What ‘light loving moths’ forgot to tell you about ‘experience design’

‘Light loving moths’ and the world of design?, why this weird comparison! Yes, you may be thinking for a while. As we know there is a common belief that moths, flies, beetles are attracted towards light and that leads them to their unfortunate miseries at the candle light. When we understand that it is by their sheer inability to understand the circular light emitting behavior of the artificial light, these little insects fall prey to the candle fire and other hazards caused by artificial sources of light. Those insects are actually in search of the moonlight that has a constant angle of radiation. 

This occurrence in nature often reminds me about the hypes of nurturing and manufacturing customer experience design. Primarily design has two layers; one physical and second ideological. When physical layer of design act as the necessary act to optimize the functional and material aspects of the subject matter or the object manifestation, ideological layer act as the force that can create a demand or customer appeal beyond its actual capacities. Hence when we make all sort of fuzz about design, design thinking, truth in design we should understand the layer in which we are applying our design efforts and logic.

Data Diary #4

Information Machines and Metadata Strategy: Some early thoughts

How much of engineering is required for designing / evolving +information machines so that they can always differentiate between data and +metadata and further go beyond to create knowledge and insights out of it. While thinking of this question. I cam across the role played by Search Engines in this. No doubt, search engines are information machines. They learn the #semantic graphs of information relationships in a sea of indexes. Let me bring some metrics here. How will we measure the effectiveness of search engines as information machines. Do we need some axis to plot / visualize their effectiveness.

One of my favorite questions will be how much of data / information / relationships / indexes / semantic webs can be converted to working knowledge by Search engines? Rather can they do this task at all without the intervention of human interactions, at all ! 

Going by the same lines, my categorization / differential positioning of +metadata with respect to data will not be merely based on the relationship between the meaning and associative positioning of data nodes. It will be rather based on how one node of data connects the other node of data to a third node of data. So data and +metadata should always have more than one connecting dot between them. Thus when we use a search engine to find all the +metadata about a particular data node, it should find the meta data based on this semantic graph. 

+Gokul Alex 

@gokulgaze, PS: Views are my own and do not subscribe to any organization or institution