Big Data: From Forecasting to Mesoscopic Understanding. Meta-Profiling as Complex Systems
AbstractWe consider Big Data as a phenomenon with acquired properties, similar to collective behaviours, that establishes virtual collective beings. We consider the occurrence of ongoing non-equivalent multiple properties in the conceptual framework of structural dynamics given by sequences of structures and not only by different values assumed by the same structure. We consider the difference between modelling and profiling in a constructivist way, as De Finetti intended probability to exist, depending on the configuration taken into consideration. The past has little or no influence, while events and their configurations are not memorised. Any configuration of events is new, and the probabilistic values to be considered are reset. As for collective behaviours, we introduce methodological and conceptual proposals using mesoscopic variables and their property profiles and meta-profile Big Data and non-computable profiles which were inspired by the use of natural computing to deal with cyber-ecosystems. The focus is on ongoing profiles, in which the arising properties trace trajectories, rather than assuming that we can foresee them based on the past. View Full-Text
Share & Cite This Article
Minati, G. Big Data: From Forecasting to Mesoscopic Understanding. Meta-Profiling as Complex Systems. Systems 2019, 7, 8.
Minati G. Big Data: From Forecasting to Mesoscopic Understanding. Meta-Profiling as Complex Systems. Systems. 2019; 7(1):8.Chicago/Turabian Style
Minati, Gianfranco. 2019. "Big Data: From Forecasting to Mesoscopic Understanding. Meta-Profiling as Complex Systems." Systems 7, no. 1: 8.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.