My main message is, and has been, that there are basic knowledge patterns that capture important types of reasoning. The pattern I am elaborating on here is a Composer, which captures content once and then configures and reconfigures it into various documents to meet a particular need.
The value of identifying these patterns is that a talented developer, like my partner Steve, can write a powerful program that consumes predefined knowledge artifacts created by domain experts and then generates a web app automatically based on that knowledge. I call this type of program an application generator, or an 'apperator', for short.
At the same time, the identification of knowledge patterns empowers us, the knowledge authors who create the knowledge artifacts, because we can use these 'apperator' programs to build our own custom solutions without writing code.
In this particular case, I built a template using KnowtShare (our online collaboration tool), and made it available to charities for developing and documenting their business plans. The shape of that template, and therefore all plans created using it, is a hierarchical tree model. I call this shape a 'triangle' because it grows from a single root to the many 'leaves' of the tree. This tree/triangle is the knowledge artifact that stores the raw material for the Grant Composer. Each charity will create and maintain its own business plan.
There is a second artifact required, and it is built and maintained by me, as a community resource. That is a table -- a 'square' -- containing the information requirements for particular foundations.
The 'apperator' Steve has written is a Composer that knows how to consume these two types of artifacts: a hierarchical KnowtShare file filled with written information items and a .csv file that contains a matrix of communication targets (foundations) and their preferred order for those information items. Context questions are used to identify which branches of the tree and which rows of the table to use when creating a solution at run-time.
I, as the knowledge author, decided to use business plan information to populate a grant application for foundations, so the actual app that is created is a Grant Application Generator. But the same pattern could be used to collect an individual's CV and generate a customized resume for a particular company -- that would be a Resume Generator. Or a student's transcript and essay questions to generate a customized college application -- that would be a College Application Generator. This makes sense: these examples are very similar to the Grant Generator.
What about something further afield? There's a whole industry evolving around using legal boilerplate and context questions to generate legal documents. The Composer pattern could be used to achieve the same results, and with far less programming.
My last post was dedicated to describing how the very same business planning information used in grant applications can be used to generate other reports and marketing materials. All of these are examples of the Composer Pattern and can be created by the same aperator with only minor tweaks.
The Composer is just one pattern. I have written about the Recommender pattern and the Scoring pattern as well, and I will be describing others going forward.
The challenge, and the opportunity, come from thinking about problem solving at a higher level of abstraction than we normally do.
Most applications are built to solve a particular problem. The IT team interviews their customers to determine the functional specifications for an application they want built. Then the IT people go off and build it, checking back in periodically with the customers to make sure they're still on track.
Typically there is a deadline looming, and everyone is focused on the problem at hand. No one is interested in investing time (and money) in designing a meta solution that will make the next problem easier to solve. In fact, if programming is paid for on an hourly basis, there is a disincentive to look for the patterns that will make application development more efficient. But as knowledge authors, and as problem solvers in general, there are many benefits to identifying and harnessing new patterns.
Knowledge patterns only become visible when you are exposed to many different but similar problems, and when you look for them. It also helps to have a vocabulary and a mental framework that make it easier to discuss the patterns you sense are emerging. My goal is to contribute to the creation of those foundational tools, and to create real world examples that will stimulate discussion.
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