Building the capture, processing and delivery system for knowledge transfer!~

Building an Inter-generational knowledge transfer system.

The reality of the almost information age is the reality of information. As I’ve mentioned previously 110 Zettabytes of information produced just by devices operating in the Internet of Things (IoT). From sensors and video surveillance systems, connected doorbells and connected cars data is being produced. A lot of the data produced by IoT devices is not consume and store. Some of it is automatically stored (video surveillance and other video feeds).

It is best in such a design process to figure out what the true requirements are first. So we need a data organization system in the world of data analytics you have two distinct concepts the first being a data lake, a data stream. Lake representing ongoing storage. A stream being either from a source (sensor or other) or from a lake and as it denotes a smaller amount of data constantly arriving. Think of it as a television station and a television. The television station has tons of content, but only streams part of the content to the television set. The TV can receive streams and choose between which streams it needs to consider.

Within the lake and stream you then break data into four distinct categories (for action/reaction) that allow you to decide what needs to be done to the data before presentation.

clip_image002The four buckets show the critical nature of the information; the example being how quickly do I need the data. The other side of this information process is the amount of analysis needed before data presentation. This second process applies to the first in how the information is moved from source to delivery.

clip_image004We take the four buckets of data delivery times and add the processing required for the overall impact of the information. This gives us a system with the overall processes in place.

Examples of this process in action are in the table below:

Data type

Time requirement

Modification requirement

Delivery type





Stored video


Remove non-requested timeline information


Sensor (water level of river)


Remove extra data (if water level is normal don’t report)

Various screen, portable device and others

Human being


Critical to be able to receive direct human input and modify that input so that it can be shared with other humans

Screen, various

Critical warning


Flexible formatting of all critical information

All devices at the same time.

Effectively what happens is information beings to move from the 110 Zettabytes possible to the more consumable amounts. Given that people use various devices, it is critical that the system be device aware in presentation. That drives into my long stated direction of the Screen as a Service. Be aware of the outputted device.

So what we get here is a delivery system for information. What we need to build is the system that captures the information effectively. The goal, is to create a human capture system that encompasses the ways humans produce information. Email, documents, presentations, video, audio and any other format including art, music and so on. The system has to adapt to the type of information produced and the person producing the information. It then adapts again to the person consuming the information. The faster the information is required, the faster the adaptation has to occur.

Placing this system into the wild requires planning. While the requirements we are gathering focus on the capture of knowledge we need to be able to place it into a simple decision matrix. As stated before John Boyd’s phenomenal OODA Loop process fits perfectly. It adds the additional needed feedback processes to improve information flow and capture along the way.


Inter-Generational Knowledge Transfer