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TRADITIONAL KNOWLEDGE

What is Traditional Knowledge?
 

Traditional Knowledge constitutes the ancient knowledge of humanity, the deepest layer onto which our science and culture developed, the local techniques that made it possible to manage and create ecosystems and cultural landscapes on the planet.

 

It originated from resource shortage in pre-industrial societies where a strong social cohesion and environmental integration were main features. Traditional Knowledge represents techniques with low energy dispersal and resource consumption that adapt to variability and are flexible in responding to environmental emergencies and catastrophes.

 

Extraordinarily tenacious cultures managed to use locally available materials and renewable resources. They exploited solar energy and the principles of Nature: thermal insulation to protect themselves from heat and cold; hydrodynamics to collect and distribute water; biology principles to combine and re-use the elements that are needed to create humus and cultivable soil. They managed to control the strength of the wind, use the law of gravity and exploit the faintest sign of humidity to start interactive autocatalytic phenomena and broaden positive dynamic processes. 

 

Today the world's ecological balance system is in danger: Traditional Knowledge shows how to intervene without disrupting the environment and how to enhance its potential without exhausting the resources. It is the bearer of the technologies disseminated on the territory that developed using everyday life materials and objects. It is constituted by fragile elements that are subject to today's transformations but form strong and ingenious systems to produce energy, recycle resources, regulate the microclimate and manage the land that is still exploited in most of the planet. 

 

This Knowledge is in danger and its disappearance would not only mean a loss of artistic and natural heritage but also of an extraordinary reservoir of knowledge and cultural differences from which appropriate innovative solutions can be derived.

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