Logseq as a QDA (qualitative data analysis) tool

Over the last year, I have been using Trilium for collecting web-clippings and taking notes. However, recently, I began seeking a tool like Logseq that did not rely so much on hierarchical organization (tree structures) but could rely on the application of keywords to blocks of text, in much the same way that qualitative data analysis (QDA) software works.

Though Logseq does not (yet) have the ability to add keywords to selected blocks of text, this would be a useful feature. The way I envisage this is that in one long text document, the user could add keywords to each group of ideas present in the document.

Does anyone here use Logseq, Roam, Obsidian etc as a qualitative data analysis tool? If so, what is your workflow? I’d like to explore this more.

Also, I will make a feature request that Logseq develop the ability to select sections of text and add codes that apply to that selection. The codes can later be queried to show all sections of text that have been tagged with a particular code. ie) if I am writing a document about farming, I would like to be able to code the various sections about soil productivity with the code “soil health” and sections about lack of rain or low yields with the code “drought”. Later I could query the database and ask to see all sections coded with the keyword “soil health” and/or with the keyword “drought”.

This type of QDA basic feature is missing in all note-taking applications. However, it would be exceedingly handy and undoubtedly well-used by researchers worldwide.

I’d like to hear from others who would like to see QDA functionality included in Logseq. This may help clarify an approach and build a clear feature-request. :grinning:

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The same idea. It is very important for me when I using logseq.

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I’m glad you think so too. I am wondering however why more people do not often request this feature. Its incredibly useful- at least as useful (and to me far more useful) than adding keywords to pages, or adding several sentences to a block like the method used in Logseq, Roam, Obsidian etc.

If others would like to see QDA style coding/keywording of selected text, please make a note here and in the feature request section.

A couple of thoughts (complete Logseq noob here, so apologies for not being able to offer anything of value…):

  • I’m really curious as to whether there are any QDA practices/frameworks/principles that could be cross-purposed for insight generation more generally in learning or knowledge management? I’m aware that I could be attempting to conflate two different sets of desired outcomes here, bearing in mind that I know little-to-nothing about QDA…
  • I’m trying to fully understand your feature request as a way of refining my own understanding of what Logseq can/‘t do: how does what you’re asking for differ from adding tags to blocks, perhaps making use of aliases if the titles for those tags/keywords are particularly long? Or are you talking about displaying this kind of block-level tagging differently from the way it might be done now?
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