Your prized collection of 19th Century marriage records have a lot of great data. There’s the bride’s given name, the bride’s maiden name, the groom’s given name, the groom’s surname, the bride’s father’s given name, the bride’s mother’s given name, the bride’s mother’s maiden name, the bride’s surname from a previous marriage, the marriage officiant’s surname…
Ugh, wait, how do you search through all those different kinds of surname fields or given name fields at the same time? Making a standalone database with MySQL and PHP might work, but it would take a lot of coding. Steve Morse’s One-Step Tools are wonderful, but you still have to search each field individually. And what if you want to loop in other kinds of records in the future to make a multi-database system?
Not to worry; LeafSeek understands that record fields can be both standalone and grouped with a certain field type too. So you can search across all surnames in a dataset at once, or just within a specific sub-section like the bride’s maiden name. Find every “Smith” in your data with one easy search, no matter how they were originally attached to the record.
The same thing applies to other kinds of common record fields, like towns. So if your marriage record was recorded in Duluth, but was performed in Fond du Lac, with a bride from Carlton, a groom from Hermantown, and an officiant from Superior, all of those different columns of town data can be understood to be part of the same data type “towns”, and all can be searchable as such–without having to edit your original data.