Optionality: Discriminating noise from useful information
Hi there
Lets talk about optionality.
Optionality is a current phenomenon in which an interested selection process "kills" the research spirit by becoming big data production in a harmful event. Optionality in data management also refers to hidden values, noise or non-useful information in large volumes of data. Basically.
We know the importance of the application of new information technologies, particularly the GIS, in the exploitation and management of large volumes of data. The optionality theory may be worth your attention if you would like to know the impact of uncertainty and noise in the interpretation of large volumes of data.
In this regard antifragile theory can explain and show the effect of size (data volume) and response to uncertainty.
Lets talk about optionality.
Optionality is a current phenomenon in which an interested selection process "kills" the research spirit by becoming big data production in a harmful event. Optionality in data management also refers to hidden values, noise or non-useful information in large volumes of data. Basically.
We know the importance of the application of new information technologies, particularly the GIS, in the exploitation and management of large volumes of data. The optionality theory may be worth your attention if you would like to know the impact of uncertainty and noise in the interpretation of large volumes of data.
In this regard antifragile theory can explain and show the effect of size (data volume) and response to uncertainty.
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