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By: Aman Kumar Kushwaha
Enroll. No: 245/17
Master Of Library And Information Sciences
2nd Semester
Session: 2018-19
Babasaheb Bhimrao Ambedkar University, Lucknow
SCIENCE INDICATORS
& MAPPING OF
SCIENCE
SCIENCE INDICATORS
 Indicators for science and technology may be
defined as "statistics which measure
quantifiable aspects of the creation,
dissemination and application of science and
technology. These indicators should help to
describe the science and technology system,
enabling better understanding of its structure, of
the impact of policies and programmes on it,
and of the impact of science and technology on
society and the economy." [Martin B. Wilk,
Stalislics Canatla, A Framework for Measuring
Research and Development Expenditures in
Canada, Catalogue 88-506E, preface.]
Present Scenario
 Today many countries and international
organizations produce science and technology
indicators. Notable among them are the Science
and Engineering Indicators, published biennially
since 1972 by the National Science Foundation
of the USA, and the European Report on S&T
Indicators, published since 1974 by the
European Commission.
 In India, the Department of Science and
Technology has a division called the National
Science and Technology Management
Information System, which produces valuable
statistical information on science and
technology in India.
What Are Science Indicators And How-are They
Different From R&D Statistics?
 Science and technology indicators, says a 1979 OECD
document, are a series of data designed to answer questions
about the current state of and/or changes in the science and
technology enterprise, its internal structures, its relationship with
the outside world, and the degree to which it is meeting the goals
set for it by those within or without.
 In the words of Giorgio Sirilli of Italy's National Council of
Research, "The purpose and function of science indicators are to
follow changes in the scientific enterprise and its components
over time, and thereby to reveal strengths and weaknesses as
they begin to develop. Such indicators, updated regularly, can
provide early warnings of trends and, taken together, can make
decision-makers more aware of the interrelationships of the many
variables that describe a scientific system's effort. Hence they can
assist those who set priorities for the enterprise and allocate
resources to it". [See Hiroko Morita-Lou (ed.), 1985. Science and
Technology Indicators for Development, UNCSTD and Westview
The Use Of Science And Technology Indicators
 The primary purpose of S&T indicators is to guide the decision of
S&T policy makers. Systematic and appropriate S&T Indicators
would provide the policy makers with an indication of the status of
the national S&T system and the relationship between scientific
and technological efforts and economic growth. They can serve
as instruments of planning, evaluation, and resource allocation.
 S&T indicators that explain historical trends or relationships
between variables at a point in time may be useful in determining
the nature and level of resources to be allocated to scientific and
technological endeavours and to sectors that support such
activity. They may also provide the necessary data for assessing
past performance in capacity building and utilization.
 With the increased importance of S&T in a nation’s economic
system, S&T Indicators have been developed to describe and
map the national system of innovation so that national
competitive advantages could be identified and promoted.
Types Of Indicators
Indicators used in the assessment of S&T can be
of different types, and so it is necessary to make
some a priori choices as to which types one wants
to utilize in one's evaluation scheme. The
following are the elegant topology of types of
indicators.
 Input vs. Output
 Quantitative vs. Qualitative
 Activity, Productivity and Progress
 Quality, Importance and Impact
 Functional vs. Instrumental Indicators
Input Vs. Output
 Input-output analysis came to prominence with
the work of the economist Wassily Leontief. It is
much easier to measure input than output.
 For example, one can measure the amount of
funds invested in research, the number and
kinds of institutions established for scientific
activities, and number of scientists trained and
employed for research, etc. On the other hand,
the output of scientific knowledge is rather
intangible and hence hard to measure.
Quantitative Vs. Qualitative
 Some indicators can be strictly quantitative, and we
can assign a definite value on some definite scale
to describe some aspect of the S&T activity.
 For example, the number of scientists working in a
given institution or on a given project.
 Quantitative indicators have a definite intellectual
appeal, giving the impression of being more
objective, more precise, and more reliable than
mere qualitative impressions.
Activity, Productivity And Progress
 In describing what we want to find indicators for, it is
useful to distinguish among the three concepts of
scientific (or technological) activity, productivity, and
progress.
 Productivity would mean going a step further from activity
and assessing whether all the activities involved in a
particular setting actually advance the attainment of an
eventual goal or not. That is, we would have to ascertain
that the activity carried out is. in the right direction and is
done well enough to move towards the given goal.
 Finally, progress would consist of measuring the degree
to which all the productivity described brought us closer to
our task. It is clear from this picture that while what would
matter most is the measurement of progress, what is
Quality, Importance And Impact
 Another useful three-way distinction can be made
among indicators along the trichotomy: quality,
importance, and impact.
 The quality of research refers to how well it has been
done, whether it is elegant, error free and general,
and how intriguing the results are. It is a relative
indicator and obviously different people may judge it
differently.
 Importance denotes the potential influence on related
research activities under ideal conditions,
extrapolated into the unknown future.
 Impact means the actual influence that piece of
research will have on the course of science and its
various aims and use in the future, something that
may be influenced by many factors, many extraneous
to science and its various aims and applications.
Functional vs. Instrumental Indicators
 We can develop indicators for certain functions of
S&T activities (e.g., for research results), or we may
want to evolve indicators for certain tools and
instruments that are used in the S&T infrastructure
(such as for the upkeep and maintenance of scientific
equipment or for management methods of scientific
research).
 While in the ultimate analysis what matters more are
the functional aspects of the S&T system, for
diagnostic purposes instrumental indicators may be
very useful and in fact even superior to purely
functional ones in that they may more readily point at
various remedial measures that can be taken to
eliminate certain deficiencies.
MAPPING OF SCIENCE
 Mapping attempts to bring out the cognitive
structure of knowledge. It helps us understand the
relational and structural aspects of scholarship and
its dynamics.
 The notion that science can be mapped was first
stated by Derek J. de Solla Price, the author of
Science since Babylon and Little Science, Big
Science, in the mid-1960s. But the idea that
knowledge could be represented spatially has been
there even before. The very word "field' (to denote
a subject or discipline) carries with it spatial
connotations.
INTRODUCTION
 Mapping Science is an area which is one of the
applications of scientometric methods and tools.
Studies and research on this area are being
conducted in many countries to identify different
facts of science such as structure of various
disciplines and sub disciplines and their
interrelationships, the scientists and their
contributions in these disciplines, the important
journals and authors contributing to these fields etc.
 The construction of both kinds of maps of
knowledge (or science) depends largely on
counting surrogates of knowledge, viz. papers
published in professional journals and cross-
citations among such papers.
 Such bibliometric maps of science may be of help
in improving information retrieval, in research
management, and in science policy, and as a tool in
science studies, in particular in sociological and
historical studies of science.
 While it is relatively easy to map science output by
nation or by subject category (descriptive mapping),
it is far more difficult to describe subject matter
(cognitive mapping).
COGNITIVE MAPPING
 There are four principal ways of constructing
cognitive maps. All of them are based on
surrogates of knowledge, viz. published papers and
references cited therein.
 Journal-to-journal Citation Maps
 Co-citation Maps
 Co-word Maps
 Co-classification Maps
Journal-to-journal Citation Maps
 The use of inter journal citation-frequency rests on
the assumption that it serves as an indication of the
magnitude of subject relation between journals.
 Journals are the primary formal channels for
communicating theories, methods and empirical
findings to researchers, and therefore they may
indicate changing research frontiers and disciplinary
transitions.
 The network of journal-journal citation links thus
reflects the macro-level structure of scientific
activities. Changes therein indicate the dynamics of
scientific fields.
 Such data have been used to rank the importance of
Co-citation Maps
 Co-citation coupling is used to establish a subject
similarity between two documents. If papers A and B
are both cited by paper C, they may be said to be
related to one another, even though they do not
directly quote each other.
 If papers A and B are both cited by many other
papers, they have a stronger relationship. The
more papers they are cited by, the stronger their
relationship is.
 Co-citation maps show the extent to which two
articles are cited together in other articles. The
method for mapping such structures of science is
Co-word Maps
 Analogous to co-citation analysis, counts of word co-
occurrences (co-word frequencies) are used to
construct a co-word structure representing research
themes in a discipline and their inter-relations, thus
capturing relevant features of the cognitive structure of
scientific (sub) specialties.
 The idea is if two or more articles use several keywords
in common, then those articles have something in
common.
 Unlike co-citation analysis, it can provide a quick idea
of the actual content of the research topic dealt with in
the literature. It is especially useful in subfields and
research fronts which do not conform to the normal
Co-classification Maps
 Co-classification maps are based on the analysis of
the co-occurrence of subject-classification terms. The
classification terms (words or phrases) mostly
represent cognitive elements which relate to scientific
topics, specialties, or fields.
 Like co-word and co-citation methods, this approach
hinges on the assumption that these items reflect the
structure and degree of relatedness in research
publications.
 Co-classification analysis is simpler than co-citation
and co-word analyses. It can quickly provide a useful
overview of a field. It can offer visualisation of the
gross or coarse structure of a research field. But, it
may not work welt with multidisciplinary fields, as
most classifications are still discipline-oriented.
When Does One Use Co-citation, Co-word And
Co-classification Analysis?
 Indeed, there is an on going rivalry between the
supporters of co-citation analysis and co-word
analysis. But as a rough guide, one can use co-
classification analysis as a first step to gain
insight into the coarse structure of knowledge.
One can use, at the meso level, journal co-
citation and author co-citation analysis to
analyse specific subfields or specialties. For fine
structure mapping or micro-level analysis of a
research front, one can use either document co-
citation analysis or co-word analysis, depending
on the characteristics of the literature of the
DESCRIPTIVE MAPPING
 A kind of mapping of knowledge, which aims to
provide an overview of the distribution of
production of knowledge at different levels of
aggregation - at the level of nations, states
(within a nation), cities/towns, institutions,
journals, disciplines, sub-disciplines, etc. this
kind of mapping is called as descriptive
mapping.
 Much of the work in cognitive mapping is done
in the United States and Europe. Most mapping
work in developing countries is of the
descriptive kind. In descriptive mapping one is
concerned with quantifying different aspects of
scientific activity at different levels of
References
 IGNOU. (2017). Unit-13 Science Indicator
[PDF]. Retrieved from
http://egyankosh.ac.in/handle/123456789/11
372
 IGNOU. (2017). Unit-14 Mapping of Science
[PDF]. Retrieved from
http://egyankosh.ac.in/handle/123456789/11
371
Science Indicators & Mapping of Science by Aman Kr Kushwaha

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Science Indicators & Mapping of Science by Aman Kr Kushwaha

  • 1. By: Aman Kumar Kushwaha Enroll. No: 245/17 Master Of Library And Information Sciences 2nd Semester Session: 2018-19 Babasaheb Bhimrao Ambedkar University, Lucknow SCIENCE INDICATORS & MAPPING OF SCIENCE
  • 2. SCIENCE INDICATORS  Indicators for science and technology may be defined as "statistics which measure quantifiable aspects of the creation, dissemination and application of science and technology. These indicators should help to describe the science and technology system, enabling better understanding of its structure, of the impact of policies and programmes on it, and of the impact of science and technology on society and the economy." [Martin B. Wilk, Stalislics Canatla, A Framework for Measuring Research and Development Expenditures in Canada, Catalogue 88-506E, preface.]
  • 3. Present Scenario  Today many countries and international organizations produce science and technology indicators. Notable among them are the Science and Engineering Indicators, published biennially since 1972 by the National Science Foundation of the USA, and the European Report on S&T Indicators, published since 1974 by the European Commission.  In India, the Department of Science and Technology has a division called the National Science and Technology Management Information System, which produces valuable statistical information on science and technology in India.
  • 4. What Are Science Indicators And How-are They Different From R&D Statistics?  Science and technology indicators, says a 1979 OECD document, are a series of data designed to answer questions about the current state of and/or changes in the science and technology enterprise, its internal structures, its relationship with the outside world, and the degree to which it is meeting the goals set for it by those within or without.  In the words of Giorgio Sirilli of Italy's National Council of Research, "The purpose and function of science indicators are to follow changes in the scientific enterprise and its components over time, and thereby to reveal strengths and weaknesses as they begin to develop. Such indicators, updated regularly, can provide early warnings of trends and, taken together, can make decision-makers more aware of the interrelationships of the many variables that describe a scientific system's effort. Hence they can assist those who set priorities for the enterprise and allocate resources to it". [See Hiroko Morita-Lou (ed.), 1985. Science and Technology Indicators for Development, UNCSTD and Westview
  • 5. The Use Of Science And Technology Indicators  The primary purpose of S&T indicators is to guide the decision of S&T policy makers. Systematic and appropriate S&T Indicators would provide the policy makers with an indication of the status of the national S&T system and the relationship between scientific and technological efforts and economic growth. They can serve as instruments of planning, evaluation, and resource allocation.  S&T indicators that explain historical trends or relationships between variables at a point in time may be useful in determining the nature and level of resources to be allocated to scientific and technological endeavours and to sectors that support such activity. They may also provide the necessary data for assessing past performance in capacity building and utilization.  With the increased importance of S&T in a nation’s economic system, S&T Indicators have been developed to describe and map the national system of innovation so that national competitive advantages could be identified and promoted.
  • 6. Types Of Indicators Indicators used in the assessment of S&T can be of different types, and so it is necessary to make some a priori choices as to which types one wants to utilize in one's evaluation scheme. The following are the elegant topology of types of indicators.  Input vs. Output  Quantitative vs. Qualitative  Activity, Productivity and Progress  Quality, Importance and Impact  Functional vs. Instrumental Indicators
  • 7. Input Vs. Output  Input-output analysis came to prominence with the work of the economist Wassily Leontief. It is much easier to measure input than output.  For example, one can measure the amount of funds invested in research, the number and kinds of institutions established for scientific activities, and number of scientists trained and employed for research, etc. On the other hand, the output of scientific knowledge is rather intangible and hence hard to measure.
  • 8. Quantitative Vs. Qualitative  Some indicators can be strictly quantitative, and we can assign a definite value on some definite scale to describe some aspect of the S&T activity.  For example, the number of scientists working in a given institution or on a given project.  Quantitative indicators have a definite intellectual appeal, giving the impression of being more objective, more precise, and more reliable than mere qualitative impressions.
  • 9. Activity, Productivity And Progress  In describing what we want to find indicators for, it is useful to distinguish among the three concepts of scientific (or technological) activity, productivity, and progress.  Productivity would mean going a step further from activity and assessing whether all the activities involved in a particular setting actually advance the attainment of an eventual goal or not. That is, we would have to ascertain that the activity carried out is. in the right direction and is done well enough to move towards the given goal.  Finally, progress would consist of measuring the degree to which all the productivity described brought us closer to our task. It is clear from this picture that while what would matter most is the measurement of progress, what is
  • 10. Quality, Importance And Impact  Another useful three-way distinction can be made among indicators along the trichotomy: quality, importance, and impact.  The quality of research refers to how well it has been done, whether it is elegant, error free and general, and how intriguing the results are. It is a relative indicator and obviously different people may judge it differently.  Importance denotes the potential influence on related research activities under ideal conditions, extrapolated into the unknown future.  Impact means the actual influence that piece of research will have on the course of science and its various aims and use in the future, something that may be influenced by many factors, many extraneous to science and its various aims and applications.
  • 11. Functional vs. Instrumental Indicators  We can develop indicators for certain functions of S&T activities (e.g., for research results), or we may want to evolve indicators for certain tools and instruments that are used in the S&T infrastructure (such as for the upkeep and maintenance of scientific equipment or for management methods of scientific research).  While in the ultimate analysis what matters more are the functional aspects of the S&T system, for diagnostic purposes instrumental indicators may be very useful and in fact even superior to purely functional ones in that they may more readily point at various remedial measures that can be taken to eliminate certain deficiencies.
  • 12. MAPPING OF SCIENCE  Mapping attempts to bring out the cognitive structure of knowledge. It helps us understand the relational and structural aspects of scholarship and its dynamics.  The notion that science can be mapped was first stated by Derek J. de Solla Price, the author of Science since Babylon and Little Science, Big Science, in the mid-1960s. But the idea that knowledge could be represented spatially has been there even before. The very word "field' (to denote a subject or discipline) carries with it spatial connotations.
  • 13. INTRODUCTION  Mapping Science is an area which is one of the applications of scientometric methods and tools. Studies and research on this area are being conducted in many countries to identify different facts of science such as structure of various disciplines and sub disciplines and their interrelationships, the scientists and their contributions in these disciplines, the important journals and authors contributing to these fields etc.
  • 14.  The construction of both kinds of maps of knowledge (or science) depends largely on counting surrogates of knowledge, viz. papers published in professional journals and cross- citations among such papers.  Such bibliometric maps of science may be of help in improving information retrieval, in research management, and in science policy, and as a tool in science studies, in particular in sociological and historical studies of science.  While it is relatively easy to map science output by nation or by subject category (descriptive mapping), it is far more difficult to describe subject matter (cognitive mapping).
  • 15. COGNITIVE MAPPING  There are four principal ways of constructing cognitive maps. All of them are based on surrogates of knowledge, viz. published papers and references cited therein.  Journal-to-journal Citation Maps  Co-citation Maps  Co-word Maps  Co-classification Maps
  • 16. Journal-to-journal Citation Maps  The use of inter journal citation-frequency rests on the assumption that it serves as an indication of the magnitude of subject relation between journals.  Journals are the primary formal channels for communicating theories, methods and empirical findings to researchers, and therefore they may indicate changing research frontiers and disciplinary transitions.  The network of journal-journal citation links thus reflects the macro-level structure of scientific activities. Changes therein indicate the dynamics of scientific fields.  Such data have been used to rank the importance of
  • 17. Co-citation Maps  Co-citation coupling is used to establish a subject similarity between two documents. If papers A and B are both cited by paper C, they may be said to be related to one another, even though they do not directly quote each other.  If papers A and B are both cited by many other papers, they have a stronger relationship. The more papers they are cited by, the stronger their relationship is.  Co-citation maps show the extent to which two articles are cited together in other articles. The method for mapping such structures of science is
  • 18. Co-word Maps  Analogous to co-citation analysis, counts of word co- occurrences (co-word frequencies) are used to construct a co-word structure representing research themes in a discipline and their inter-relations, thus capturing relevant features of the cognitive structure of scientific (sub) specialties.  The idea is if two or more articles use several keywords in common, then those articles have something in common.  Unlike co-citation analysis, it can provide a quick idea of the actual content of the research topic dealt with in the literature. It is especially useful in subfields and research fronts which do not conform to the normal
  • 19. Co-classification Maps  Co-classification maps are based on the analysis of the co-occurrence of subject-classification terms. The classification terms (words or phrases) mostly represent cognitive elements which relate to scientific topics, specialties, or fields.  Like co-word and co-citation methods, this approach hinges on the assumption that these items reflect the structure and degree of relatedness in research publications.  Co-classification analysis is simpler than co-citation and co-word analyses. It can quickly provide a useful overview of a field. It can offer visualisation of the gross or coarse structure of a research field. But, it may not work welt with multidisciplinary fields, as most classifications are still discipline-oriented.
  • 20. When Does One Use Co-citation, Co-word And Co-classification Analysis?  Indeed, there is an on going rivalry between the supporters of co-citation analysis and co-word analysis. But as a rough guide, one can use co- classification analysis as a first step to gain insight into the coarse structure of knowledge. One can use, at the meso level, journal co- citation and author co-citation analysis to analyse specific subfields or specialties. For fine structure mapping or micro-level analysis of a research front, one can use either document co- citation analysis or co-word analysis, depending on the characteristics of the literature of the
  • 21. DESCRIPTIVE MAPPING  A kind of mapping of knowledge, which aims to provide an overview of the distribution of production of knowledge at different levels of aggregation - at the level of nations, states (within a nation), cities/towns, institutions, journals, disciplines, sub-disciplines, etc. this kind of mapping is called as descriptive mapping.  Much of the work in cognitive mapping is done in the United States and Europe. Most mapping work in developing countries is of the descriptive kind. In descriptive mapping one is concerned with quantifying different aspects of scientific activity at different levels of
  • 22. References  IGNOU. (2017). Unit-13 Science Indicator [PDF]. Retrieved from http://egyankosh.ac.in/handle/123456789/11 372  IGNOU. (2017). Unit-14 Mapping of Science [PDF]. Retrieved from http://egyankosh.ac.in/handle/123456789/11 371