Posts Tagged ‘map’

AGB2009- democracy @ work – visual map

Friday, September 18th, 2009

This part of the AGB2009 series (see the presentation)
AGB2009: democracy @ work

This short article contains the visual outline of the article, using an OpenSource “mind mapping” software and community, called Xmind.net
The
original abstract and bibliography was published on 2009-09-10
democracy @ work: the map

everybody talks about democracy- at the polls.

but why limiting democracy to a voting exercise? how could you extend that into the workplace?

and what are the consequences of new technologies and media access to the workplace social environment

read this short article for an explanation of the visual map (and a link to the source, so that you can study its details!)

visual approach

A picture is worth 1000 words.

Actually, a picture can be used as an outline to understand more than 1000 words.

I have no artistic pretense- but I think visually.

As explained in the the presentation, the abstract is the first step, followed by this map, and then, the article.

Read the abstract if you want to think about your own position on the subject. Read the map if you want to just see what are my arguments. And read the article if you want to read my position and some experience-based ideas and suggestions.

XXI Century libraries and search engines

Thursday, May 21st, 2009

XXI century encyclopedias and knowledge processing.

How Google, WolframAlpha, Wikipedia, and Eurostat process a query.

Or: models of knowledge processing and distribution.

GMN2009: Reality

Friday, May 15th, 2009

When you build a model of reality, you try to reduce complexity.

Reducing complexity means making choices- and reducing the risk of something unexpected affecting the results of your model.

Actually, it means also reducing the number of parameters- and, therefore, making any evolution in your world more predictable.

But reality is not necessarily limited by your definition: and managing the reality within a model requires more that planning beforehand for what you know, in terms of activities or risks.

You have also to identify what is the “normal” way in which your model will react to unexpected changes in the “reality” surrounding your model.

This post is part of a series, first published in May 2009.