Map cycling refers to the practice of how we work with creating maps with the aid of a computer.
The "augmented" part refers to the way in which the computer can support the artist in the process of drawing. In the case of drawing maps this support extends to more than simple vector illustration tools, to include the ability of the computer to assist in laying out the map algorithmically and also for artificial intelligence to assist in the graph drawing process.
A "map" in the sense we use it here loosely is a yet-to-be-defined form of diagram or illustration which shares some of the properties of a geographic map (it is used for navigation), and some of the properties of a "graph" (it is visually informative about the underlying concepts or data). However it is intended to be a new specific form of illustration which is serves the function of a visual way to navigate, summarise and provide "gestalt" views of an information space.
Furthermore, we are using the term "map" here to refer to more than a simple passive description of a body of information - maps in the context of Map of the Future are active or Perfomative. This feature of maps as implemented in the Map of the Future is described further in the section Every Map is a DAO.
This is the fundamental methodology for a Mapathon, and is used whenever a mapathon is part of another event type (such as a Creatathon). The basic idea is that every mapathon workshop starts with a map (however simple), and results with a modified version of this map that is then sent somewhere (to another workshop, person or repository). As such a map is the fundamental product (form of documentation) of every mapathon. This enables the asynchronous growth of the mapping effort, and supports groups working in person, without good internet connection (or even offline entirely), as well as groups working in different time zones and across extended periods of time.
The Map of the Future is focussed around action. The map provides a Decision Making Architecture - that is a map of informed choices. As such we can imagine these maps as Blueprints for Action, where these blueprints are represented as ecosystems of DAO's or digital institutions.
The process of augmented map cycling is not simply one way from data, to augmented layout to hand crafted (designed) map. It is cyclic in that hand crafted maps, can be imported and then augmented by algorithms and artificial intelligence to form a cycle of augmentation that fuels the graph-in-graph-out workshop practice.
Thus cycling enables us to start anywhere in the cycle. We can start with data form questionnaires (or AI generated transcriptions of Freeform or structured interviews), and generate maps from these - or we can start with hand-drawn maps form workshops and use ai augmented tools to enable us to import these efficiently and suggest improved layouts.
This is a rapidly evolving field, but we can imagine the following use-cases for AI within this cycle: