This is something I keep running into, as the data I want to memorise becomes more in-depth with more layers/strands, so I’m wondering how other folk here approach this in a methodical way.
Take this an example: Native/Naturalised UK tree species and their basic taxonomy and attributes. Each has a common name, latin name and could include a number of related species within the genus. An example would be Birch, 5th in my palace after Alder, Apple, Ash and Beech (I used common names of the genus in alphabetical order as this was logical to me when I first encoded it). So Scots Pine is filed under Pine, and the 6 species Willows under just Willow.
Main Loci: Birch
Genus: Betula
Deciduous
Species:
- Common Name: Silver Birch
- Latin Name: Betula Pendula
- & other information about soil type, leaf shape, bark characteristics and buds (this is where I find the data harder and harder to layer into a given loci).
- Common Name: Downy Birch
- Latin Name: Betula pubescens
- & other information…
So how do you approach layering repetitive sub strands of data onto each loci?
I almost want to use a secondary palace for each tree species but that seems very labour intensive. Perhaps those who have database-like structures they’re trying to memorise have ideal systems here?
Another example would be a friends list; their full name, date of birth, other important dates/anniversaries, their address, their partners, kids names, kids birthdays, pets names etc etc. I have a palace for this but as it gets fuller and deeper it’s become harder to encode and keep a clear ‘gangway’ for the route I’m walking. Same for family. And Acquaintances…
Any thoughts would be hugely appreciated as I undertake more and more complex data encoding (I’ve started Portuguese vocabulary and want to expand on memorising more complex Javascript functions/concepts)
(Apologies if this has been asked often - but searching didn’t really turn up the ideals/methods I’d hoped for).




