The Method of Automated Identification
Information technology offers powerful tools for exploring the Unknown. Our idea indicates in which direction the Big Data toolkit can develop, capable of providing convincing evidence to confirm or refute modern views on, for example, Time; Big Bang (before and mechanism or instead); history of mankind; Information, Matter and Magnetism, their mutual connection; or what is Mass, how does it arise.
We believe that you should start with the database, with its main feature, which distinguishes the DBMS (Database Management System) from other software tools and is called the Dictionary. With the help of special tools used for maintenance, the Dictionary prepares a variety of representations of subjects of interest, which accumulate data. They are stored as metadata or data about data. The totality of such data is called models. A separate model covers one or several flat - two-dimensional - tables consisting of columns, where the measurement results and non-metric characteristics are recorded, the mutual combination of which reflects (false or true) representations of the authors.
As you study the subject of cognition, there is a need for new - quantitative and qualitative - characteristics, as well as a rejection of previous results, which for some reason seemed to the authors unsuccessful, of little value, or completely useless. The model of accumulated information will reflect this with the appearance of new tabular columns, as well as the correction or even the disappearance of the old ones.
The set of properties of the investigated phenomenon or its hypothetical characteristics reflected by the model are called attributes. The initial set of properties of the phenomenon is called the physical model (Physical View). A set where, along with the original attributes, liquidated, modified, and added columns can be found does not actually exist. This is a multitude combined using integration and projection techniques, collectively called Filter. It represents the resulting pivot table, formed from the selected initial physical attributes, and, very often, contains transformed column values, as well as filled columns, which are extracted from several tables at once. For this reason, the attributes of this representation are called non-existent or Virtual, and the selective union of the attributes of a virtual set, using a similar technique using another filter selected in a separate population, which the authors consider to be the most correctly reflecting the subject under study is a logical or logical model table (Logical View).
When research is just beginning, the authors may already have some kind of - most likely false - understanding of the subject being studied or its logical model. As you study with pilot studies and determine the appropriate results, new data is recorded. In combination with the already accumulated aggregate and taking into account the chosen level of mutual dependencies of different attributes, this allows you to correct and refine the virtual model so that its projection more accurately reflects the properties and characteristics of the subject under study, closer approaching the Full True Model.
Thus, the task of the Researchers is to create a consistent data structure of the analyzed subject or to obtain Information that, with a predetermined level of correctness, reflects a model that demonstrates the structure of weak and strong mutual dependencies of the attributes representing the data obtained in the research process. For this reason, to solve this problem, we propose to supplement and correct the logical model of the subject of study with iterative penetration through a set of virtual attributes to the physical level, which, at a chosen degree of approximation, will become identical to the subject of study. #AlexeyPopovitch #USA #Britain