type I believe >3) If extra contextual information is needed at the time of design or will >probably be needed in future (This requires a careful study by taking into >consideration all viewpoints: legal, epidemiological and etc.) then assign >"Knowledge-Enabled Contextual Archetype Plug-Ins" and provide mappings to >the essential ones. > >That is my "simple" solution proposal that I had been deeply thinking on for >some years! > >Best regards, > >Dr. Koray Atalag >METU Informatics Institute >Ph.D. Candidate on Information Systems > > > - If you have any questions about using this list, please send a message to d.lloyd at openehr.org
