This is where we design and build our knowledge models, our ontologies and our patterns of meaning across all domains. Help us identify the variables and relationships that will come alive through models. Initially, we focus on the highest levels of knowledge representation and less on levels of detail. We organize first by using the words we are all familiar with, and then translating and expanding these linear placeholders into rich dynamic maps of relationship, exchange and complex knowledge.
We believe initiative, creativity, thoughtfulness and passion for the architecture of science and natural systems will allow us to construct dynamic models and large scale representations of everything complex.
We believe everything is a component of multiple interconnected systems and events. Given the technology at our disposal, we think the best way to organize and display this complexity is through pre-built iconic models populated by ontological categories organized visually for easy identification. We deliver meaning through an elegant array of colors, flow, and pattern that propagate on top of and within the models. Here are some of the principles we are using to guide the development of knowledge models:
- Everything has programming at its core and is dynamic
- Knowledge is comprehensive systemic understanding
- Y Worlds communicates knowledge by generating a spectrum of patterns representing past, present and future while addressing the objectives of a user
- Data is are points of association that contribute to understanding.
- Ontologies are useful schemas of organization. Technology allows us to develop different ontological frameworks serving different viewpoints and objectives. We will craft ontologies into visual models that operate within map windows
- We are building a visual language. We think assigning meaning to certain colors, shapes and forms makes sense.
Here are our current models:
We look forward to the exchange of ideas about how to construct ontologies and transform them into living representational visual models on screen.