Epistemología de la codificación de datos

Abstract

This study explores data encoding from an epistemological standpoint, investigating how mathematics
not only structures and validates knowledge but also addresses complex challenges through coding theory.
At the core of this investigation are the processes of encoding, decoding, and the application of Hamming
distance. These key concepts illustrate how coding theory meets practical needs in information transmission
by minimizing errors and ensuring data integrity. From a historical perspective, mathematics has evolved to
solve specific technical problems while simultaneously creating abstract frameworks that can be applied across
disciplines. Error correction within coding theory exemplifies this dual role, where tools designed for reliable
data transmission also contribute to broader theoretical models and applications in areas with complex, uncertain
environments. Thus, encoding emerges not only as a technical solution but also as a method for preserving
and structuring knowledge, offering insights into the ways mathematics extends its utility beyond immediate
applications. This dual perspective emphasizes the unique role of mathematics in crafting resilient structures
for knowledge transfer that support technological advances and enhance theoretical understanding.