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A Digital Footprint is the data trace or trail left by someone activity in a digital environment. Digital Footprints are the capture in an electronic fashion of memories and moments and are built from the interaction with TV, mobile phone, World Wide Web, Internet, mobile web and other digital devices and sensors. Digital Footprints are invisible but provide data on what you have done, where the person has been, how long they stayed (physically and reading this Wiki page), both via the web and by location (geography), how often, the route or routine and increasingly who with, your social crowd.
As ‘becoming digital’ continues its pervasive invasion into every aspect of life, there will be a wider realisation that your/our/my digital footprint is not important, and the ownership and rights of the data is going to be critical for the web to continue to become the semantic web.
Data (digital footprint) is collected from a user and this is used to build a profile, which can used by a business to improve recommendation. This is an open system.
Digital data from many users interactions and purchases generates better recommendations.
If the same business can now collect data on how that user actually uses and interacts with the service, there is now an additional component of data. The output of one process becomes the input to the next.
If the same business can now collect data on how that user influences others to use and interact with the service, there is now an new component of data.
The closed loop digital footprint was first explained by Tony Fish in his book on digital footprints: Jan 2010. The closed loop takes the data from the open loop and provides this as a new data input. This new data can determine what the user has reacted to or how they have been influenced. The feedback now builds a digital footprint based on your and social data and the controller of the social digital footprint data can determine who and why people purchase and behave.
The goal of Digital Footprints is to have all this data and then in real timedeliver improvement via a feedback loop that closes the system. This closed loop brings stability to the service improvement as there is direct and immediate feedback, making the perpetual Beta model of continuous improvement even more attractive. This closed direct feedback loop is enhanced if further data can be collected from the user’s social cloud, friends and norms.