Many systems are organized hierarchically. The CERNDOC documentation system is an example, as is the Unix file system, and the VMS/HELP system. A tree has the practical advantage of giving every node a unique name. However, it does not allow the system to model the real world. For example, in a hierarchical HELP system such as VMS/HELP, one often gets to a lead on a tree such as:
HELP COMPILER SOURCE_FORMAT PRAGMAS DEFAULTS
only to find a reference to another leaf: Please see
HELP COMPILER COMMAND OPTIONS DEFAULTS PRAGMAS
and it is necessary to leave the system and re-enter it. What was needed was a link from one node to another, because in this case the information was not naturally organized into a tree.
This, I think, is the brilliance of Notion, and what makes it one of the best examples of “fidelity to digital information” that I’ve come across. The structure of the app reflects the structure of the web itself: digital content is purposefully formatted, like semantic HTML elements, and exists in a hierarchical structure (directories on the web, nested pages in Notion), yet can be linked and referenced to create a complex network of information. And pages in Notion reveal the structure of the information: when nesting a page within a page, the child page always displays on the parent page. There’s no way to create a child page that doesn’t display on a parent page, no way to obscure the structure of the information. The semantic structure of Notion reflects the semantic structure of the web itself.
Truchet's approach was more topological than geometric, and the qualitative aspects of pattern take priority over the metric ones. His principles provide a kind of metaphor for the hierarchy of separation and connection in all things.
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance.