Visualizing and rendering visible are two terms that refer to the constructive aspects of scientific images as opposed to the passive idea of ​​representation. Visualization involves any means by which an object becomes perceptible to the human eye, from optical devices such as the microscope to new means of modeling and virtual simulation. Technical images are not illustrative but rather productive agents and elements with multiple layers of the epistemic process. The production and advancement of scientific knowledge through the centuries has been dependent in one way or another on various media and techniques of the image. Graphs, diagrams, maps, drawings or schemes, among many others, have been vehicles for the theoretical visual formulation, the presentation of evidence or the understanding of complex biological, physical, chemical and mathematical processes. Although the visualization of knowledge has not been considered relevant by the philosophy of science and it has generally been assumed that images show what has been proven or developed in the field of language, they are a method of knowledge in themselves. The visualization of knowledge has been a fundamental element for scientific development as well as discursive development.

Technical images are not finished products but processes that renders something visible. That is why techniques and instruments created for that purpose must be taken into account (visualizing)) as well as the distinction between the representations of an observation in images, whether mechanical, made by the scientist or artist and their choices and their choices and the way in which a form becomes an instance of the style of a period (Bredekamp, Dünkel, y Schneider, 2015). LForm is a central element of technical images and the basis of their configuring power. The search for visual forms also implies the conventionalization of these pictorial forms and procedures. Scientific images are a type of image that condenses these formative and active aspects of images. They transmit knowledge and information. Their technical character comes from the cultural processes of production that involve procedures and instruments for obtaining them. The way in which images are produced and used represents more than the conscious intentions of the scientists, artists or researchers who have produced them and also the theories or formulas that would make them evident. Images have a constructive and agency capacity that explains their intrinsic effectiveness (Werner, 2019, p. 2). As Bredekamp points out, the concept of form eludes the more traditional concepts of objectivity, document and evidence that are generally attributed to this type of images and modifies the angle from which they are considered

The diversity of functions of the image in the scientific field is multiple, whether as testimony, as evidence or as representations that organize knowledge. W.J.T Mitchell has suggested a movement between image and theory, an inversion of the traditional way of thinking about their relationship. Images are not mere ornaments of discourse, but structuring analogies that shape entire epistemes (Mitchell 2009). The image can be thought of as a method of representation or as models that articulate in a truly complex way, language, variables, processes, numbers, data and images. The history of the relationship between the image and science allows us to understand the way in which knowledge has been dependent on visualization in order to establish connections, hypotheses, evidence and even develop new theories about unrepresentable objects. Associated with art for centuries, the process of data visualization was strongly connected to the imagination, even when data and observation were based on the use of telescopes or microscopes. Science and art depended on each other. The 19th century introduced a new set of ideas regarding the production of scientific knowledge, based on observation and evidence. Measuring devices began to become central to this production process. The image was thought of as a vehicle for the presentation and recording of reality, a de-aestheticized and de-humanized production of facts and results, without the intervention of subjectivity. The means of the image were reduced to a vehicle for translating signals, movements, sounds or stimuli into their graphic representation

The 20th century and the contemporary scenario introduced the use of new devices based on digital modelling through mathematical data processing and its graphic representation. Mathematics became the means to construct virtual images and their corresponding graphic models. This opens up new questions about the images produced by scientific knowledge: what they are, what we see in them and what they represent. New approaches to images are presented as a necessary theoretical framework to be able to answer these questions since we are faced with different types of images, generated by different image media and that can be thought of as traces, icons or mere abstractions. As Dietr Mersch (2014) points out, we are not dealing with clear visualisations that represent something concrete but with possibilities that can claim different epistemic forms. Many of the images that science produces today do not respond to anything “real” but rather to topologies and relationships that do not serve as proof or testimony of “something”. The ambiguity of some images is no longer a product of mimesis but of the logics that produce them. What we can define as mathematical unrepresentability, which, like art-historical representation, involves symbols and visual metaphors (Elkins, 1995). This tension between figuration and graphics, the ambiguity of the iconic or the aestheticization of what is represented, which was brought about by the distrust of artists in past centuries, presents new forms of dependence in computer-produced images. From maps, engravings and drawings to computer graphics, from hand-made images to geometric abstraction, vision in scale, projection or perspective, the influence between art and science continues to be one of the central elements for understanding the visualization of knowledge, even that of the order of the unrepresentable.