Executive Summary

Sense making is all about knowing what to do in a given situation, both individually and collectively. Many observe problems with our capacity for collaborative, intelligent behavior. As automated systems (bots) get more involved in decision making, the world must be described more explicitly for intelligent, automated behavior.

This is where natural-system and formalized ontologies come into play.

This paper focuses on using markup to capture the natural languages that individuals use when they make sense of the world — the languages of internal narratives — to start negotiations around formalizing natural system ontologies into automated support systems to help individuals and groups make sense of complexity from multiple perspectives.

Formalizing an individual's personal ontology involves digitizing the way that they think about and organize information. This paper reports lessons learned from experiments developing a personalized XML doctype, prodoc. After being modified, as needed, for over a decade, prodoc has evolved to ease the authoring of information from many different perspectives/ logical systems/ ontologies.


What makes for a better bot? One that's fast, cheap, low-risk, easily trained, and thinks like me.

 --Test subject

The first section, What's computer-assisted sense making? looks at the role of automation in helping see patterns and organizing actionable information to enable the intelligent behavior of individuals, groups, and bots. It starts by relating semantic markup, semantic technologies, and formalized ontologies to human and automated sense making processes.

The path to prodoc contrasts word processing's focus on visual formatting behaviors and storage models with generalized markup, where text files contain start and end tags that describe nested containers that make content easy to process and stylesheets provide visual formatting specifications.

It introduces semantic markup, which involves giving the containers meaningful names, and semantic authoring, which allows authors to easily create new markup and name the data structures, themselves. Technically simple, allowing authors to declare new markup within documents has significant policy and value-proposition impacts.

prodoc in practice describes computer-assisted sense making tools that a test subject developed using custom markup and element/ attribute-based control surfaces. These control surfaces, sometimes augmented with form controls, allow the author to easily change and adjust CSS visual rendering properties. Sheet music, engineering accessible color pallets, and a modeling language are described.

The politics of markup and meaning deals with politics, which is defined as the way that groups make decisions. Complex global publishing lifecycles bring countless perspectives to the negotiation table. When semantic formalization and authoring are viewed from this perspective, semantics get dynamic. People change their minds about what's meaningful and how to communicate it.

A generalized process for values-based decision making is introduced, and its use in stabilizing and formalizing ontologies during markup development is described. Possible roles for semantic authoring in bottom-up data negotiations are considered. The results from mapping personalized markup to authoritative third-parties, WordNet and SUMO, are reported.

The paper concludes by introducing H1, a semantic authoring training system that is available for testing.