Phenomenological and ontological models in natural science

TL;DR

This paper discusses the importance of ontological models in natural science, emphasizing their reliability over phenomenological models for extrapolation beyond measured data, and critiques the dominance of phenomenological approaches influenced by positivism.

Contribution

It highlights the necessity of ontological models in scientific understanding, especially for extrapolation, challenging the prevailing phenomenological and positivistic perspectives.

Findings

Ontological models are more reliable for extrapolation.

Phenomenological models are limited to interpolation.

Ontological considerations are essential for a realistic understanding.

Abstract

The observation of the nature and world represents the main source of human knowledge on the basis of our reason. At the present it is also the use of precise measurement approaches, which may contribute significantly to the knowledge of the world but cannot substitute fully the knowledge of the whole reality obtained also with the help of our senses. It is not possible to omit the ontological nature of matter world. However, any metaphysical consideration was abandoned when mainly under the influence of positivistic philosophy phenomenological models started to be strongly preferred and any intuitive approach based on human senses has been refused. Their success in application region has seemed to provide decisive support for such preference. However, it is limited practically to the cases when only interpolation between measured data is involved. When the extrapolation is required the ontological models are much more reliable and practically indispensable in realistic approach.