response on keyword search

keyword search

the other thread has gotten extremely cluttered so it’s better to respond here

keyword search is basically the same as tagging/classing/metadata

what this seems to basically do is:

  1. create an ‘idea’

  2. the idea could be a character or a cure for cancer, and basically anything

  3. the ‘keyword’ would be the term/word for the idea

  4. and searching for the keyword, you can find all instances/cases of that idea

it’s unclear / unknown to me why you would want to do this

one type/kind of tagging/classing/metadata/keywords is:

  • ‘label/coloring’ - this is basically color-coding

  • one example is ‘which location is featured in the scene/chapter’

  • but why would that be a helpful thing to do?

one type/kind of tagging/classing/metadata/keywords is:

  • ‘status’ for each info/content (this personally wont help me cos to me something is either ‘done’ or ‘not’)

tagging/classing/metadata/keywords applies to many things on the web and in life and in the universe

but i dont know what are the common cases for how this is commonly helpful

im not sure if this counts as the most helpful things to most users, but this is what i responded to

Scrivener works best when you break your project into many small chunks — this could be subsections in a non-fiction document, or individual scenes within chapters in a novel. This way you work on the words of each individual ‘chunk’ while still retaining the ability at any time to rearrange the order of the chunks.

Keywords (and the other metadata) allow you to classify each chunk in several different ways: this is important because it allows you to form a Collection (the word Scrivener uses) of those documents which have certain keywords. These collections can be saved and are dynamic, so that you can add keywords to any document and they will automatically be added to the relevant Collection in future (no need to search again). The documents within a collection can be read and edited as a single virtual document using the feature called Scrivenings.

Taken together, these features are the basis of what makes Scrivener so much more powerful than Word. To use the example you gave elsewhere of a project about cancer.

Say your project has 100 sections and subsections dealing with cancer, its various forms and its cures. In most word processors, whichever way your structure your outline, you’re stuck with that outline as you write. For example, you outline deals with each form of cancer one after another. That means you can only view it in ‘Cancer form’ order and the cures are spread out within the whole document. Or your outline could by ‘Cure’, in which case you’ can’t see all the various types of cancer as a whole.

There’s no such problem in Scrivener: all you would do is assign the keyword ‘throat’ to sections dealing with throat cancer, ‘lung’ to those dealing with lung cancer and so on. You would then do similarly with sections dealing with cures (‘chemotherapy’, ‘homeopathic’ etc).

Then, when you want to work on all the sections dealing with chemotherapy — even if the whole document is actually structured by cancer type — all you need to do is to search on the keyword chemotherapy and you’ll see them all in one long virtual document and you can work on the subject of chemotherapy as a whole, which means that it’s far easier to pick up inconsistencies and to know whether you’ve covered the whole subject properly. Doing this doesn’t affect the publication order of the chunks — it just brings them together temporarily to work on.

And you can do this for any combination of keywords and other metadata. If you wanted to extend this, say to including geographical data, just add a suitable keyword to the relevant sections; then you can see all the chunks dealing with chemotherapy for bowel cancer in the UK together.

There are many reasons why Scrivener is so much more useful than Word for long form writing but what I’ve described above is probably the main one for most people.