Tana - Increase Discoverability with Tags, Fields, and Queries
In this article, I am going to introduce you to the concept of discoverability, why it is important, and I will give you some tips on how to increase it through Tana's primitives.
Tana is a PKM tool, available invite-only, that has been shaking the community for months now. It is trying to be a general-purpose tool to manage your knowledge, tasks, and projects through a flexible data model and a set of constructs that make it very powerful. If you are interested to know more about the tool, I have expressed my opinions about it in a previous article (available here).
The scope of this article is to talk about how we can increase the discoverability of our knowledge by leveraging two powerful constructs of Tana, namely fields and queries. These two constructs are what enable Tana to be so powerful. Let's now start with some context.
The Idea of Discoverability
Discoverability sounds like a buzzword but in reality, it is nothing complicated. It is defined online in the following way:
Discoverability is the degree to which something can be discovered through a process of searching.
While I do like the simplicity of this definition, in the context of PKM tools I would slightly reframe it as follows:
Discoverability is the quality possessed by elements of knowledge that enables them to be discovered with the least amount of information and context.
To explain it in simpler terms it means that when we have achieved discoverability in our knowledge base we are able to look for information with the least amount of details possible, which is great.
I have also decided to associate discoverability with the elements of knowledge because I think that we should be able to search for information in the smallest possible form in which it is encoded (e.g., note, block, or even word). Of course, what an element of knowledge is, differs from tool to tool. For example, tools with node-based data models have the benefit of having very granular elements of knowledge, whereas a markdown-based tool will have less granularity.
One important thing to note is that achieving discoverability is hard and depends on multiple factors such as the complexity of the domain, the data model of the tool, and most importantly, the features of the tool. In addition, increasing discoverability is an ongoing process that should be refined based on the access patterns to your data.