Difference between information and data. Difference between information and data
Data and information are often equated, but there is a significant difference between the two terms:
● Information- knowledge relating to concepts and objects (facts, events, things, processes, ideas) in the human brain;
● Data- presentation of processed information suitable for transmission, interpretation, or processing ( computer files, paper documents, records in the information system).
The difference between information and data is that:
1) data is fixed information about events and phenomena that is stored on certain media, and information appears as a result of data processing when solving specific problems.
For example, various data are stored in databases, and upon a certain request, the database management system provides the required information.
2) data are information carriers, not the information itself.
3) Data turns into information only when a person becomes interested in it. A person extracts information from data, evaluates, analyzes it and, based on the results of the analysis, makes one decision or another.
Data turns into information in several ways:
Contextualization: we know what the data is for;
Counting: We process data mathematically;
Correction: we correct errors and eliminate omissions;
Compression: We compress, concentrate, aggregate data.
Thus, if it is possible to use data to reduce the uncertainty of knowledge about a subject, then data turns into information. Therefore, it can be argued that information is the data used.
4) Information can be measured. The measure of measuring the content of information is associated with a change in the degree of ignorance of the recipient and is based on methods of information theory.
2. Subject area- this is a part of the real world, the data about which we want to reflect in the database. The subject area is infinite and contains both essentially important concepts and data, as well as insignificant or non-significant data. Thus, the importance of the data depends on the choice subject area.
Domain model. A domain model is our knowledge about a domain. Knowledge can be either in the form of informal knowledge in the expert’s brain or expressed formally using some means. Experience shows that the textual way of representing a domain model is extremely ineffective. Much more informative and useful when developing databases are descriptions of the subject area made using specialized graphic notations. Available large number methods for describing the subject area. The most well-known include the SADT structural analysis technique and IDEF0 based on it, Gein-Sarson data flow diagrams, the UML object-oriented analysis technique, etc. The domain model rather describes the processes occurring in the subject area and the data used by these processes. The success of further application development depends on how correctly the subject area is modeled.
3. Database- a set of independent materials presented in an objective form (articles, calculations, regulations, court decisions and other similar materials), systematized in such a way that these materials can be found and processed using electronic computer(COMPUTER).
Many experts point out the common mistake of incorrectly using the term “database” instead of the term “database management system”, and point out the need to distinguish between these concepts.
There are many definitions and views on the concept "information". So, for example, the most general philosophical definition is as follows: “Information is a reflection of the real world. Information is reflected diversity, that is, a violation of monotony. Information is one of the main universal properties of matter.” In a narrow, practical interpretation, the definition of the concept “information” is presented as follows: “Information is all information that is the object of storage, transmission and transformation.”
The author of information theory, K. Shannon (1916), defined the concept of information as communication, a connection in the process of which uncertainty is eliminated. Shannon proposed in the 1940s a unit of information measurement - a bit. In theory, each signal was assigned an a priori probability of its occurrence. The less likely the occurrence of a particular signal, the more information it carries for the consumer (i.e., the more unexpected the news, the more informative it is).
Information is zero when only one event is possible. As the number of events increases, it increases and reaches maximum value when events are equally probable. With this understanding, information is the result of a choice from a set of possible alternatives. However, mathematical information theory does not cover all the richness of information content, since it does not take into account the content side of the message.
Further development mathematical approach to the concept of “information” is noted in the works of logicians (R. Carnap, I. Bar-Hillel) and mathematicians (A.N. Kolmogorov). In these theories, the concept of information is not associated with either the form or the content of messages transmitted over a communication channel. The concept of "information" in in this case is defined as an abstract quantity that does not exist in physical reality, just as an imaginary number or a point that does not have linear dimensions does not exist.
WITH cybernetic point of view, information (information processes) exists in all self-governing systems (technical, biological, social). At the same time, one part of cybernetics defines information as the content of a signal, a message received by a cybernetic system from the outside world. Here the signal is identified with information; they are considered as synonyms. Another part of cybernetics interprets information as a measure of the complexity of structures, a measure of organization. This is how the American scientist B. Wiener defines the concept of “information,” who formulated the main directions of cybernetics and the author of works on mathematical analysis, probability theory, electrical networks And computer technology: Information is a designation for content received from the outside world.
IN physics information acts as a measure of diversity. The higher the orderliness (organization) of an object's system, the more “related” information it contains. From here the conclusion is drawn that information is a fundamental natural science category, located next to such categories as “matter” and “energy”, that it is an integral property of matter and therefore has existed and will exist forever. For example, the French physicist L. Brillouin (1889-1969), the founder of the band theory of solids, the author of works on quantum mechanics, magnetism, radiophysics, philosophy of natural science, information theory, defines information as the negation of entropy (entropy is a measure of uncertainty that takes into account the probability of occurrence and information content of certain messages).
Since the 50-60s, the terminology of information theory began to be used in physiology(D. Adam). A close analogy was discovered between control and communication in a living organism and in information technology devices. As a result of the introduction of the concept of “sensory information” (i.e. optical, acoustic, taste, thermal and other signals coming to the body from the outside or generated within it, which are converted into impulses of electrical or chemical nature, transmitted along neural circuits to the central nervous system and from it - to the corresponding effectors) new opportunities have emerged for describing and explaining the physiological processes of irritability, sensitivity, perception of the environment by the senses and the functioning of the nervous system.
Within genetics The concept of genetic information was formulated - as a program (code) for the biosynthesis of proteins, materially represented by polymer chains of DNA. Genetic information is contained primarily in chromosomes, where it is encrypted in a specific sequence of nucleotides in DNA molecules. This information is realized during the development of the individual (ontogenesis).
Thus, systematizing the above, we can conclude that for engineers, biologists, geneticists, psychologists the concept of “information” is identified with those signals, impulses, codes that are observed in technical and biological systems. Radio technicians, telemechanics, programmers Information is understood as a working fluid that can be processed and transported, just like electricity in electrical engineering or fluid in hydraulics. This working fluid consists of ordered discrete or continuous signals, with which information technology deals.
WITH legal point of view, information is defined as “a certain set of different messages about events occurring in legal system society, its subsystems and elements and in the environment external to the given legal information formations, about changes in the characteristics of information formations and the external environment, or as a measure of the organization of socio-economic, political, legal, spatial and temporal factors of the object. It eliminates the legal information education, phenomena and processes, uncertainty and is usually associated with new, previously unknown to us phenomena and facts."
Information from economic point of view - this is a strategic resource, one of the main resources for increasing the productivity of an enterprise. Information is the basis for an entrepreneur’s maneuver with matter and energy, since it is information that allows one to set the strategic goals and objectives of an enterprise and take advantage of emerging opportunities; make informed and timely management decisions; coordinate the actions of various departments, directing their efforts to achieve common goals. For example, marketers R.D. Basel, D.F. Cox, R.W. Brown define the concept of “information” as follows: “information consists of all objective facts and all assumptions that influence the decision maker’s perception of the nature and degree of uncertainty associated with a given problem or opportunity (in the management process). Everything that is potentially will reduce the degree of uncertainty, whether facts, estimates, forecasts, general communications or rumors, should be considered information."
IN management Information is understood as information about the control object, external environmental phenomena, their parameters, properties and state at a specific point in time. Information is the subject of managerial work, a means of justifying management decisions, without which the process of influence of the control subsystem on the managed one and their interaction is impossible. In this sense, information is the fundamental basis of the management process.
The value of the information for business identified D.I. Blumenau and A.V. Sokolov: “information is a product of scientific knowledge, a means of studying reality within the framework allowed by the methodology of one of the information approaches to the study of objects of various natures (biological, technical, social). The approach involves describing and considering these objects in the form of a system that includes a source, channel and receiver of control actions that allow for their meaningful interpretation." If you try to combine the proposed approaches, you will get the following:
Data carry information about events that occurred in the material world, since they are a registration of signals that arose as a result of these events. However, data is not the same as information. Whether data becomes information depends on whether a method is known to transform the data into known concepts. That is, in order to extract information from data, it is necessary to select an adequate method for obtaining information that corresponds to the form of the data. The data that makes up the information has properties that uniquely determine an adequate method for obtaining this information. Moreover, it is necessary to take into account the fact that information is not a static object - it changes dynamically and exists only at the moment of interaction between data and methods. All other times it remains in a state of data. Information exists only at the moment of occurrence information process. The rest of the time it is contained in the form of data.
The same data may present different information at the time of consumption depending on the degree of adequacy of the methods interacting with it.
By its nature, data is objective, since it is the result of recording objectively existing signals caused by changes in material bodies or fields. The methods are subjective. Artificial methods are based on algorithms (ordered sequences of commands) compiled and prepared by people (subjects). Natural methods are based on biological properties subjects of the information process. Thus, information arises and exists at the moment of dialectical interaction between objective data and subjective methods.
Moving on to the consideration of approaches to defining the concept of “knowledge”, the following interpretations can be distinguished. Knowledge- This:
- * type of information reflecting the knowledge, experience and perception of a person - a specialist (expert) in a certain subject area;
- * set of all current situations in objects of this type and ways of moving from one description of an object to another;
- * awareness and interpretation of certain information, taking into account the ways of its best use to achieve specific goals, the characteristics of knowledge are: internal interpretability, structuredness, coherence and activity.
Based on the above interpretations of the concepts under consideration, we can state the fact that knowledge is information, but not all information is knowledge. Information acts as knowledge, alienated from its carriers and socialized for general use. In other words, information is a transformed form of knowledge that ensures its dissemination and social functioning. Receiving information, the user transforms it through intellectual assimilation into his personal knowledge. Here we are dealing with the so-called information-cognitive processes associated with the representation of personal knowledge in the form of information and the reconstruction of this knowledge based on the information.
The transformation of information into knowledge involves a number of patterns that regulate the activity of the brain and various mental processes, as well as various rules that include knowledge of the system of social relations - the cultural context of a certain era. Thanks to this, knowledge becomes the property of society, and not just of individuals. There is a gap between information and knowledge. A person must creatively process information to gain new knowledge.
Thus, given the above, we can do conclusion, that the recorded perceived facts of the surrounding world represent data. When using data in the process of solving specific problems, it appears information. Results of problem solving, true, verified information ( intelligence), generalized in the form of laws, theories, sets of views and ideas, represents knowledge.
Concept, structure, classification, features of intelligent systems.
A system is called intelligent if it implements 3 basic functions:
1. Representation and processing of knowledge.
2. Reasoning.
3. Communication.
User
Functional Mechanisms Knowledge Base
Structural knowledge – knowledge about the operating environment. Metaknowledge is knowledge about the properties of knowledge.
1. Biochemical (everything related to the brain);
2. Software-pragmatic direction (writing programs that replace functions).
1. Local (task) approach: for each task special programs who achieve results no worse than humans.
2. Systematic approach, based on knowledge - the creation of automation tools, the creation of the programs themselves.
3. An approach using the method of procedural programming - creating algorithms in natural languages.
Main sections of IIT:
1. Knowledge management.
2. Formal languages and semantics.
3. Quantum semantics.
4. Cognitive modeling.
5. Convergent (converging) decision support systems.
6. Evolutionary genetic algorithms.
7. Neural networks.
8. Ant and immune algorithms.
9. Expert systems.
10. Fuzzy sets and calculations.
11. Nonmonotonic logics.
12. Active multi-agent systems.
13. Natural language communication and translation.
14. Pattern recognition, playing chess.
Characteristics of problem areas where the use of information information systems is necessary:
1. Quality and efficiency of decision making.
2. Unclear goals.
3. Chaotic, fluctuating and quantized behavior of the environment.
4. Multiplicity of factors that replace each other.
5. Weak formalizability.
6. Uniqueness (non-stereotypicality) of the situation.
7. Latency (hiddenness) of information.
8. Deviance in the implementation of plans, as well as the significance of small actions.
9. Paradoxical logic of decisions.
Instability, lack of focus, chaotic environment
Concept of data, information and knowledge. Properties of knowledge and their difference from data.
Information is:
· any information received and transmitted, stored by various sources;
· this is the entire set of information about the world around us, about all kinds of processes occurring in it that can be perceived by living organisms, electronic machines and other information systems;
· this is significant information about something, when the form of its presentation is also information, that is, it has a formatting function in accordance with its own nature;
· this is all that can be added to our knowledge and assumptions.
Data is information of a factual nature that describes objects, processes and phenomena of the subject area, as well as their properties. In computer processing processes, data passes next steps transformations:
· the original form of data existence (results of observations and measurements, tables, reference books, diagrams, graphs, etc.);
· presentation on special languages descriptions of data intended for input and processing of source data into a computer;
· databases on computer storage media.
Knowledge - in theory artificial intelligence and expert systems - a set of information and rules of inference (from an individual, society or an AI system) about the world, the properties of objects, the patterns of processes and phenomena, as well as the rules for using them for decision making. The main difference between knowledge and data is their structure and activity; the appearance of new facts in the database or the establishment of new connections can become a source of changes in decision making.
In order to place knowledge into an information system, it must be represented by certain data structures corresponding to the selected development environment intelligent system. Therefore, when developing information system First, the accumulation and presentation of knowledge is carried out, and at this stage human participation is mandatory, and then the knowledge is represented by certain data structures that are convenient for storage and processing in a computer.
IP knowledge exists in the following forms:
· initial knowledge (rules derived from practical experience, mathematical and empirical dependencies reflecting mutual connections between facts; patterns and trends describing changes in facts over time; functions, diagrams, graphs, etc.);
· description of initial knowledge by means of the selected knowledge representation model (many logical formulas or production rules, semantic network, hierarchies of frames, etc.);
· representation of knowledge by data structures that are intended for storage and processing on a computer;
· knowledge bases on computer storage media.
Knowledge is a more complex category compared to data. Knowledge describes not only individual facts, but also the relationships between them, which is why knowledge is sometimes called structured data. Knowledge is the result of a person’s mental activity aimed at generalizing his experience gained as a result of practical activity.
Knowledge is obtained as a result of applying certain processing methods to the source data and connecting external procedures.
DATA + PROCESSING PROCEDURE = INFORMATION
INFORMATION + PROCESSING PROCEDURE = KNOWLEDGE
Feature knowledge is that it is not contained in the source system. Knowledge arises from comparison information units, finding and resolving contradictions between them, i.e. knowledge is active; its appearance or shortage leads to the implementation of certain actions or the emergence of new knowledge. Knowledge differs from data by having the following properties.
Properties of knowledge (from lectures):
· Internal interpretability (data + method data). Methodological - structured data, which represents the characteristics of the described entities for the purposes of their identification, search, evaluation, and management
· Availability of connections (internal, external), communication structure
· Possibility of scaling (assessment of the relationship between information units) – quantitative
· Availability of semantic metrics (a means of assessing poorly formalized information units)
· The presence of activity (incompleteness, inaccuracy encourages them to develop, replenish).
Classification of knowledge
Knowledge– form of existence and systematization of results cognitive activity person. Knowledge helps people rationally organize their activities and solve various problems that arise in the process.
Knowledge(in the theory of artificial intelligence and expert systems) - a set of information and rules of inference (from an individual, society or an AI system) about the world, the properties of objects, the patterns of processes and phenomena, as well as the rules for using them for decision making.
The main difference between knowledge and data is their structure and activity; the appearance of new facts in the database or the establishment of new connections can become a source of changes in decision making.
Highlight various types knowledge:
Scientific,
Extra-scientific,
Ordinary-practical (ordinary, common sense),
Intuitive,
Religious, etc.
Everyday practical knowledge is unsystematic, unsubstantiated, and unwritten. Ordinary knowledge serves as the basis for a person’s orientation in the world around him, the basis for his everyday behavior and foresight, but usually contains errors and contradictions. Scientific knowledge based on rationality is characterized by objectivity and universality, and claims to be universally valid. Its task is to describe, explain and predict the process and phenomenon of reality. Extrascientific knowledge is produced by a certain intellectual community according to norms and standards that differ from rationalistic ones; they have their own sources and means of knowledge.
Classification of knowledge
I. by nature. Knowledge can be declarative And procedural.
Declarative knowledge contain only an idea of the structure of certain concepts. This knowledge is close to data, facts. For example: a higher educational institution is a collection of faculties, and each faculty, in turn, is a collection of departments. Procedural knowledge is of an active nature. They define ideas about the means and ways of obtaining new knowledge and testing knowledge. These are different types of algorithms. For example: method brainstorming to search for new ideas.
II. according to the degree of science. Knowledge can be scientific And extra-scientific.Scientific knowledge can be:
1) empirical (based on experience or observation);
2) theoretical (based on the analysis of abstract models, analogies, diagrams reflecting the structure and nature of processes, i.e. generalization of empirical data).
Extra-scientific knowledge can be:
parascientific knowledge - teachings or thoughts about phenomena, the explanation of which is not convincing from the point of view of scientific criteria.
pseudoscientific – deliberately exploiting conjectures and prejudices.
quasi-scientific - they are looking for supporters and adherents, relying on methods of violence and coercion. Quasi-scientific knowledge, as a rule, flourishes in conditions of strictly hierarchical science, where criticism of those in power is impossible, where the ideological regime is strictly manifested. (In the history of Russia, the periods of “triumph of quasi-science” are well known: Lysenkoism; fixism, etc.)
anti-scientific - as utopian and deliberately distorting ideas about reality.
pseudoscientific - represent intellectual activity that speculates on a set of popular theories (stories about ancient astronauts, about Bigfoot, about the monster from Loch Ness)
everyday-practical - delivering basic information about nature and the surrounding reality. Ordinary knowledge includes common sense, signs, edifications, recipes, and personal experience, and traditions. Although it records the truth, it does so unsystematically and without evidence.
personal – depending on the abilities of a particular subject and on the characteristics of his intellectual cognitive activity. Collective knowledge is generally valid (transpersonal), presupposes the presence of concepts, methods, techniques and rules of construction common to the entire system. III. by location
Highlight personal(tacit, hidden, not yet formalized) knowledge and formalized(explicit) knowledge.
Tacit knowledge– knowledge of people that has not yet been formalized and cannot be transferred to other people.
Formalized in some language (explicit) knowledge:
knowledge in documents;
knowledge on CDs;
knowledge in personal computers;
Internet knowledge;
knowledge in knowledge bases;
knowledge in expert systems, extracted from the tacit knowledge of human experts.
Distinctive characteristics knowledge is still a matter of uncertainty in philosophy. According to most thinkers, for something to be considered knowledge, it must satisfy three criteria:
a) be confirmed,
b) be true,
c) trustworthy.
Related information.
TO basic concepts that are used in economic informatics include: data, information and knowledge. These concepts are often used interchangeably, but there are fundamental differences between these concepts.
The term data comes from the word data - fact, and information (informatio) means explanation, presentation, i.e. information or message.
Data is a collection of information recorded on a specific medium in a form suitable for permanent storage, transmission and processing. Transformation and processing of data allows you to obtain information.
Information is the result of data transformation and analysis. The difference between information and data is that data is fixed information about events and phenomena that is stored on certain media, and information appears as a result of data processing when solving specific problems. For example, various data are stored in databases, and upon a certain request, the database management system provides the required information.
There are other definitions of information, for example, information is information about objects and phenomena of the environment, their parameters, properties and state, which reduce the degree of uncertainty and incomplete knowledge about them.
Knowledge is processed information recorded and verified by practice, which has been used and can be reused for decision making.
Knowledge is a type of information that is stored in a knowledge base and reflects the knowledge of a specialist in a specific subject area. Knowledge is intellectual capital.
Formal knowledge can be in the form of documents (standards, regulations) regulating decision-making or textbooks, instructions describing how to solve problems. Informal knowledge is the knowledge and experience of specialists in a certain subject area.
It should be noted that there are no universal definitions of these concepts (data, information, knowledge), they are interpreted differently. Decisions are made based on the information received and existing knowledge.
Decision making is the selection of the best, in some sense, solution option from a set of acceptable ones based on available information. The relationship between data, information and knowledge in the decision-making process is presented in the figure.
The relationship between data, information and knowledge in the decision-making process
To solve the problem, fixed data is processed on the basis of existing knowledge, then the information received is analyzed using existing knowledge. Based on the analysis, all are offered feasible solutions, and as a result of choice, one decision that is best in some sense is made. The results of the solution add to knowledge.
Depending on the scope of use, information can be different: scientific, technical, management, economic, etc. For economic informatics, economic information is of interest.