The present edition of this workshop tries to kill
a few big scientific birds with one small iconic stone.

We do not know much about the way representations are elaborated, and even less on their manner to evolve in the degree of abstraction or to merge into larger ones, from one support or one scale to another. It is admitted they are necessary for humans to understanding phenomena and they may help elaborating theories, thus condensing sparse images into a single explanatory one. They are likely key features of the leaving, where programs (acting models) of systems are transmitted, having thus been elaborated as representations, together with the systems themselves which are then “ante-replication” representations of their avatars.

The importance of images for system behaviours and their understanding puts forward the role of representations as information supports: same as conductors convey energy or aging systems convey the time, representations transmit abstracted versions of systems, for them to be better perceived and acted.  Conversely, a same image gets different meanings (triggers different actions) to different perceiving entities even equally equipped. That in turns introduces the importance of noise, already latent in biological growth, and sends back to the compressing role of representations through the notion of robustness.

Eventually, representation as an imaging and abstracting process appears central to any intelligent activity. Among them, Science is a swing between conjectures i.e. abstract representations of a problem, and understanding i.e. effective representation of solutions, through experimentations i.e. concrete representation of both in terms of actions. And the technological burst of “informatics” images spreads them every where and at every stage of any current scientific steps: process flowcharts, blue prints and system sketches before experiment, Signals, images, matrices or graphics and dependency graphs after. So that a problem to solve in parallel with most other scientific studies turns out to be “how to master the huge amount of data generated by the least observation”. Indeed, one is far here from the unique image mentioned above and intermediate representations are rather dense than sparse!

The workshop “SCIENCE: IMAGe IN AcTION” aims at studying and discussing a few instances of the representation problem in different areas of Physics and Biology, with emphasis on Astronomy, Cosmology, Earth environment and climate studies. Speaking of imaging and abstraction, we will endeavor to stress links between the various topics considered in these areas. Unifying theories and trans-discipline tools should illustrate the character of universality of pertaining representations. On the other hand, the emergence of artificial agents, synthetic images, data miners and other computed facilities to help abstraction handling will be discussed both in its genuine aspects and through examples at various levels.

Targeted specific topics could be, but not limited to:

  1. Bullet inference mechanisms in modelling: from Bayes to self-assembly and perhaps more

  2. Bullet data merging: mastering uncertainty, imprecision and incompleteness

  3. Bullet perceptual models: scale invariance, quantum physics and geometry, etc.

  4. Bullet credible agents: reality, models and (computer) representation of complex systems

  5. Bullet multi scale analysis: rare phenomena, data mining and large data bases

  6. Bullet virtual and augmented reality to experiment: from computer graphics to virtual
    observation or computational biology


On the behalf of
Prof. A. Zichichi

(President of the EMFCSC)

the DAA - Data Analysis in Astronomy Workshops are from now dedicated to
Livio Scarsi and Vito DiGesù
who enthusiastically inspired the series.