Knowledge Models in the Age of Cognition

In the age of cognition, data, information and content assumes hyperbolic importance. Every quantum of information is a new pathway to discovery. We are building new semantic constructs through data science. We are depicting hidden connections through intricate and beautiful data visualizations. From information overload, we are marching towards a discipline of information architecture in every domain of technology and business. Content governance is helping us to devise logical structures in the organization. Content economy charts out the monetary aspects and details the return on investment from content management systems.

Is content, information and data stand alone entities in an enterprise ? No. Then what connects data, content and information ? The relationship between data, content and information is mediated by the context of use and reuse. Data, content and information are the semantic representations of a larger construct known as knowledge model. Knowledge exist in and through data, content and knowledge. Beyond the nomenclatures and the synonymous identity, these terms differ substantially in the terrains of knowledge models.

Knowledge model lies at the bedrock of content economy, information architecture and data science. It is the intrinsic value of knowledge in content, information and data that helps human beings to build higher order cognitive products such as data science, information architecture and content economy on the top of the elements of data, information and content.

To discuss further on the finite difference between data, information and  content and to define the contextual framework of knowledge modelling, read further from my story published in Medium Social Knowledge platform : 

Knowledge Models in the Age of Cognition by Gokul Baby Alex.