Overview - AutoFill Keyword Sets - English - Foundation 22.1 - OnBase - Essential - Premier - Standard - external - Standard - Essential - Premier

AutoFill Keyword Sets

Platform
OnBase
Product
AutoFill Keyword Sets
Release
Foundation 22.1
License
Standard
Essential
Premier

When importing data set values from a text file into OnBase, depending on the data contained within the file, it might be possible to configure External AutoFill Keyword Sets for indexing purposes instead of Cascading Data Sets. Using External AutoFill Keyword Sets can reduce the number of keystrokes and mouse clicks when indexing, thus streamlining the process.

To configure an External AutoFill Keyword Set to function in place of a Cascading Data Set, modify each data set in the text file by adding to the data set (and to the corresponding database table) an extra value that combines successive values in the data set up to, but not including, the last value. Then set this combined value as the Primary Keyword of the External AutoFill Keyword Set using a SQL Select String query.

When configured in this fashion, the combined value functions as each layer of filtering would function in a Cascading Data Set. Because the combined value contains all of the individual values that would be filtered, and because it is used to trigger the AutoFill, the combined value would simply need to be entered to populate all corresponding values in the data set. Also, because the combined value does not correspond to any OnBase Keyword Type, it will not be populated in any of the Keyword fields once the AutoFill is triggered. Depending on the length of the combined value, however, you might have to increase the maximum length of the Primary Keyword Type to allow the combined value to be entered to trigger the AutoFill.

Note:

In some scenarios, Cascading Data Sets might still be preferable to External AutoFill Keyword Sets. If, for instance, the data sets consist of very long and/or complex values, entering the combined value could be time-consuming and prone to error. When analyzing the values in your data sets, carefully consider the pros and cons of each indexing method to determine which method is best for your solution.