> For the complete documentation index, see [llms.txt](https://docs.natsec.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.natsec.io/about/elements/data/tags.md). # Tags {% hint style="warning" %} The idea of **`Tags`** is one we feel is important, but right now they are sort-of all over the place and we need to find a good balance between the [Google Sheets](/learning/tools/google-sheets.md) approach and something much more robust. We think [Kumu](/learning/tools/kumu.md) offers some options with JSON blueprints, but need to explore further. {% endhint %} `Tags` allow for the easy filtering of [Entities](/about/elements/data/entities.md) based on a single field with multiple keywords (e.g. `Kessel Run` is an `Entity` that might have the `Tags` `Military` `Air Force` `Software`, and so on. By clicking on or filtering by a `Tag` one can easily see all the `Entities` associated with it in the [Data](/about/elements/data.md), [Graph](/about/elements/graph.md), [Map](/about/elements/map.md), and [Timeline](/about/elements/timeline.md). ### Problems with Tags Unfortunately, executing this in [Google Sheets](/learning/tools/google-sheets.md) using [Kumu](/learning/tools/kumu.md) is sort-of a challenge because: 1. [Kumu](/learning/tools/kumu.md) uses `|` connectors in a single field to separate `Tags` (which means you cannot run a simple `Data Validation` rule against a list of keywords like we do with `Labels`, `Categories`, and `Connections`. 2. The whole idea of `Tags` depends on a common set of terms... but how do you know whether to use `Software` or `DevSecOps` or `Technology` or something else? Who makes these decisions and how do the uninitiated learn? (NOTE: We will keep this page updated with our hypotheses and approaches). ### Future Plans for Tags We are very open to ideas and existing best practices here, so please [Contact Us](/about/contact-us.md) if you have ideas or examples to share! We think our [Partners](/about/support/partners.md) may be able to help with this as well. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.natsec.io/about/elements/data/tags.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.