Anyone working in scientometrics and informetrics quickly learns that good analysis depends on good resources. Citation data, ready-made indicators, visualization software, and reliable documentation are scattered across dozens of websites, and knowing which ones to trust saves enormous time. This guide maps out the most dependable online destinations for bibliometric and scientometric work, from data portals run by leading research centres to the free tools that let students run their first citation analysis without spending a rupee. Whether you are writing a dissertation, evaluating research output, or simply trying to understand how scholarly impact is measured, these websites form the working infrastructure of the field.

Table of Contents

Informetric research portals

A handful of dedicated portals act as the central hubs of the field, combining datasets, indicators, and software in one place. They are the natural starting point because they are built and maintained by the same research communities that define how metrics are calculated.

The Centre for Science and Technology Studies (CWTS)

The Centre for Science and Technology Studies at Leiden University is widely regarded as the most influential single institution in this space. According to its own description, CWTS studies the development of science and technology using large-scale databases of publications and patents and is recognised internationally in bibliometrics, scientometrics, and informetrics. Its public-facing resources are what make it so valuable to students.

The first is the CWTS Leiden Ranking, an annual university ranking built entirely on bibliometric indicators rather than reputation surveys. The 2025 Traditional Edition covers more than 1,500 universities using Web of Science data, while the newer Open Edition draws on the OpenAlex database and includes over 2,800 institutions. The ranking is transparent about its methods, which makes it a useful teaching example of how indicators like the share of publications among the top 10% most cited are constructed.

The second is CWTS Journal Indicators, which offers free access to journal-level metrics calculated from Scopus. Its signature measure is the SNIP indicator (source normalized impact per paper), which corrects for differences in citation behaviour between fields so that journals from different disciplines can be compared more fairly. For anyone deciding where to publish, this is a more honest tool than the raw impact factor.

The Bibliometric Toolbox tradition

The phrase “Bibliometric Toolbox” originally referred to a set of programs developed by Leo Egghe and Ronald Rousseau to accompany their foundational text Introduction to Informetrics, published in 1990. These two scholars jointly received the Derek de Solla Price Medal, the field’s highest honour, and Egghe went on to become the founding editor of the Journal of Informetrics. Their toolbox illustrated laws such as Lotka’s law and Bradford’s law in a hands-on way, and it shaped how a generation learned the mathematics behind the metrics.

Today that tradition continues through modern equivalents. The most prominent is bibliometrix, an open-source R package described in the Journal of Informetrics as a tool for comprehensive science mapping analysis. It imports data from Scopus and Web of Science, then runs co-citation, co-word, and collaboration analyses. Its point-and-click interface, Biblioshiny, removes most of the coding barrier, which makes it especially friendly for newcomers who are comfortable with spreadsheets but new to programming.

Academic and professional resources

Beyond data portals, several organisations and universities maintain websites built specifically to support learning, networking, and professional practice in scientometrics. These are the places to go when you want context rather than raw numbers.

The International Society for Scientometrics and Informetrics (ISSI)

The International Society for Scientometrics and Informetrics is the professional home of the field. Founded in Berlin in 1993 and incorporated in the Netherlands the following year, ISSI brings together scholars from more than 30 countries who study science using quantitative methods, including informetrics, scientometrics, and webometrics. Its website is more than an organisational front page.

It hosts an archive of conference proceedings stretching back decades, giving researchers a searchable record of how the field has evolved. It publishes Quantitative Science Studies, the society’s official open-access journal, so the latest theoretical and empirical work is freely readable rather than locked behind paywalls. The ISSI Newsletter keeps members updated on methodological developments, and the society’s award programmes, including the Derek de Solla Price Medal, signal which contributions the community considers landmark work. For a student trying to identify the key debates and key people, the ISSI site is the single best orientation point.

University-hosted research resources

Many universities maintain dedicated portals that bridge scientometric methods with the broader practice of scholarly communication. The University of New South Wales, for instance, has developed widely cited material on communicating science and research evaluation, the kind of resource that helps students see how citation metrics fit into the larger picture of how research is shared and assessed. Similar guides are common in university library systems, which increasingly offer bibliometrics support pages explaining the h-index, journal metrics, and responsible use of indicators.

CWTS also runs structured courses through its education programme, teaching participants to interpret citation statistics and to reflect critically on the proper and improper use of metrics in research evaluation. This emphasis on responsible use matters in the Indian context too, where bibliometric indicators increasingly influence faculty assessment, accreditation, and funding decisions. Treating an h-index as a complete measure of a scholar’s worth is precisely the error these resources are designed to prevent.

Educational content and tools

The final category is the most practical: the free software and learning material that let you actually run an analysis. These tools have democratised scientometric research, putting capabilities that once required expensive licences into the hands of any student with a laptop.

Visualization and mapping software

The standout tool here is VOSviewer, a free Java-based program developed at CWTS for building and visualizing bibliometric networks. It can map co-authorship between researchers, co-citation between publications, and co-occurrence of keywords, turning thousands of references into a readable map of a research field. Its companion CitNetExplorer focuses on citation networks over time. Both are widely taught and appear in countless published studies, which means tutorials and worked examples are easy to find.

Citation analysis and productivity tools

For quick, individual-level analysis, Publish or Perish remains a favourite. It retrieves citations from sources like Google Scholar and calculates a battery of metrics, including the number of papers, total citations, citations per paper, the h-index, and the g-index. Because Google Scholar has broad coverage of Indian journals and conference proceedings that are sometimes missing from Scopus or Web of Science, this tool is often more inclusive for researchers based in India.

A wider ecosystem of free software surrounds these flagship tools. BibExcel handles data preparation and basic analysis, CiteSpace detects emerging trends and turning points in a literature, and packages such as ScientoPy and the broader bibliometrix family extend the options for those who want scripted, reproducible workflows. Many of these are catalogued on researcher-maintained portals that list tools alongside short descriptions of what each does best.

Foundational reading and reference

Tools are only as good as your understanding of what they measure, so reference material belongs in any serious toolkit. Encyclopedic overviews such as the entries on informetrics and scientometrics are a sound starting point for definitions and history, tracing how the field moved from statistical bibliography in the 1920s to bibliometrics and scientometrics in the mid-twentieth century and finally to informetrics. For deeper grounding, review articles like the Springer survey on the literature of bibliometrics, scientometrics, and informetrics assemble the key papers and debates in one place. Reading a few of these before opening any software prevents the common mistake of generating impressive-looking metrics that you cannot actually interpret.

Used together, these resources cover the full research cycle. The data portals give you reliable indicators, the professional and academic sites supply context and standards, and the free tools let you carry out the analysis yourself. For a student in India starting out, a sensible path is to read the foundational overviews, register for the open resources at ISSI and CWTS, install bibliometrix or Publish or Perish, and practise on a small dataset from your own discipline before attempting anything ambitious.

What do you think? Which of these resources fits the kind of research questions you most want to answer, and how might responsible use of bibliometric indicators change the way research is evaluated in your own institution?

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References
  1. https://www.journalindicators.com/about
  2. https://www.leidenranking.com/
  3. https://www.journalindicators.com/
  4. https://shop.elsevier.com/books/becoming-metric-wise/rousseau/978-0-08-102474-4
  5. https://massimoaria.github.io/bibliometrix/
  6. https://www.issi-society.org/about/
  7. https://www.cwts.nl/education/bibliometrics-and-scientometrics-for-research-evaluation/bibliometric-course-leiden-nl
  8. https://en.wikipedia.org/wiki/Informetrics
  9. https://en.wikipedia.org/wiki/Scientometrics
  10. https://link.springer.com/article/10.1023/A:1017919924342

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Informetrics & Scientometrics

1 Information and Measurement

  1. Information Revisited
  2. Framework for Information Exchange
  3. Measurement Techniques
  4. Informativeness
  5. Standardization of Measurement

2 Measure of Information

  1. Information and Entropy
  2. Shannon Information
  3. Probabilistic Information
  4. Properties of Shannon Information
  5. Derivation of Shannon Information Formula
  6. Normalization Condition
  7. Relating Semantic Value to Shannon Type Measures
  8. Other Shannon Type Measures of Information
  9. Semantic Information
  10. Fuzzy Information Measure
  11. Other Information Measures

3 Informetrics – Definition, Scope and Evolution

  1. Definitions
  2. Scope
  3. Evolution
  4. Summary

4 Sociology of Science and Scientometrics

  1. Sociology of Science
  2. Growth of Scientific Knowledge
  3. Social Organization in Research Areas
  4. Approaches of Scientometrics to Sociology of Science
  5. Models of Growth of Knowledge

5 Organizations Engaged in Scientometrics and Informetrics Studies

  1. Organizations Engaged in or Supporting Scientometrics/Informetrics Studies
  2. Websites
  3. Research Groups/Discussion Groups
  4. Periodical Publications
  5. Conferences/Seminars/Workshops/Congresses
  6. Individuals Engaged in the Study and Research in Scientometrics/Informetrics

6 Law of Scattering and its Applications

  1. Introduction
  2. Historical Account
  3. Bradford’s Law
  4. Verbal Form of Bradford’s Law
  5. Applications of Bradford’s Law
  6. Graphical Representation of Bradford’s Law
  7. Conditions for Bradford’s Law
  8. Falling Tail of Bradford Curve: The Groos Droop
  9. Ambiguity in Bradford’s Law
  10. Fitting Bibliographic Data to Bradford’s Law

7 Rank and Size Frequency Models

  1. Representations and Organization of Numerical Data
  2. Size – Frequency Approach
  3. Rank – Frequency Approach
  4. Size – Frequency Models
  5. Rank – Frequency Cumulative (Fractional) Models
  6. Rank – Frequency Cumulative (Non-Fractional) Models
  7. Rank – Frequency Non – Cumulative Models

8 Informetrics Phenomena

  1. Terminology and Historical Development
  2. Selected Laws of Bibliometrics and Informetrics
  3. Informetrics Phenomena in Science
  4. Practical Applications of Informetrics

9 Analysis of Library Related Data

  1. Necessity for Analytical Studies in Libraries
  2. Citation Counting: A Versatile Tool for Journal Selection
  3. An Alternative Method of Citation Analysis
  4. Selection of New Source Journals to Eliminate Bias Due to Country, and Language
  5. Weightage Formula to Correct Citation for Post-War Periodicals
  6. Three New Bibliometric Parameters to Re-Rank Scientific Periodicals
  7. Garfield’s Methods for Cito-Analytical Studies
  8. Librametric Analysis
  9. Bibliometric Analysis
  10. Informetrics
  11. Scientometrics: Its Genesis, Scope, Definition, and Applications

10 User Studies

  1. User Studies
  2. Questionnaire Method
  3. Interview Method
  4. Diary Method
  5. Observation Method
  6. Planning a Survey
  7. Classification and Tabulation of Data
  8. Analysis of Data
  9. Presentation of Results
  10. Important User Studies
  11. Application of User Studies

11 Laws of Scientific Productivity

  1. Scientific Productivity – Influencing Factors
  2. Scientific Productivity – Problems in Measurement
  3. Scientific Productivity – Distribution Characteristics
  4. Lotka’s Law
  5. Statistical Distributions or Models
  6. Application of Lotka’s Law
  7. Goodness-of-Fit Test

12 Growth and Obsolescence of Literature

  1. Growth of Literature
  2. Obsolescence of Literature
  3. Growth Vs Obsolescence of Literature

13 Science Indicators

  1. Indicators
  2. Towards Science Indicators
  3. Historical Aspects
  4. Functions of Science Indicators
  5. S&T Indicators for the Developing Countries
  6. Types of Indicators
  7. Validity and Reliability of Indicators
  8. Building S&T Indicators
  9. Literature Based Indicators
  10. Patent Indicators

14 Mapping of Science

  1. Cognitive Mapping
  2. Journal-to-journal Citation Maps
  3. Co-citation Maps
  4. Co-word Maps
  5. Co-classification Maps
  6. Descriptive Mapping

15 Elements of Statistics

  1. Data and Its Measurement
  2. Graphical Representation
  3. Measures of Central Tendency
  4. Measure of Variability
  5. Correlation and Regression

16 Probability Distributions and their Applications

  1. Probability – Definition
  2. Random Variables
  3. Joint Probability Distribution
  4. Conditional Probability Distribution
  5. Some Special Distributions
  6. Applications of Probability

17 Regression Analysis

  1. Simple Linear Regression
  2. Multiple Regression
  3. Stepwise Regression
  4. Regression with Qualitative Explanatory Variables

18 Cluster Analysis and Factor Analysis

  1. Introduction
  2. Cluster Analysis
  3. Factor Analysis
  4. Examples of Cluster and Factor Analysis