Iconography of Science Representations as Visual Concepts in the Digital Era. First Outline

Federico Alberto Brunetti ()
Additional contact information
Federico Alberto Brunetti: Politecnico di Milano, Department of Design

A chapter in The Visual Language of Technique, 2015, pp 119-123 from Springer

Abstract: Abstract As far as apparently distant, the discoveries of scientific investigation and the inventions of new modalities of representation in arts encourage each other to develop knowledge to understand the reality around us. The iconic component becomes particularly important in this type of path, as it can even shape the thought that generated it. The technologies and tools developed in the history of science, and even more the computing power of digital technology, allow us to explore scales of time and space profoundly remote from our existential coordinates. An interesting interweaving is actually occurring. “Big Science” is verifying an unexpected and significant correlation of interests concerning some fundamental arguments, in an unexpected continuum of open questions and possible cross-solutions, from the Zeptospace to the new cosmology. Digital platforms now make it totally interagibile the relationship between pure alphanumeric data and their presentation through qualitative forms of spatiotemporal algorithms. This possible visual quality of the quantitative values reasonably prelude to a series of next-generation -or mutation—of scientific iconography. The Statistical disciplines of probabilities are reasonably matching with the arts of imagination, in a process of deep convergence between the power of techno-sciences on the human mind to suggest new perceptions for the creativity and the imagination in arts.

Keywords: Black Hole; Dark Matter; Digital Technology; Virtual Object; Visual Concept (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-05326-4_14

Ordering information: This item can be ordered from
http://www.springer.com/9783319053264

DOI: 10.1007/978-3-319-05326-4_14

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().