1. 1

2. Introduction Information is the product of the human brain in action. It may be abstract or concrete. When an individual begins to think, a variety of images and sensations flash across his mind. This makes some information to accumulate in his mind and his memory retains some pieces of knowledge 2

3. A close analysis of the variety of experience gained by an individual also reveals the relationship of these units of thought with associated ideas. Also different individuals may derive different sets of experience on or about the same unit of thought. And each ones experience on identical units of thought may remain isolated and prove less valuable, if both these individuals do not share their experiences. 3

4. The individual subjective knowledge of each person is transformed into objective knowledge is publicly observable by all and comes very new to the concept of information. Many scientists have correlated information and energy viz., information is a commodity no less tangible than energy; if anything, it is more pervasive in human affairs. 4

5. Definitions According to Bell, Information is news, facts, statistics, reports legislation, tax codes, judicial decisions, resolutions and the like. Webster’s Third New International Dictionary defines the term “Information” as the communication or reception of knowledge or intelligence; something obtained received through informing; the process by which the form of an object of knowledge is impressed upon the apprehending mind so as to bring about the status of knowing. 5

6. According to Shera (1970) information is a ‘fact’. It is the stimulus which we perceive through our senses. This may be a single isolate fact or it may be a whole cluster of factors; but it is still a unit; it is a unit of thought. It is a unit of thought. It can have any dimensions. It is the intellectual entity which we receive the building block of knowledge. 6

7. Information and Knowledge Information and Knowledge are often used synonymously. There is a slight difference between these two. Information may be a single fact or may unrelated facts. Whereas, knowledge is an ordered and structured or organized information. 7

8. When a person observes studies or measures an object, a phenomenon or an event, he identifies and records the occurrence of some properties or value (s) of the attribute (s) of the object etc. These (isolate) results of his observation or study as well as their symbolic representation in any form are data. We may also consider an assumed attributes or facts of any being (concrete or conceptual) in isolation and their representation is symbolic form as data. 8

9. When these raw data are processed, analysed, organized it becomes information. The processed data or information convey significant or specific meaning to us. The raw observation facts or data in isolation, when placed in meaningful contexts by data processing operations. Conceptually or with the aid of computers, allow to draw inferences. In order to draw inferences, human beings depends on his cognition ability and knowledge or expertise, be possess the body of truths or meaningful facts/information accumulated by a human in the course of studies. 9

10. Ten Aspects that Add Value to Information TimelinessCurrency. Information is perishable. Different information has different half lives (‘sell by dates’). Some degrades rapidly. AccessibilityEasy to find and retrieve – no long-winded searches, good hits UsabilityEase of use; user can manipulate to suit application UtilityIs suited and usable for multiple applications QualityAccurate, reliable, credible, validated CustomisedFiltered, targeted, appropriate style and format; needs minimum processing for specified application MediumAppropriate for portability and ongoing use RepackagingReformatted to match onward use FlexibilityEasy to process; can be used in different ways ReusabilityCan be reused; ideally extra use should refine its quality; the more people that can access and use, the better. 10

11. Information Management The term ‘Information Management’ can be defined by examining the following processes: Information and Knowledge creation: Scholars, research & development, analysts, writers, reporters, editors, software developers, inventors, consultants. Information Production: Service bureaus, printers, broadcast studios, film production studios, advertising agencies, and data-entry services. 11

12. Information dissemination: Telephone companies, newspapers, publishers, radio and TV stations, libraries, news services, databases, Internet providers, bulletin board systems, satellite downlink facilities, fax, e-mail. Information Organization: indexers, bibliographers, compilers, abstractors, clipping services, catalogers, search engines, industry yearbooks and annuals, trade show organizers. 12

13. Information diffusion: Workshops, conferences, listservs, news groups, professional organizations, education institutions, customer services. Information Utilization: Information brokers, decision support services. Information preservation: Archives, museums, newspapers of records, copyright and patent offices, libraries. 13

14. ‘Information Management’ is thus defined as the process of handling information acquired from one or many different sources in a way that it optimizes access by all who have a share in that information or a right to that information. The process of information handling or information management as we call it has evolved over the past years, influenced by the changes in the society and the technological trends in the knowledge society. 14

15. During the early part of 1970’s, maintenance of information was largely limited to files, file maintenance and life cycle management of paper and a small number of other media. The growth of information technology during the 70’s saw the change in the role of information management putting it into a new light. It graduated to a higher level which required expertise and no longer remained a simple job performed by anyone. An understanding of the technology and the theory behind it became necessary, as information was ever more stored via electronic means. 15

16. By the later 1990’s when information was regularly disseminated across computers and other electronic devices, information managers found themselves tasked with increasingly complex devices. With the latest tools available, information management has become a powerful resource for organizations. 16

17. ‘Information Management’ is also defined as the process of planning, budgeting, organizing, directing, training and controlling associated with organizational information. IM includes the management of information per se and related information resources, such as personnel, equipment, funds, and technology. Distinguishing between ‘information’ and ‘information resources’ is crucial for at least two reasons: 17

18. 1. Confusion about the differences between information and its manifestations is squandering the information resources of many organizations, leading to ineffective information processes. 2. That is the desired end of information processes are being confused with the means. Of vital concern, many organizations are confusing expression of information needs with the design of computerized information systems. 18

19. 2. It is important to distinguish between information and its related resources because many of the information- related issues, which are faced by organizations, have to do precisely with the choice of available information resources. Starting with a choice of medium (e.g. computer) is inappropriate until one clearly grasps what information is needed. 3. The medium is the message most writers about IM maintain, that the choice of information resources is a secondary matter, which should be preceded by a determination of what information is actually needed. 19

20. IM is relatively new and rapidly evolving activity and is separately recognized aspect of management. Although the fundamental ideas of IM have fairly wide currency, the implementation of IM is not evident in many organizations as yet. IM appeared in coherent from leading to a few pioneering organizations putting it into action. 20

21. Like any set of recommended principles for management, the implementation of IM requires understanding, acceptance, decisions making, and finally implementation by managers. The roles and attitudes of managers – especially senior managers – are critical to the successful application of IM ideas. IM requires enterprise – wide changes of organization, information responsibilities, policy, and procedures, the changes are pervasive, they take some time to fully implement, and the benefits can only be fully realized in the long run – five years or more. 21

22. What we need to remember is, however that Information Management is forever – there is little point of pursuing this approach from a short-term point of view. ‘Information Management’ is an umbrella term that encompasses all the systems and processes within an organization for the creation and use of corporate information. In terms of technology, information management encompasses systems such as: 22

23. Web content management (CM) Document management (DM) Records management (RM) Digital asset management (DAM) Learning management systems (LM) Learning content management systems (LCM) Collaboration Enterprise search 23

24. Information Management system incorporates the following subsystems: information dissemination systems, information technology, communications systems, and content providers into a potent mix of information services and information management systems. 24

25. Information management encompasses people, process, technology and content. It is important to address each of these aspects to succeed. Implementing information technology solutions in a complex and ever-changing organizational environment is not an easy task. The challenges inherent in information management projects mean that new approaches need to be taken, if they are to succeed, with focus on the organizational and cultural changes required to drive forward the improvements. 25

26. The Role of New Information Manager Information Management is about getting the right information, in the right format, at the right time, to the right person, at the best cost, at the best place, for the right action. To accomplish this information manager must be able to: Diagnose information needs Read and monitor the information environment Understand new technology 26

27. Develop and implement services Customize services Be user oriented Support end-user activities Perform information audits Evaluate systems, services, personnel Communicate the value of information Create effective information policies 27

28. Good information managers are obsessed with obtaining high quality information for their clients. They excel in assessing information and information systems. They have self-confidence, subscribe to a code of ethics, and must have the ability to withstand external pressure from a variety of interest groups. Finally, the key objectives of information management are: 28

29. Improved communications Improved access to internal and external databases Improved information processing Increased information flow Increased document preparation and information repackaging Increased utilization of information for decision-making Improved information resources management 29

30. Conclusion The information age requires information management for an organization’s second most important resource next to its people. Without managed information, public sector agencies waste time and taxpayers’ money hunting and chasing information, verifying and fixing it, or performing work around so that they can serve their citizens. Agencies can increase their effectiveness, as well as their stewardship to their citizens, by applying sound management principles to their information resource. 30

31. With effective training the information manager can be expected to function in a professional manner, i.e. fully motivated, up-to-date, effective in performance, and so on. While interest groups may form, and societies such as the Society for Information Management may flourish, however, it is unlikely that a new ‘profession’ will emerge. That, too, has its educational implications: there is something very secure about preparing people for an established profession – they have an inherently conservative character which encourages stability in educational programmes. 31

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33. Introduction Knowledge has always been a prime source through which human societies have advanced materially and elevated themselves spiritually. Knowledge comprises hundreds of fields and sub-fields, known as subjects, which are interlocking and interlinking. This universe of knowledge is infinite, dynamic and continuously expanding. 33

34. The structure of a subject is never complete or closed; every aspect of it remains always open, offering new problems for further study and research. Knowledge is also seen as personal and public knowledge, as tacit/ implicit and explicit knowledge. Popper sees knowledge as three worlds viz., physical, subjective and objective knowledge. 34

35. Knowledge being a social product, its sociology is of interest to us as well as its sub-sets sociology of science, literature, and reading. Finally knowledge utilization is the ultimate goal, which gets the human being, the value and utility. The advent of Information and Communication Technology (ICT) has offered a tremendous opportunity to generate new knowledge, disseminate, distribute, and provide access and many other facilities cutting across space. 35

36. Knowledge From cave life to the sophisticated life of the information / knowledge society, knowledge has been the prime resource that has advanced human communities materially and spiritually. 36

37. Definition A precise single definition of knowledge, universally acceptable to all and in all contexts, is highly impossible. Scholars who are interested in the study of knowledge, as a resource, as a philosophical concept, as social wealth, etc. have given their own definitions to suit their line of studies. The meanings of “knowledge” as given by the Random House Dictionary (RHD), and words synonymous with ‘knowledge’ are: 37

38. Acquaintance with facts or principles, as from study or investigation; general erudition; Familiarity or conversance, as with a particular subject or branch of learning; Acquaintance or familiarity gained by sight, experience, or report; as for example ‘knowledge of human nature’; Awareness, as of a fact or circumstance; That which is or may be known; information; and The body of truths or facts accumulated by mankind in the course of time, as for example ‘man’s knowledge of the moon’. 38

39. Words synonymous with ‘knowledge’ given in the RHD are Enlightment, Information, understanding, Discernment, Comprehension, Judgement, Wisdom, Lore and Science. Daniel Bell, the Harvard University Professor of Sociology while discussing ‘knowledge’ as the moving force of the Post-industrial Society, gives a comprehensive definition of knowledge as follows: 39

40. “Knowledge is an organized set of statement of fact or ideas, presenting a reasoned judgment or an experimental result, which is transmitted to others through some communication medium is some systematic form. Knowledge consists of new judgments (Research and Scholarship) or presentation of older judgments as exemplified in text books, teaching and learning and collected as library and archival material”. 40

41. Alvin Toffler, the well known author of Future Shock, Third Wave and Power Shift, gives another meaning of knowledge, which includes data, information, images and imagery, as well as attitudes, values and other symbolic products of society whether true, approximate or even false. 41

42. In the fast emerging new discipline of ‘Knowledge Management’, Davenport defines knowledge as follows: “Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides an environment and framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knower. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms”. 42

43. Knowledge is a highly organized intellectual product of humans that includes personal experience, skills, understanding of the different contexts in which we operate our activities, assimilation of all these and recording all this in a form that could be communicated to others. This communication of recorded experience, data, information, etc. makes for further of growth. 43

44. Some of the important characteristics of knowledge are: Knowledge is infinite Knowledge is dynamic, continuous and ever expanding. No final word can ever be said of any discipline; they are at best provisional, subject to criticism, correction, contradiction, change or modification. A gifted man may acquire wide knowledge, deep wisdom and spiritual insights but all these are lost when he/she dies except those that he / she had recorded. Knowledge once parted to others, results in no loss to the person. Knowledge becomes obsolete. 44

45. Types of Knowledge Personal and Public Knowledge Knowledge is broadly divided into two groups, personal knowledge (private knowledge) and social knowledge (public knowledge). Personal knowledge is the knowledge of the individual and as such is available to others only if communicated.  Social knowledge is the knowledge possessed collectively by a society. It is supposed to be available to all the members of the society freely and equally. Libraries and information centres provide this kind of knowledge. It must be, however, stated here that these two kinds of knowledge are not mutually exclusive. Social knowledge is an essential source of personal knowledge and it is personal knowledge that most social knowledge is built up. 45

46. Tacit and Explicit Knowledge The above two groups of knowledge is expressed slightly differently by Michael Polayani. Explicit knowledge is that expressed to others, orally or in a recorded form and tacit knowledge is personal knowledge that may or may not be expressed by an individual. Generally most people express their personal knowledge up to a point but not beyond for reasons of their own. Sometimes it may be deliberate or sometimes they may not be able to describe their special skill. For instance a particular skill in arts and crafts may only be demonstrated by an expert and not explained. In music, a curve of a musical phrase may be explained. 46

47. This makes Polayani to point out that we know more than we can tell or explain to others. “Another way of distinguishing between tacit and explicit knowledge is knowledge of the body, which is subjective, practical, analog while explicit knowledge is of the mind which is objective, theoretical and digital’. Quite often we talk about the body language, facial expressions and other signals that communicate quite a lot of the intention of the person but never expressed in words. Therefore, it is said that tacit knowledge is highly personal and hard to formalize, making it difficult to communicate or share with others. 47

48. What is Knowledge Management? Knowledge Management is about applying the collective knowledge of the entire workforce to achieve specific organizational goals. The aim of knowledge management is not necessarily to manage all knowledge, just the knowledge that is most important to the organization. It is about ensuring that people have the knowledge they need, where they need it, when they need it – the right knowledge, in the right place, at the right time. Barclay and Murray define knowledge management as a business activity with two primary aspects: 48

49. Treating the knowledge component of business activities as an explicit concern of business reflected in strategy, policy, and practice at all levels of the organization. Making a direct connection between an organisation’s intellectual assets – both explicit (recorded) and tacit (personal know-how) – and positive business results. 49

50. Knowledge management often encompasses identifying and mapping intellectual assets within the organization, generating new knowledge for competitive advantage within the organization, making vast amounts of corporate information accessible, sharing of best practices, and technology that enables all of the above – including groupware and intranets. That covers a lot of ground. And it should, because applying knowledge to work is integral to most business activities. 50

51. Knowledge Management caters to the critical issues of organizational adaptation, survival, and competence in face of increasingly discontinuous environmental change… Essentially, it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings”. 51

52. “The creation and subsequent management of an environment which encourages knowledge to be created, shared, learnt, enhanced, organized and utilized for the benefit of the organization and its customers.” Abell & Oxbrow, Tfpl Ltd. 2001. “Knowledge is power, which is why people who had it in the past often tried to make a secret of it. In post- capatalism, power comes from transmitting information to make it productive, not from hiding it”, Peter Drucker. 52

53. “Knowledge Management is not about data, but about getting the right information to the right people at the right time for them to impact the bottom line”, IBM 53

54. The Need for Knowledge Management The increasing use of electronic group collaboration tools to support teamwork has fueled interest in the ways by which what goes on when people use those tools can be captured, stored, and reused by others. Called ‘knowledge management’, this is important for enterprises whose principal currency is knowledge, rather than physical or financial resources. 54

55. These are enterprises who have always been wholly devoted to knowledge work, such as consultancies; a growing number of enterprises who discover that knowledge of how to produce products is as salable as the products themselves; and any enterprise who realizes that its knowledge is an asset to be managed. 55

56. The core issue of knowledge management is to place knowledge under management remit to get value from it – to realize intellectual capital. That intellectual capital can be regarded as a major determiner of the difference between a company’s book price and the total value of its stock. Why do we need to manage knowledge? Ann Macintosh of the Artificial Intelligence Applications Institute (University of Edinburgh) has written a “Position Paper on Knowledge Asset Management” that identifies some of the specific business factors including: 56

57. Marketplaces are increasingly competitive and the rate of innovation is rising. Reductions in staffing create a need to replace informal knowledge with formal methods. Competitive pressures reduce the size of the work force that holds valuable business knowledge. The amount of time available to experience and acquire knowledge has diminished. Early retirements and increasing mobility of the work force lead to loss of knowledge. There is a need to manage increasing complexity, as small operating companies are trans-national sourcing operations. Changes in strategic direction may result in the loss of knowledge in a specific area. 57

58. Conclusion Knowledge and information have become the medium in which business problems occur. As a result, managing knowledge represents the primary opportunity for achieving substantial savings, significant improvements in human performance, and competitive advantage. Knowledge management tools don’t really manage knowledge, but help capture, organize, store and transmit source material from which an individual may acquire knowledge. Whether an individual does acquire knowledge from a source depends on a dynamic interaction in which two factors are important here: 58

59. The similarity between the person’s context (their situation, history and assumptions) and the context described. The degree of congruence between how the material is structured and how the structure of the domain appears to the reader. Central to current concerns is the issue of team knowledge management. Teams, described as the power house of the effective enterprise, are more intractable from a knowledge management point of view than individuals. By their very nature teams create a great deal of new knowledge, which as such is of high value to the enterprise. 59

60. Differences between Information Management and Knowledge Management Information management is the harnessing of the information resources and information capabilities of the organization in order to add and create value both for itself and for its clients or customers. Knowledge management is a framework for designing an organization’s goals, structures, and processes so that the organization can use what it knows to learn and to create value for its customers and community. A KM framework involves designing and working with the following elements: 60

61. Categories of organizational knowledge (tacit knowledge, explicit knowledge, cultural knowledge) Knowledge processes (knowledge creation, knowledge sharing, knowledge utilization) Organizational enablers (vision and strategy; roles and skills; policies and processes; tools and platforms) 61

62. IM provides the foundation for KM, but the two are focused differently. IM is concerned with processing and adding value to information, and the basic issues here include access, control, coordination, timeliness, accuracy, and usability. KM is concerned with using the knowledge to take action, and the basic issues here include codification, diffusion, practice, learning, innovation, and community building. 62

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64. Introduction: Data refers to “anything that is given”, or “something given”. Data is plural of “datum”. Data is raw. It may be in any form, which can be used. The data cannot be defined unless we know the value assigned to it. Ex: - Data is used in discussion of problems in Geometry & Engineering. Such usage is the origin of data as a concept in computer science: data are numbers, words, images, etc., accepted as they stand. Data is an observed fact, obtained on the basis of systematic survey. 64

65. Definition: According to Devenport and Prusak - “Data is a set of discrete, objective facts about events… Data described only a part of what happened; it provides no judgment or interpretation and no sustainable basis of action… Data says nothing about its own importance or relevance”. The CODAT (Committee on Data for Science and Technology) defines data as a “crystallized presentation of the essence of scientific knowledge in most accurate form”. Random House Webster Computer and Internet Dictionary defines data as – “distinct pieces of information, usually formatted in a special way”. 65

66. Types of Data: Data in Sciences: CODATA has recognized scientific data which are repented as follows:  Data with Reference to Time Factor: Based on the time the data can be classified into two categories. Time independent data: The term refers to the data, which can be measured repeatedly, e.g., data in Geosciences and Astronomy such as geological structures, rocks, fixed stars etc. 66

67. Time dependent data: These can be measured only once, e.g., certain geophysical or cosmological phenomena like volcanic eruptions and solar flares. Likewise, data pertaining to rare fossils are time-dependent data.  Data with reference to location factor: Data with reference to location factor can be categorized as follows: Location independent data: These are independent of the location of objects measured e.g., data on pure Physics and Chemistry. 67

68. Data with reference to mode of generation:  Primary data: Data are primary when obtained by experiment or observation designed for the measurement, e.g., values of velocity derived by measuring length and time.  Derived data: Combining several primary data with the aid of a theoretical model derives these data.  Theoretical data: These are derived by theoretical calculations. Basic data such as fundamental constants are used in theoretical calculations, e.g., data concerning solar eclipses are predicted with the use of celestial mechanics. 68

69. Data with reference to nature of quantitative values Determinable data: Data on a quantity, which can be assumed to take a definite value under a given condition, are known as determinable data. Time-dependent data are usually determinable data, if the given condition is understood to include the specification of time. Stochastic data: Data relating to a quantity, which take fluctuating values from one sample to another, from one measurement to another, under a given condition, are referred to as stochastic. In Geosciences, most data are stochastic. 69

70. Data with reference to terms of expression Quantitative data: these are measures of quantities expressed in terms of well-defined units, changing the magnitude of a quality to a numerical value. Most data in Physical Sciences are quantitative data.  Semi-quantitative data: These data consists of affirmative or negative answers to posed questions concerning different characteristics of the objects involved.  e.g., in Biology, classification of organisms is based upon a set of ‘Yes’ and ‘No’ responses to questions concerning morphological, biological and other characteristics of species.  Such data are regarded as semi quantitative. ‘Yes’ and ‘No’ can be coded as ‘1’ and ‘0’ (zero) for obtaining data. 70

71. Qualitative data: The data expressed in terms of definitive statements concerning scientific objects are qualitative in nature. Qualitative data in this sense are almost equivalent to established knowledge. 71

72. Data with reference to mode of presentation Numerical data: These are presented in numerical values, e.g., most quantitative data fall in this category. Graphic data: Here data are presented in graphic form or as models. In some cases, graphs are constructed for the sake of helping users grasp a mass of data by visual perception. Charts and maps also belong to the category. 72

73. Graphic data 73

74. Symbolic data: These are presented in symbolic form, e.g., symbolic presentation of weather data. 74

75. Types of data in social sciences: Nominal data: The nominal scale is used for assigning numbers as the identification of individual unit. For example, the classification of journals according to the discipline that belong to, may be considered as nominal data. If numbers are assigned to describe the categories the numbers represent only the name of the category. 75

76. Ordinal data Interval data ordered categories of data and the difference between various categories are of equal measurement for example, we can measure the IQ (Intelligent Quotient) of a group of children. After assigning numerical value to the IQ of each child, the data can be grouped with interval of 10, like 0 to 10 to 20, 20 to 30 and so on. In this case, ‘0’ does not mean the absence of intelligence and children with IQ ‘20’ are not doubly intelligent than children with IQ ‘10’. 76

77. Ratio Data: Ratio data are the quantitative measurement of a variable in terms of magnitude. In ratio data, we can say that one thing is twice of thrice of another as for example, measurements involving weight, distance, price, etc. Data with reference to continuity Continues data: Continuous data are infinite set of possible values. Between ranges there are infinite possible values. For example, height of an individual is not restricted to values like 155 cm and after that to 156 cm it can be 155.59 cm or 155.99 cm continuous value. 77

78. Discrete data: The discrete data are finite or potentially countable set of values. For example, the number of members in a library it can be 3575 or 2599 but certainly not 2599 ½. Similarly the number of citizens in a country, the number of vehicles registered is the examples of discrete data. 78

79. Data with reference to number of characteristics Univariate data: Univariate data: are obtained when one charectoristics is used for observation.  e.g., the performance of the student in a given class. Bivariate data: Bivariate data result when instead of one two characteristics are measured simultaneously.  e.g., height and weight of tenth class students. Multivariate data: Multivariate data consist of observation on there or more characteristics.  e.g., family size, income and savings in a metropolitan city in India. 79

80. Data with reference to time Time series data: Data recorded in a chronological order across time are referred to as time series data. It takes different values at different times. e.g., the number of books added to a library in different years, monthly production of steel in a plant, yearly intake of students in university. Cross-sectional data: This refers to data for the same unit or for different units at a point of time. e.g., data across sections of people, region or segments of the society. 80

81. Data with reference to origin Primary data: The data obtained first hand from individuals by direct observation, counting and measurement or by interviews or mailing a questionnaire are called primary data. It may be complete enumeration of sampling e.g., data collected from a market survey. Secondary data: The data collected initially for the purpose and already published in books or respects but are used later on for some other purpose are referred to as secondary data.  For example, data collected from census reports, books, data monographs, etc. 81

82. Data with reference to characteristics Quantitative data: When the characteristic of observation is quantified we get quantitative data. Quantitative data result from the measurement of the magnitude of the characteristic used. For example, age of a person, price of a commodity, income of a family etc. Qualitative data: When the characteristic of observation is a quality of attribute, we get qualitative data. For example sex or coloure of a person or intelligence of a student. 82

83. Nature of Data The value of attained by data with specific items then transformed into meaningful form to perform a function is the nature of data.. The nature of data in computers may be numeric, alphanumeric, text; graphics etc., in sciences and social science the data to a large extent a quantitative data are numerical data. he nature of data in science with reference to types of data is as follows: 83

84. Numerical Data: The data measured in the science is derived and stated in numerical values. Descriptive data: The nature of data is descriptive expressed in terms of definitive statements concerning the objects. Graphic and Symbolic Data: The nature of data is modes of presentation, which enables users to grasp data by visual perception. 84

85. Enumerative data: Most data in social science are enumerative in nature. However, they are refined with the help of statistical techniques to make them more meaningful. Descriptive data: All qualitative data in social sciences can be descriptive in nature. These can be in the form of definitive statements. 85

86. Properties of data: For examining the properties of data, reference to the various definitions of data discussed in section earlier. Reference to these definitions reveals that following are the properties of data: (1) Amenability to use, (2) Clarity, (3) Accuracy and (4) The quality of being the essence of the matter. 86

87. Amenability to use From the dictionary meaning of data it is learnt that data are facts used in deciding something. In short, data are meant to be used as a basis for arriving at definitive conclusions. They are not required, if they are not amenable to use. The use may differ with the context. Amenability to use nevertheless remains a characteristic of data. 87

88. Clarity According to CODATA definition, data are a crystallized presentation. This means data should necessarily display clarity so essential for communicating the essence of the matter. Without clarity, the meaning desired to be communicated will remain hidden. 88

89. Accuracy Data should be real, complete and accurate. Accuracy is thus an essential property of data. Since data offer a basis for deciding something, they must necessarily be accurate if valid conclusions are to be drawn. 89

90. Compression Large amounts of data are always compressed to make them more meaningful. To present the essence of the matter, it is necessary to compress data. Compress date are manageable and can be grasped quickly. There exist a number of a number of techniques to compress data to a manageable size. Graphs and charts are some examples of compressed data. 90

91. Refinement Data require processing of refinement. When refined, they are capable of leading to conclusions or even generalizations. This refinement can then discover new facts. Bradford’s bibliography denoting the scatter of a subject of Garfield’s historiography denoting the development of a discipline are two examples of data refinement. Conclusions can drawn only when data are processed or refined. 91

92. Period of Data In science the interpretations and conclusions are mainly drawn keeping in view the whole text of the subject. In social science and humanities, however, the cumulative period is not taken into account of data collection. The importance of data in library service is manifold. Librarians are users of data in more than one way. They collect bibliographic data for providing services and generate and use non-bibliographic data for managing these services. 92

93. Interrelationship of Data, Information and Knowledge Data has commonly been seen as simple facts that can be structured to become information, in turn, becomes knowledge when it is interpreted, put into context, or when meaning is added to it. The common idea is that data is something less than information, and information is less than knowledge. Moreover, it is assumed that we first need to have data before information can be created and only when we have information, knowledge can emerge. 93

94. The interrelations of the concept of data, information and knowledge will be understood from the following example: Data- Raw material- Cotton Information- Intermediary- Yarn knowledge - Finished product- Cloth. 94