In Reference to Halasz’s ‘Seven Issues’ (Halasz, 2005) and Millard and Anderson’s ‘Seven Hypertexts’ (Anderson & Millard, 2023), I wonder if maybe we can consider Seven Knowledge Spaces, where the spaces referred to are spaces in traditional digital environments and in XR/VR/AR. For this purposes of this over view, Knowledge Spaces are defined as visual graphs/maps of nodes with attributes including names, locations and connections and the core use case is in XR. Key is identifying the purposes of knowledge spaces, in order to consider aspects and design directions, and name them according to purpose rather than other attributes. These spaces can be presented to a user in specific forms which all influence the affordances offered, including AR and VR.
Purposes of Knowledge Spaces
• To Find. To find information in the world already understood and presented by others.
• To Learn. To understand information in the world already understood and presented by others.
• To Think. To see and follow connections in order to synthesise information which has not already been presented in a cohesive form.
• To Present. The other side of the coin of ‘To Learn’ where the user’s goal is to present knowledge for someone else to understand.
• To Store & Find. To provide the means through which the user can store information with the hope of finding it in the future either through searching or browsing.
• To Collaborate. For more than one user to access synchronously or asynchronously to perform any of the activities above.
• To Meld. To meld with the knowledge in ways we have yet to even consider in rough terms.
Spatiality
• 2D in small spaces, such as on laptop screens or screens in XR environments.
• 2D in large spaces, such as Murals, including primarily 2D with 3D extensions.
• 3D in small spaces, such as a knowledge sculpture with the expectation to interact with from a seated perspective, at arms length.
• 3D in large spaces, such as a walkthrough knowledge sculpture or environment to interact in.
Shallow or Deep & Connected
Such Knowledge Spaces can be shallow, in that they are limited in how much information they contain and in that they are not connected to other spaces, or Deep & Connected where they contain more information and they are connected to other Knowledge Spaces. How Knowledge Spaces connect, both technically and visual interface wise will become an interesting and important challenge to deal with.
Use Case : Sloan & SpaSca with Author & Reader
Integration with the Alfred P. Sloan Foundation, Fabien’s SpaSca and my person macOS Author and Reader is eminently possible through JSON but the question we need to address is what the purpose(s) should be and how to make this happen. I’m just very glad to start putting a shape to this from a knowledge perspective and not just from a data perspective.
We should likely also consider how these spaces can co-exist and connect.
These systems are what we are focused on and building in the Future Text Lab. It will be crucial to expand beyond this, in terms of thinking, connecting and software, so this is only a starting set of systems and ideas.