Structuredness (recursive structuredness) of knowledge. variety of elements and the difference in their nature

Lecture 4. Data and knowledge

The relationship between data and knowledge is always of interest, in particular the presentation (ways of formalization) of both, the model of data and knowledge presentation, since data and knowledge is a form of information presentation in a computer (Fig. 1.17).
The information with which the computer deals is divided into procedural and declarative.

Procedural information is embodied in programs that are executed in the process of solving problems, declarative information - in the data with which these programs work (Fig. 1.18).

The standard form of information representation in a computer is a machine word, consisting of a number of binary digits - bits defined for a given type of computer. In some cases, machine words are divided into groups of eight binary bits, which are called bytes.

The same number of bits in machine words for commands and data allows them to be considered in a computer as identical information units (IE) and to perform operations on commands as on data. The contents of the memory form an information base (Fig. 1.19).

For the convenience of comparing data and knowledge, the main forms (levels) of the existence of knowledge and data can be distinguished. As presented in table. 1.2, data and knowledge have a lot in common. However, knowledge has a more complex structure, and the transition from data to knowledge is a natural consequence of the development and complication of information structures processed on a computer.

Data

In parallel with the development of the computer structure, the development of information structures for data presentation took place.

There are ways of describing data in the form of vectors, matrices, list structures, hierarchical structures, structures created by the programmer (abstract data types).

Currently, high-level programming languages \u200b\u200buse abstract data types, the structure of which is created by the programmer. The advent of databases (DB) marked another step towards organizing work with declarative information.

With the development of research in the field of InS, knowledge concept,which combined many features of procedural and declarative information.
Today the terms "database", "information intelligent system", like many other terms of informatics, have become widely used. The reason for this is the general awareness (social need) of the need for intensive introduction of computers and other means of automated information processing in the most diverse areas of modern society. The beginning of the last quarter of this century can rightfully be called the beginning of an era of new information technology - technology supported by automated information InS.

The relevance of the problematics of InS and underlying databases is determined not only by social need, but also by the scientific and technical possibility of solving classes of problems related to satisfying the information needs of various categories of users (including both a person and a software-controlled device). This opportunity arose (approximately at the turn of the 70s) thanks to significant advances in the field of hardware and software for computing systems.

The database as a natural science concept is characterized by two main aspects: informational and manipulation. The first aspect reflects such data structuring, which is most suitable for providing information needs arising in the domain (software). Each software is associated with a set of "information objects", links between them (for example, "suppliers", "product range", "consumers" - categories of information objects, and "supply" - the type of relations that take place between these objects), and also the tasks of their processing. The manipulation aspect of the database concerns the meaning of those actions on data structures, with the help of which various components are selected from them, new ones are added, deleted and updated obsolete data structure components, as well as their transformation.
A database management system (DBMS) is a set of tools (language, software and, possibly, hardware) that support a certain type of database. The main purpose of the DBMS, from the point of view of users, is to provide them with tools that allow them to operate with data in abstract terms (names and / or characteristics of information objects) that are not related to methods of storing data in computer memory. It should be noted that DBMS tools may, generally speaking, not be enough to solve all the tasks of a particular software. Therefore, in practice, it is necessary to adapt (supplement, tune) the DBMS tools to provide the required capabilities. The systems obtained by adapting the DBMS to this software belong to InS.

A viable InS, i.e., capable of supporting the database model, taking into account the dynamics of software development, should, if necessary, contain a DBMS as its core. The INS design methodology developed to date (from the DB point of view) includes four main tasks:

1) system analysis of software, specification of information objects and relationships between them (as a result, a so-called conceptual, or semantic, software model is developed);

2) building a database model that provides an adequate representation of the conceptual software model;

3) development of a DBMS that supports the selected database model;

4) functional expansion (through some programming system) of the DBMS in order to provide the ability to solve the required class of problems, i.e. data processing tasks specific to this software.

Knowledge

Let us consider the general set of qualitative properties for knowledge (specific features of knowledge) and list a number of features inherent in this form of information presentation in a computer and that allow us to characterize the term “knowledge” itself.

First of all, knowledge has a more complex structure than data (metadata). At the same time, knowledge is set both extensionally (i.e., through a set of specific facts corresponding to a given concept and relating to the subject area), and intensionally (i.e., through properties corresponding to a given concept, and a scheme of relations between attributes).

With that said, let's list the properties.

Internal interpretability of knowledge.

Each information unit (IE) must have a unique name by which the IS finds it, and also responds to requests in which this name is mentioned. When the data stored in memory was stripped of names, there was no way to identify them by the system. Only the program could identify the data.
If, for example, in the computer memory it was necessary to record information about university students presented in Table. 1.10, then without internal interpretation, a set of four machine words corresponding to the rows of this table would have been written into the computer memory.
At the same time, the system does not have information about what groups of binary digits in these machine words are encoded information about students. They are known only to the programmer.
During the transition to knowledge, information about a certain protostructure of information units is entered into the computer memory. In the example under consideration, it is a special machine word that indicates in which bits the information about surnames, years of birth, specialties and course is stored. In this case, special dictionaries must be specified, which list the surnames, year of birth, specialties and course names in the system memory. All these attributes can play the role of names for those machine words that correspond to the rows of the table. They can be used to search for the information you need. Each row of the table will be an instance of a protostructure. Currently, DBMS provide implementation of the internal interpretability of all IE stored in the database.

Examples of simple groups:

· address (zip code, city, street, house, apartment);

· date (day, month, day);

· person (surname, name, patronymic);

· product (name, code, grade, size).

Examples of complex groups:

driver (person, car);

addressee (address, person).

Intermediate components are called in groups , moreover, those that consist only of details are called simple, and those that contain other components are called complex.

Indicators.

An indicator is a structural unit of information consisting of one attribute of the basis, reflecting a particular fact in a quantitative assessment, and a number of attributes-attributes (time, place, characters, objects of labor, etc.) that characterize it and associated logical relationships with it. ...

The general view of the indicator can be presented as follows:

П \u003d (P 1, P 2 ... P n, Q),

where P 1, P 2 ... P n - attributes-signs; and Q is the base variable.

One of the reasons for separating indicators into a special kind of structural units of information is that the indicator is essentially the minimum composition of the population, retaining information content, and therefore sufficient for the formation of an independent document.

For an indicator, a name (identifier), structure or form, and value are also distinguished.

The structure of an indicator is called its requisite composition.

The value of the indicator is a certain structure in which each variable included in the indicator is assigned a specific value from the corresponding domain of definition.

When classifying indicators, the following aspects are highlighted:

· An object, the state of which is reflected by the indicator;

· State of objects;

· Unit of measurement of the base;

· Stability of the indicator values.

To the most common groupings on the basis of "object" the indicators that determine the population, natural resources, social product, structural units (the number of enterprises, organizations, territorial entities, etc.) are classified.

Of particular interest in this group are indicators with a base value equal to one, in which the phenomenon of a veiled base is observed before the processing process.

Such exponents will be called Boolean. A feature of the Boolean indicator is the alternativeness of the value of its base, which is reduced to one of two values: one or zero. At the first meaning the indicator, as it were, is subject to registration due to the presence of the observed object and its inherent features. At the second, zero, value, as it were, the absence of these signs is established, and, consequently, the entire unit of observation. With outward simplicity, Boolean indicators make it possible to carry out generalization, aggregation, as a result of which enlarged indicators are created.

On the basis of "state" indicators are subdivided into static, characterizing the displayed object or its properties at a certain point in time (for example, the number of employees, the price of products, the tariff for services, etc.), and dynamic characterizing the processes of activity or the change in the state of the displayed object over a certain period of time (for example, the movement of labor resources, changes in natural resources, etc. ).

When classifying indicators based on "base units" stand out absolute and relative indicators.

Absolute indicators are called, the bases of which are obtained by direct counting, measurement and weighing, algebraic summation of other absolute indicators, as well as various average absolute indicators.

In number relative includes indicators, the base values \u200b\u200bof which are obtained by the ratio of the bases of the other two indicators (for example, structure indicators characterizing the specific weight of a part as a whole, intensity indicators, namely, capital productivity, material consumption, labor productivity, etc.) and relative average indicators.

When classifying on the basis of stability distinguish variables and permanent indicators. In the group of constant indicators, there are normative indicators (norms, standards, rates, prices, constant coefficients and interest rates).

Information space of economic objects

The information space of some object is understood as the totality of all information components of this object or a set of objects, regardless of the methods and means of displaying these components.

One of the most important characteristics of the information space is the degree of its structuredness.

Structurality is understood as a property of an information space, in which all the content and features of this space are represented by its components and the relationships between them, expressed in an explicit form.

Depending on the degree of structuredness of the information space, the following five types of it are distinguished.

Unstructured space - this is one for which it is characteristic that the structuredness of its components of information is rare.

An example of an unstructured information space is spoken language, although some elements of structuredness may be present in it.

Weakly structured information space one in which only individual components are fully structured.

An example is a written language in which syntax rules are followed.

Structured information spacecharacterized by a significant predominance of structured components, the information in it is documented, coding is widely used to provide an unambiguous interpretation of certain concepts. An example is the economic information system.

Formally structured information space - this is a space where descriptions of information formations exist in an explicit form, in which not only information structures and connections are defined, but also algorithms for obtaining the values \u200b\u200bof any data element.

Machine-structured information space - this is the one in which all information formations are described, including the forms of input and output documents. A typical example is a database.

Verification tests for topic 1

1. Props are:

a) Data value

b) Characteristics of the determined property of the object

c) Composite unit of information

d) Collection of records

e) Data set

2. Economic information is classified by management functions into

b) primary and secondary

3. Economic information is classified by the way of education on