Composite unit of information. Dispensers for structured components Injection molding design using Solid Edge tutorial

By the information space of a certain object or set of objects we mean the totality of all information components of this object or set of objects, regardless of the methods and means of displaying these components. The information space is heterogeneous. It contains oral and written messages, including organizational and administrative documentation, reports on scientific research work, economic, technical and design documentation, etc., messages on machine media (punched cards, punched tapes, magic magnetic tapes, magnetic disks, etc.), as well as such types of information presentation as sound, electromagnetic, etc. One of the most important characteristics of the information space is the degree of its structure. Structuredness 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 explicitly. The more structured the information space is, the greater its orderliness. Depending on the degree of structure of the information space, the following five types are distinguished: 1. Unstructured information space (UIS). It is typical for NPIs that structured information components are rare. Examples of NPCs are spoken language or information exchanged between dolphins. Some elements of structure may be present in this subclass. 2. Weakly structured information space (SSIP) - only individual components are fully structured. A typical example of SSIP is written language. The structuring of the main volume of information consists in fulfilling the requirements of a certain syntax. As a rule, such requirements are ambiguous, contradictory, have exceptions, retain homonymy and synonymy, etc. 3. Structured information space (SIS) - characterized by a significant predominance of structured components. In SIP, information is documented, coding is widely used to ensure unambiguous interpretation of certain concepts. A typical example of an SIP is an economic information system (EIS), which is a part of the information space that reflects the activities of some economic entity. 4. The structured information space (FSIP) is formalized - for it there must be an explicit description of information formations in which not only information structures and connections are defined, but also algorithms for obtaining the values ​​of any data element. 5. Machine-structured information space (MSIP) - all information formations are formally described, including forms of input and output documents, end user requests. A typical example of MSIP is a database in a system for computer processing of economic information. All processes of information transformation in such a space are formalized and presented in the form of machine programs. Some unstructured elements are used to organize the interaction between end users and the computing system in natural (or close to natural) language.

Examples of simple groups:

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

· date (day, month, day);

· person (last name, first name, patronymic);

· product (name, code, grade, size).

Examples of complex groups:

driver (person, car);

addressee (address, person).

Intermediate components are called groups , and 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 requisite of the basis, reflecting a particular fact in a quantitative assessment, and a number of requisite attributes (time, place, actors, objects of labor, etc.) that characterize it and are connected with it by logical relationships. .

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

P = (P 1 ,P 2 ... P n ,Q) ,

where P 1 , P 2 ... P n - attributes; and Q is the basis attribute.

One of the reasons for identifying indicators as a special type of structural units of information is that an indicator is essentially a minimum composition that retains information content, and therefore sufficient to form an independent document.

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

The structure of an indicator is its requisite composition.

The value of an indicator is a certain construction in which each attribute 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 whose state is reflected by the indicator;

· condition of objects;

· unit of measurement of the base;

· stability of indicator values.

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

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.

We will call such indicators Boolean. A feature of the Boolean indicator is the alternative nature of its base, which can be reduced to one of two values: one or zero. At the first meaning the indicator is subject to registration due to the presence of the observed object and its inherent characteristics. At the second, zero value, as it were, establishes the absence of these characteristics, and, consequently, of the entire observation unit. Despite their apparent simplicity, Boolean indicators make it possible to carry out generalization and aggregation, as a result of which aggregated indicators are created.

Based on "condition"" indicators are divided into static, characterizing the displayed object or its properties at a certain point in time (for example, the number of employees, product price, tariff for services, etc.), and dynamic , characterizing activity processes or changes 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 are indicators whose bases 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 values ​​of the bases of which are obtained by the ratio of the bases of two other indicators (for example, indicators of structure, characterizing the share of the part as a whole, indicators of intensity, namely, capital productivity, material intensity, labor productivity, etc.) and relative average indicators.

When classifying based on stability differentiate variables And permanent indicators. In the group of constant indicators there are regulatory indicators (norms, standards, rates, prices, constant coefficients and interest rates).

Information space of economic objects

The information space of a certain object is understood as the totality of all information components of this object or 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 structure.

Structuredness 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 explicitly.

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

Unstructured space– is something that is characterized by the fact that the structure of its information components is rare.

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

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

An example is a written language that follows rules of syntax.

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

Formally structured information space– this is a space where there are explicit descriptions of information formations, in which not only information structures and connections are defined, but also algorithms for obtaining the values ​​of any data element.

Machine-structured information space– this is the one that describes all information formations, including the forms of input and output documents. A typical example would be a database.

Screening 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 according to the method of education on

a) planning, accounting, analytical, management

b) primary and secondary

c) excessive, complete and insufficient

d) reliable and unreliable

e) constant, conditionally constant and variable

4. Economic information is classified according to information saturation into

a) planning, accounting, analytical, management

b) primary and secondary

c) excessive, complete and insufficient

d) reliable and unreliable

e) constant, conditionally constant and variable

5. Economic information is classified according to the objectivity of its reflection on

a) planning, accounting, analytical, management

b) primary and secondary

c) excessive, complete and insufficient

d) reliable and unreliable

e) constant, conditionally constant and variable

6. Economic information is classified by stability into

a) planning, accounting, analytical, management

b) primary and secondary

c) excessive, complete and insufficient

d) reliable and unreliable

e) constant, conditionally constant and variable

7. Economic information is classified according to the place of origin and use on

a) planning, accounting, analytical, management

b) primary and secondary

c) excessive, complete and insufficient

d) reliable and unreliable

e) incoming, outgoing and internal

8. What models of knowledge representation exist?

a) frame models

b) nomenclature models

c) product models

d) semantic network models

e) logical models

Lecture 4. Data and knowledge

The relationship between data and knowledge is always of interest, especially the representations (methods of formalization) of both, the models for presenting data and knowledge, since data and knowledge are a form of representing information in a computer (Fig. 1.17).
The information the computer deals with is divided into procedural and declarative.

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

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

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

For the convenience of comparing data and knowledge, we can identify the main forms (levels) of existence of knowledge and data. As presented in table. 1.2, data and knowledge have much 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 presenting data occurred.

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

Currently, high-level programming languages ​​use abstract data types, the structure of which is created by the programmer. The emergence of databases (DBs) marked another step towards organizing work with declarative information.

As research in the field of InS developed, knowledge Concept, which combines many features of procedural and declarative information.
Today, the terms “database”, “information intelligent system”, like many other computer science terms, have become widely used. The reason for this is the general awareness (social need) of the need for intensive implementation of computers and other means of automated information processing in the most diverse areas of activity of modern society. The beginning of the last quarter of this century can rightly be called the beginning of the era of new information technology - technology supported by automated information systems.

The relevance of the problems of InS and the underlying databases is determined not only by social need, but also by the scientific and technical possibility of solving classes of problems related to meeting the information needs of various categories of users (including both humans and software-controlled devices). This opportunity arose (around the turn of the 70s) thanks to significant advances in the field of hardware and software of computer systems.

A database as a natural science concept is characterized by two main aspects: informational and manipulation. The first aspect reflects the structuring of data that is most suitable for meeting the information needs arising in the subject area (software). Each software is associated with a set of “information objects”, connections between them (for example, “suppliers”, “product range”, “consumers” are categories of information objects, and “supplies” are the type of relationships 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, and obsolete components of data structures are deleted and updated, as well as their transformations.
A database management system (DBMS) is understood as a set of tools (language, software and, possibly, hardware) that support a certain type of database. The main purpose of a DBMS, from the point of view of users, is to provide them with tools that allow them to operate 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 problems of a particular software. Therefore, in practice, it is necessary to adapt (supplement, configure) DBMS tools to provide the required capabilities. Systems obtained by adapting a DBMS to this software are classified as InS.

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

1) system analysis of software, specification of information objects and connections 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 characteristics of knowledge) and list a number of features inherent in this form of information representation in a computer and allowing us to characterize the term “knowledge” itself.

First of all, knowledge has a more complex structure than data (metadata). In this case, knowledge is specified 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 relationships between attributes).

With that said, let's list the properties.

Internal interpretability of knowledge.

Each information unit (IU) must have a unique name by which the IS finds it and also responds to queries in which this name is mentioned. When data stored in memory was devoid of names, there was no way for the system to identify it. Only the program could identify the data.
If, for example, it was necessary to record information about university students presented in Table 1 into the computer memory. 1.10, then without internal interpretation a set of four machine words corresponding to the rows of this table would be written into the computer memory.
At the same time, the system does not have information about which groups of binary digits in these machine words encode information about students. They are known only to the programmer.
During the transition to knowledge, information about a certain proto-structure of information units is entered into the computer memory. In the example under consideration, it is a special machine word, which indicates in which categories information about last names, years of birth, specialties and course is stored. In this case, special dictionaries must be specified, which list the surnames, years of birth, and names of specialties and courses available in the system’s memory. All these attributes can play the role of names for those machine words that correspond to the rows of the table. You can use them to search for the information you need. Each row of the table will be an instance of the protostructure. Currently, DBMSs provide internal interpretability for all IUs stored in the database.

A system is understood as a set of elements or parts connected with each other and with the external environment, the functioning of which is aimed at obtaining a specific useful result.

Question 2: The concept of a system, its properties. IS, Economic and automated information system.

In accordance with this definition, almost every economic object can be considered as a system that strives in its functioning to achieve a certain goal. As an example, we can name the education system, energy, transport, economic, etc.

The system is characterized by the following basic properties:

complexity;

divisibility;

integrity;

variety of elements and differences in their nature;

System complexity depends on the many components included in it, their structural interaction, as well as the complexity of internal and external connections and dynamism.

Divisibility of the system means that it consists of a number of subsystems or elements, identified according to a certain characteristic that meets specific goals and objectives.

System integrity means that the functioning of many elements of the system is subordinated to a single goal.

Variety of elements systems and the differences in their nature are associated with their functional specificity and autonomy. For example, in the material system of an object associated with the transformation of material and energy resources, elements such as raw materials, basic and auxiliary materials, fuel, semi-finished products, spare parts, finished products, labor and monetary resources can be identified.

System structure determines the presence of established connections and relationships between elements within the system, the distribution of system elements across hierarchy levels.

A system that implements control functions is called control system. The most important functions implemented by this system are forecasting, planning, accounting, analysis, control and regulation.

The systems differ significantly from each other both in composition and in their main goals.

Example 1. Here are several systems consisting of different elements and aimed at achieving different goals.

In computer science, the concept of “system” is widespread and has many semantic meanings. Most often it is used in relation to a set of technical tools and programs. The hardware of a computer can be called a system. A system can also be considered a set of programs for solving specific application problems, supplemented by procedures for maintaining documentation and managing calculations.

Adding the word “information” to the concept of “system” reflects the purpose of its creation and operation. Information systems provide the collection, storage, processing, retrieval, and issuance of information necessary in the decision-making process of problems from any area. They help analyze problems and create new products.

Information system- an interconnected set of means, methods and personnel used to store, process, and issue information in the interests of achieving a set goal.

The modern understanding of an information system assumes the use of a personal computer as the main technical means of information processing. In large organizations, along with personal computers, the technical base of the information system may include a mainframe or supercomputer. In addition, the technical implementation of an information system in itself will not mean anything if the role of the person for whom the information produced is intended and without whom its receipt and presentation is impossible is not taken into account.

It is necessary to understand the difference between computers and information systems. Computers equipped with specialized software are the technical basis and tool for information systems. An information system is unthinkable without personnel interacting with computers and telecommunications.

Information system- a human-computer system for supporting decision-making and production of information products, using computer information technology.

A characteristic property of the information space is its structure. This means that its elements are highlighted, connections between them are established, designations are introduced, elements and connections are ordered. The property of structure in different types of information spaces can be expressed to varying degrees. A high level provides the ability to present information in the form of documents and manipulate data using software and hardware of information systems.

Khotshov E.N. and Korolev M.A. There are five degrees of IP structuring:

Unstructured IP (NIP);

Weakly structured (SSIP);

Structured (SIP);

Formalized-structured (FSIP);

Machine-structured (MSIP).

Let us consider in more detail the signs of degrees of structure.

NPC - signs of structuring are extremely rare, an example is human speech, the transmission of messages in the animal world from individual to individual.

SSIP - components of structuring do not have a finished form, it is a natural written language, where the signs of structuring are grammatical rules, which are often ambiguous, contradictory, have exceptions, are not strict enough, etc.

SIP is distinguished by the predominance of structured components, coding has been introduced, information is documented; This is information prepared for “downloading” into an information system.

FSIP - there are specifications of information objects and their relationships that contain algorithms for obtaining any values ​​of data elements; data management operations are provided, reorganization and optimization of the EIS structure, as well as information processing algorithms, are possible.

MSIP - all information objects and their relationships are presented in a formalized form, information transformation processes are described in programming languages, interaction between the user and the electronic information system is ensured in natural or close to natural language or according to extremely simplified rules.

Elements of the structure of the information space.

Concept of indicator

Units of information act as elements of the structure of the information space. This concept, which is considered in the theory of economic information systems (EIS), expresses the essential or semantic content of the IP element. A unit of information (3) is understood as “a set of symbols to which a certain meaning is attached.” We consider a system of information units that has a rather complex hierarchical structure. There are several levels of information units depending on the semantic meaning and its fullness.

In order of increasing content of the concept, the following units of information are defined: details and a composite unit of information (CUI), which includes such units as an indicator and a database.

The elementary unit of information at the lower level is the props. This is an information display of the properties of an object, some process or phenomenon. Messages consist of definitions of the properties of objects, objects, phenomena, which are formed in some way from the corresponding details. It should be noted that a synonym for the concept of attribute is attribute, a term widely used in the literature on databases.

Hence, a composite unit of information is assembled from a set of details corresponding to the definition of a given object and represents an information display of the object or its part.

A type of composite unit of information is an indicator. This is a complex concept. There are various definitions of it. Some authors emphasize the essential meaning or character tied to the subject area, in particular economics. Others proceed from a formal-structural approach, focused on structuring the information contained in the indicator in order to adapt its structure for effective use in the information system. The results of such structuring are also used in information and analytical systems.

In this context, we present the definition of the formal-structural approach according to M.A. Korolev. in the interpretation (presentation) of Yasin E.G. “The indicator represents a statement with a complete meaning, including both the name of the variable and its specific quantitative value with all the qualitative features necessary to identify the latter.” An indicator is formed from a set of details or terms.

The details are divided into two groups:

Requisites-signs expressing the qualitative differences of the indicator, its semantic content, in particular economic;

Basic details containing quantitative values ​​of the indicator.

The indicator loses its meaning without any of the named details. Taken together, they form a statement (message) that has a complete objective meaning, which allows us to state that the indicator is the smallest component unit of information that is sufficient for document generation, transmission, storage and perception of messages.

When structuring the information space, a system of indicators is developed and their own structure is analyzed. In the course of this work, it is necessary to explore general patterns and identify categories of indicators - members of the general structural formula for describing indicators.

In general, the structure of the indicator is as follows: P→〈R, x>, Where:

P - indicator (can be economic);

R is a set of details (terms) identifying the semantic meaning of the indicator;

x - quantitative or qualitative value of the indicator.

The identifier, in turn, can be represented as two parts:

R→〈S,Q> , Where:

S - the name of the indicator, compiled from the details, revealing its substantive meaning;

Q - additional characteristics of the indicator, also composed of details and clarifying its quantitative value.

The selected details can, in turn, be composite. To clarify the connections between them, diagrams are built that detail the object to such an extent that further detail is impossible or makes no sense. The details of the lowest level are called single. Others located at higher levels are multiple.

We will carry out further analysis, starting with additional features. They may consist of:

E - units of measurement, there may be several of them in the indicator;

C - subjects, these can be the names of subjects and objects of economic activity, regions, location of the enterprise and other objects;

B - time or details that determine the time aspect - the moments of the origin of events, periods of time during the course of economic or other processes, phenomena;

Y is a sign of the accounting stage or, as stated in (9), management functions, that is, planned, actual, normative or any other indicator values.

Let's imagine this structure as a relation:

Q → 〈E,WITH,IN,U〉,

Thus R→〈S〈E,WITH,IN,U〉〉

The name of the indicator can be combined (defined by one attribute) or have its own structure and, in turn, consist of attributes, such as:

F is a formal (calculated) characteristic of an indicator that reveals its structure or an algorithm for aggregating initial detailed data, for example, sales volume, average, maximum value of a particular value (this implies a calculation method);

P - designation of the displayed technological or business process, for example manufacturing, sales, transportation, etc.

O - object of measurement, counting - types of goods, equipment, employees by category or total number.

Then S →〈F,P,ABOUT〉

Thus, the general structural formula of the indicator will take the form:

P →

R→

S→<Ф ,P,O>

Q→<Е ,WITH,IN,Y>

R→<<Ф ,P,O>,<Е ,WITH,IN,У>>

P→<<Ф ,P,O>,<Е ,WITH,IN,У>,x>

This structure, presented in Table 2.1, can display almost any indicator.

Table 2.1

R
S	Q
F	P	ABOUT	E	WITH	IN	U
R
F	P	ABOUT	E	WITH	IN	U	x