Scanning and computer-assisted judging may safeguard against the pitfalls of human judging. On the eve of the 2019 gymnastics world championships in Stuttgart, Germany, the 527 participating athletes were asked to consent to a scan by multiple laser sensors to create a precise, three-dimensional image of their bodies. Those images, in turn, are being used to improve the accuracy of a so-called "judging support system," developed by Japanese IT giant Fujitsu, that's being used for the first time in the competition. The expectation, pending approval by the International Olympic Committee, is that the technology -- in which artificial intelligence helps human judges score gymnastics routines -- will be used at the 2020 Tokyo Olympics. And it may presage the day when computers replace human judges entirely in the largely subjective sport, although that is not the plan "for now," officials said.

A Computer-Assisted Reading and Analysis of Texts (CARAT) process is a complex technology that connects language, text, information and knowledge theories with computational formalizations, statistical approaches, symbolic approaches, standard and non-standard logics, etc. This process should be, always, under the control of the user according to his subjectivity, his knowledge and the purpose of his analysis. It becomes important to design platforms to support the design of CARAT tools, their management, their adaptation to new needs and the experiments. Even, in the last years, several platforms for digging data, including textual data have emerged; they lack flexibility and sound formal foundations. We propose, in this paper, a formal model with strong logical foundations, based on typed applicative systems.