Context charting: a visual research and note-taking method for the age of AI

In an era where artificial intelligence significantly influences how we gather, analyze, and employ information, a new method emerges, reshaping the landscape of research, note-taking, and content creation: context charting. This method is particularly advantageous for content writers, researchers, and entrepreneurs who seek to maintain an edge in their domains by synthesizing ever-expanding information streams into coherent narratives or actionable insights. Context charting offers a structured approach to visually represent and explore the complex web of ideas, facts, information sources, and their interconnections, much like a map guides a journey through unfamiliar terrain.

Origins of context charting

Context charting is an evolution of established visual methods, with its roots embedded in traditional mind mapping and concept mapping. These methods originated before AI (I mean LLMs like ChatGPT) and even before the internet as we know it today. Although human thinking remains the same, both the internet and AI significantly impact everything we do, and visual methods need an update to stay functional. Context charting brings such an update.

Context charting as a visual method enhanced beyond mind and concept mapping

Mind mapping and concept mapping have long been cherished in educational and professional settings. Mind mapping serves primarily for brainstorming, capturing spontaneous ideas through a non-linear format that encourages free thinking. Concept mapping, on the other hand, focuses on delineating the relationships between concepts or keywords, offering a structured visualization of knowledge. However, both methods have limitations when applied to the multifaceted tasks of content creation and research that require linking information to varied sources.

In contrast, context charting transcends these limitations by capturing isolated ideas or concepts and weaving them with their sources, as well as by relaxing the rigidity that is not needed, thanks to the assistance of AI. This method enlists the support of AI and search tools to enhance the discovery and association of relevant information, optimizing how knowledge is organized and utilized.

The necessity for a comprehensive method

The need for a method that synthesizes ideas and sources into a cohesive framework is increasingly urgent. In a digital world where information is abundant yet fleeting, especially when interfacing with AI-powered search engines, the ability to capture, access, and integrate comprehensive data efficiently is invaluable. Context charting fulfills this need by categorizing each item on the map—be it a keyword, topic, article, question, or heading—thereby enriching the layers of understanding associated with each note or idea. This is useful for human users and even more for AI assistants.

Inspiration from Zettelkasten

Context charting also draws inspiration from Zettelkasten, a method rooted in the art of connecting notes. In Zettelkasten, each note is interlinked with others, creating a dense network of knowledge that facilitates exploratory learning and idea development. Mirroring this, context charting encourages the linking of ideas with their sources. It aligns them with keywords used to discover or understand them, creating an easily backtrackable research roadmap.

The origin of the term “context charting”

While the name “context mapping” would be more fitting by keeping the mapping part as in mind mapping and concept mapping, "context mapping" is already used for the method businesses employ to identify and understand relationships within their ecosystem, whether it be customer behavior patterns, market dynamics, or internal process linkages. It helps organizations make informed decisions by visualizing complex data in comprehensible formats. Hence we came up with a variation. The "charting" is, after all, even more fitting, as it referrs to creating a map of an uncharted territory, a previously uncharted connection of ideas and sources. And since the result of charting is still a map, we keep the term "context map" for the result of context charting.

The use cases of context charting

Context charting caters to a variety of scenarios, offering unique advantages wherever there is a need for in-depth research, insight generation, and knowledge dissemination.

Research and content creation

For scientific research and content creation, context charting acts as a tool for systematically organizing vast amounts of information. Researchers can track how various findings intersect and influence each other, while content writers can map out the narrative framework of their articles, ensuring a logical flow of information and making the progress from research to writing an effortless step.

Context charting can be especially useful to content marketers, to those who plan the overall structure of blogs, websites, etc.

Learning, training, and teaching

Context charting enhances learning in educational settings by enabling students to visually organize and connect learning materials. It serves as a tool for instructors to map out lesson plans in a manner that highlights thematic connections and learning paths.

Industry tracking and development

Entrepreneurs and industry professionals can use context charting to stay abreast of new developments. By organizing the gathering of industry insights, trend analysis, and competitive intelligence, they can visualize potential opportunities and threats.

Enhanced brainstorming

Traditional brainstorming receives a contextual upgrade through context charting. By linking each idea to relevant topics and sources, it facilitates the identification of underlying patterns and relationships, leading to more innovative and grounded results.

The basic elements of context charting

Whiteboard

The central point of context charting is the whiteboard, where you gather and organize all items in a context map. An important rule about the whiteboard is that there are no rules except for one - every item should have a type assigned and the types should be distinguished by colors, shapes or icons. The structure of the whiteboard is up to you - whatever works, use it - link items, put them in lists, use colors... Or just keep everything in random chaos if that suits you.

Item types

An item can have many forms: a single word, phrase, sentence, or whole paragraph. It can be a link or reference to an external article, an image, video, or other file attached to the map.

Regardless of its form, whenever you add an item to the map, you should assign it a role it will have in the map's context.

Item types are essential not just for you but also for anyone else who will work with the context map. That someone will often be an AI assistant for whom item types are fundamental.

The exact set of item types may depend on the use case. Here is a set designed for content creation, which can, however, fit most other use cases:

• Topic: something you want to talk about in the content. It can also be a fact or an idea.
• Keyword: a word or phrase you want to mention in the content.
• Question: something you want to answer.
• Heading: a part of the content structure you want to create.
• Article: any external source you want to cite or use - it can be a web page, social media post, video, PDF...
• Note: (or stickie) metadata, notes and comments about the items on your map. Everything that is not supposed to be a direct part of the context and the resulting content.

Search & AI sources

Even though we all already use web search and AI assistants whenever possible, they are an explicit key component of context charting because you can't create a proper context without checking existing information.

There are two ways or directions of using external sources for context charting: broadening the scope and deepening the understanding. You can use web search, AI assistants, or specialized tools like keyword research tools to find related topics and keywords and include those in your context map if it makes it more comprehensive.

Then, you can research existing content (or consult AI) to learn about topics in the context you know less about or find supporting evidence for your claims coming from your expertise.

The basic steps of context charting

Creating an effective context map involves a systematic process that brings clarity and depth to the researched or brainstormed topics. Let's look at it with a running example where the goal is to write an article about the Lord of the Rings' Gandalf backstory and motivation.

Step 1: Define your focus question and goal

The initial step in context charting is clearly articulating the focus question you aim to explore. This question serves as the foundation of your map, guiding the collection and organization of related ideas, topics, and sources. It should be based on the goal you are currently trying to achieve.

Step 2: Categorize

Depending on your goal, you should choose the set of types for items you will be adding to the map. Using item types helps you and understand the role of each piece of information you add to the map. It makes the map easier to read and to transform it into AI prompts. We have shown an example set of item types above.

Step 3: Brain dump: dump all you know - related to the question

Begin by transferring all pre-existing ideas, topics, keywords, and related questions relevant to your focus question onto a whiteboard. This brainstorming phase captures the initial breadth of your knowledge, gives you a starting point on what to research, and helps you link any new findings back to what you know, following the meaningful learning best practices. Don't forget to set the item type for every new item.

Step 4: Expand with suggestions and search

Enrich your map by using external sources to surface additional topics, keywords, and questions. This is crucial for expanding the horizon of your research and ensuring that your map covers the whole context. The basic idea is to retrieve suggestions of related items that might fit your context map, browse them, and assess if they actually fit your map. If they fit, add them with a proper item type set. The only other important thing is to stop expanding your context map at some point. Your focus question helps with that - if your context map is big enough to answer the question with respect to your audience or use case, you are good to go.

The suggestion sources you use depend on your goal, but there are some general ones that fit any use case.

The obvious is using your favorite GPT AI chat tool. You can give them your focus question and ask for related topics or keywords.

Another obvious source is Google. Although it's designed more for answering questions than looking for related topics, you can still use its People also Ask feature. And, of course, you can find related topics by actually reading the content found by Google, but that's time-consuming.

A more old-school but still valid source is Wikipedia. Thanks to its comprehensive linking, it allows you to start from the core topic related to your question and checking all the outgoing links that might be relevant in your context.

Then, there are specialized tools, especially keyword research tools like SemRUSH, AHREFs, or SpyFu. Most of them allow searching for related keywords, and some even search for generalized related topics.

Organizing as you go

Organize the items on your whiteboard by clustering closely related ideas. This step is pivotal in uncovering hidden relationships and starting to bring structure to the map. Aim to identify and name groups of related items. That will help you identify patterns and help you with further understanding. If an important relationship spans across distant groups, represent it with a link.

You will probably organize your context map iteratively throughout the context expansion and research phases. Every time you feel the map became too cluttered, spend some time organizing it.

However, remember that the amount of organization and structuring depends on your thinking style - you don't need to organize much if you don't like or need it.

There is only one actually important rule for organizing items: keep more useful items separate from the less useful ones. As you build your context map, you will usually gather more items than needed and you will need to decide which of them you will use in your current content piece (or current learning session, current project or whatever your use case is) and which of them you leave for later. A simple way is to drag the "in use" items to the right side of the whiteboard and leave the rest on the left side.

Search for sources

At this stage, integrate sources—articles, blogs, podcasts, videos, etc.—into your context map. Each source should be represented as a unique item linked to the related topics or questions it elaborates upon. Include the search queries used to find these sources to maintain the research path. It is important to be able to back-track and prevent redundant searches.

There are two main goals of finding sources - to gain an understanding of the topics you need to answer the focus question and to support your own claims.

The context map suggests what to search for

You can look at the items on your context map as a set of possible search queries. Start with the most intriguing ones. If you find a resource that answers or covers multiple items, reorganize your map accordingly. It is simple but extremely powerful feature of context map - it can guide and track your research at the same time.

Extract key messages

Optionally, as you integrate each source, extract key messages pertinent to your focus question and add these as separate items on your map. This distillation of insights ensures that the map captures information and crystallizes significant findings that directly inform your original focus.

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Step 5: Reduce to fit your current goal

Once you expand the map to have enough context to answer your focus question, you'll likely see you gathered some details that are unnecessary to achieve your current goal. That is to be expected with context mapping. All the details are helpful to get a more complete understanding of your topic. But to make you map practical in terms of your focus question and goal, you’ll need to reduce it to a version containing only the neccessary items to meet your goal. As you do so, it is also useful to reorganize and regroup the items.

Making use of the context map

The process of building a context map is the goal itself because as you work on the map, you organize your thoughts, learn, and find sources. But there are many possible next steps.

Sharing and collaboration

The obvious is sharing your map for comments or collaboration. You can also use your context map to build an outline or a whole content plan. Or you can feed it to AI and ask it to do it (or anything else) for you

Feeding the map to AI assistants

The context map can serve as a source of context for AI LLM models, provided you create the map using a tool that supports easy export or integration with GPT chatbots. The beauty of this is the AI does not care much about how well-organized your context map is. It will make sense of it on its own and then perform your task being perfectly informed, with the right context. The task can be content creation or just outlining content, creating a summary of the most important facts, a list of FAQs, or building a study guide... The possibilities are endless.

Organizing complex Information: practical considerations

As with any advanced method, context charting requires careful consideration and skillful execution to realize its full potential. Here are some practical guidelines to enhance your proficiency in context charting.

Keep everything, except clutter

An essential tenet of context charting is to retain everything pertinent to your study, even the items deemed initially less relevant. These peripheral items may later reveal themselves as critical insights or bridge gaps between seemingly disparate ideas. However, actively manage clutter by ensuring that each item on the map serves a purpose or holds potential value.

Emphasize relationships with links

The utility of context charting lies in its ability to emphasize relationships, not just within clusters of items but across the entire map. Use links not only to highlight direct connections but also to represent potential or speculative relationships that merit further exploration.

Balance structure and flexibility

While maintaining a structured approach is important, remain open to the map's organic evolution. Flexibility allows new insights to emerge and refines your focus question or exploration path as more information is reviewed and analyzed.

Iterative refinement

Context maps are dynamic entities that benefit from iterative refinement. As new sources are acquired or fresh insights are generated, revisit and revise your map to accommodate the evolving understanding of your research focus. The map can serve as a search query you can use over time to check for news or new developments in the area.

Iterate not only in time, but also as you build your map at the first time. Context charting is not a linear process where you go through the steps once and you are done. Often, you may realize the map does not fit it's purpose, that it is not good enough yet. Then you may go back to expanding it (or shrinking it, removing some items), adding more sources, reorganizing, or even redefining the initial focus question.

Versioning

With every iteration, every time you feel you are about to make a big change, save a copy of your context map. This will allow you to reorganize and edit the map without regrets, ensuring you can use the original map later for a different project, or just back track when you find out the change was not for the better. Versioning is especially important when you progress to the final step of reducing the map.

A New Paradigm

In sum, context charting redefines visual research and note-taking by accommodating the complexities of the digital age, where AI and vast knowledge repositories continuously reshape our understanding of information gathering. Through a disciplined yet flexible approach to organizing data, context charting empowers writers, researchers, students, and entrepreneurs to discover and convey deeper insights and connections.

By adopting and mastering context charting, professionals across various fields will not only streamline the process of research and content creation but will also cultivate an ability to synthesize information in a way that is both coherent and compelling. This method is more than just a tool—it is a new paradigm for thinking, learning, and creating in the modern era.

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