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Scientometric and bibliometric analysis tools and software

  • You might also find this Wikipedia comparison of research networking tools and research profiling systems useful.

  • BajiMacro. Free Excel ad-on (Macro) that uses biblimetric data from Scopus, WoS etc , processed by Loet Leydesdort scripts (e.g. ISI.exe) to create co-occurance matrices.

  • Bibexcel. Free software designed by Olle Persson to assist a user in analyzing bibliographic data, or any data of a textual nature formatted in a similar manner. The idea is to generate data files that can be imported to Excel or any program that takes tabbed data records, for further processing. It can be used for co-citation, bibliographic coupling, mapping and clustering analysis.

  • Bibliometrix R package. A free tool that provides various routines for importing bibliographic data from SCOPUS and Clarivate Analytics' Web of Science databases, performing bibliometric analysis and building data matrices for co-citation, coupling, scientific collaboration analysis and co-word analysis.

  • BiblioTool. It is a set of python scripts (open source) written by Sebastian Grauwin. They can read ISI data in CSV format and do some analyses including co-occurrence map and bibliographic coupling.

  • CiteSpace. A free Java-based software for visualizing and analyzing trends and patterns in the scientific literature. It is designed as a tool for progressive knowledge domain visualization. Its primary source of input data is ISI WoS. But it also provides some simple interfaces for obtaining data from PubMed, arXiv, ADS, and NSF Award Abstracts. It can be used to generate geographic map overlays viewable in Google Earth based on the locations of authors.

  • CitNetExplorer. A free Java-based software tool developed by Uni of Leiden for visualizing and analyzing citation networks of scientific publications. It allows citation networks to be imported directly from the Web of Science database. Citation networks can be explored interactively, for instance by drilling down into a network and by identifying clusters of closely related publications.

  • CopalRed. (obsoleted) A free program written by Xavier Polanco for the analysis of scholarly publications and scientometric purposes for example for analysing and visualizing the network structure of a scientific field.

  • CRExplorer. Or Cited Reference Explorer is a free Java-based program that was primarily developed to identify those publications in a field, a topic or by a researcher which have been frequently cited. It is especially suitable to study the historical roots of this field, topic or researcher.

  • InCite Retrieve: a set of Python codes for retrieving journal impact factor values from InCite API.

  • InterDisciplinary Research (IDR). It's a free tool to measure and map interdisciplinary research. It creates overlay maps of science, as a method to explore the degree of interdisciplinarity of a set of publications.

  • IN-SPIRE. A commercial software for exploring and visualizing textual data, including Boolean and “topical” queries, term gisting, and time/trend analysis tools. It can be used to explore technical and patent literature, marketing and business documents, web data, accident and safety reports, newswire feeds and message traffic, and more.

  • Headstart. A free open-source software to visualize readership data from Mendeley. It presents users with the main areas in the field and lets them zoom into the most important publications within each area. It is intended to give researchers that are new to a field a head start on their literature review (hence the name). It has been developed by P. Kraker.

  • HistCite. (obsoleted) free software developed by E. Garfield to aid researchers in visualizing the results of literature searches in the Web of Science. It lets you analyze and organize the results of a search to obtain various views of the topic's structure, history, and relationships. It visualizes the citation network in a historical manner.

  • Loet Leydesdorff software, A set of free DOS-based pieces of software to parse, transform and analyse bibliometrics data obtained from sources such as Scopus, ISI, and Google Scholar for analyses such as coauthorship, international, institutional, inter-city collaboration networks, co-word, co-citation and bibliographic analysis and so on. Although they do not include visualization tools, they prepare the data for the creation of relational databases and visualization by other tools such as Pajek. ISI.exe reads ISI data in txt format and generates files suitable for creating a relational database.

  • Network Workbench. A free Java-based large-scale network analysis, modelling and visualization toolkit for biomedical, social science and physics research. It includes specific features for bibliometric studies.

  • Publish or Perish. A free software program that retrieves and analyzes academic citations Google Scholar and calculates No of papers, citations, average No. of citations per paper and per author and per year as well as h-index, g-index, and some more metrics.

  • SAINT: (obsoleted) (Science Assessment Integrated Network Toolkit). It is open-source software for scientometrics analysis and one of the few packages that can be used to convert ISI data into a relational database (dbm or accdb or sql files). There is a forum to discuss the issues related to SAINT. The software is not available on its original website anymore.

  • ScientoPY, a free open source scientometric software. You can read about it in this paper.

  • SciMAT. SciMAT (Science Mapping Anaylsis Tool) is a java-based open source (GPLv3) free software tool developed to perform a science mapping analysis under a longitudinal framework. SciMAT reads bibliographic data in different formats and creates a relational database in Sqlite 3 format and allows you to do different analyses. The advantage is that you can amend the data in the knowledgebase as you wish.

  • Sci2 Tool. A free Java-based modular toolset specifically designed for the study of science. It supports the temporal, geospatial, topical, and network analysis and visualization of scholarly datasets at the micro (individual), meso (local), and macro (global) levels. It has several visualization features.

  • Scientometric Project. A set of open-source Python scripts for some scientometric data analyses written by Theresa Velden.

  • Scopus API R code: This is some R code to query Scopus API and parse the results into a data frame. For instance, if you have a list of DOI and want to get citation data for them from Scopus.

  • Pybliometrics: Python-based API-Wrapper to access Scopus: A free Python library to cache and extract data from the Scopus, developed by M. E. Rose and J. R. Kitchin. You can read about it in this paper.

  • Sitkis: (obsoleted) Sitkis is a free Java-based software tool developed exclusively for bibliometric analysis. Sitkis provides tools for extremely streamlined analysis of bibliometric networks. Read more about it here.

  • VOSviewer. A free Java-based program, primarily intended to be used for analyzing and visualizing bibliometric networks. It can create maps of publications, authors, or journals based on a co-citation network or to construct maps of keywords based on a co-occurrence network.

  • Web of Science API: a set of Python code to retrieve the times cited counts for DOIs and/or PMIDs.

  • Webometric Analyst: a free Windows-based program for altmetrics, citation analysis, social web analysis and webometrics, including link analysis, developed by Prof. Mike Thelwall.

For a list of some of the tools used in scientometrics studies see Borner et al (2010) and for comparison of some of these software packages see Cobo et al. (2011).

Science Mapping Resources


    • Places & Spaces: Mapping Science. It is a collection of science maps and visualizations. It is exhibited in different places and they can be ordered.

    • Atlas of Science. This is a book by Katy Börner published by MIT press. It includes 500 colour illustrations of different science maps.

    • Excellence Mapping. This web application visualizes the scientific performance of institutions (universities or research-focused institutions) within specific subject areas (e.g. Chemical Engineering) as ranking lists and on maps.

Science Analysis Companies and Services

  • Academic Analytics. It is a provider of high-quality, custom business intelligence data and solutions for research universities in the United States and the United Kingdom. It helps universities identify their strengths and areas where improvements can be made.

  • Clarivate. It publishes Web of Knowledge and Web of Science and it also produces a few science analysis databases such as Journal Citation Reports, Science Watch, and Essential Science Indicators. WoS includes some analysis tools.

  • Elsevier. It is the publisher of Scopus database as well as SciVal which Is a suite of research tools that helps you evaluate, establish and execute your research strategies more effectively. SciVal Spotlight is a unique web-based strategic analysis tool that enables academic executives to make informed strategic decisions by measuring and evaluating an institution's research performance. It evaluates your institution's research output in a single interface. SciVal Funding is a web-based solution that gives research administrators and researchers in the pre-award stage access to current research funding opportunities and award information. It allows you to find the right funding opportunities and analyze the funding environment.

  • SCImago. Is a portal that includes the journals and country scientific indicators developed from the information contained in the Scopus. These indicators can be used to assess and analyze scientific domains.

  • Science Metrix. (now owned by Elsevier) It provides customized services in performance measurement and program evaluation using advanced bibliometric indicators and recognized quantitative and qualitative research methods. In 2010 it published a '30 Years in Science' report.

  • SciTech Strategies Inc. It mainly creates maps of science.

Journals related to Scientometrics, Informetrics and Bibliometrics

Books on Scientometrics

  1. Anderes, A. (2009). Measuring Academic Research: How to undertake a bibliometric study. Oxford: Chandos.

  2. Ball, R. (editor) (2021). Bibliometrics handbook. De Gruyter.

  3. Biagioli, M., & Lippman, A. (editors) (2020). Gaming the Metrics: Misconduct and Manipulation in Academic Research, Cambridge: MIT Press.

  4. Borgman, C.L. (1990). Scholarly communication and bibliometrics: Sage Publications.

  5. Borner, K. (2010). Atlas of Science: Visualizing What We Know: MIT Press.

  6. Braam, R.R. (1991). Mapping of science: foci of intellectual interest in scientific literature: DSWO Press, University of Leiden.

  7. Braun, T. (Ed.). (2006). Evaluations of Individual Scientists and Research Institutions. Part I. Scientometrics Guidebooks Series: Akademiai Kiado Zrt.

  8. Braun, T. (Ed.). (2006). Evaluations of Individual Scientists and Research Institutions. Part II. Scientometrics Guidebooks Series: Akademiai Kiado Zrt.

  9. Braun, T. (2007). The Impact Factor of Scientific and Scholarly Journals: Its Use and Misuse in Research Evaluation: Akadémiai Kiadó.

  10. Braun, T. (2008). The Hirsch-index for evaluating science and scientists. Its uses and misuses: Akadémiai Kiadó.

  11. Braun, T., Bujdosó, E., & Schubert, A. (1987). Literature of analytical chemistry: a scientometric evaluation: CRC Press.

  12. Braun, T., Glänzel, W., & Schubert, A. (1985). Scientometric indicators: a 32 country comparative evaluation of publishing performance and citation impact: World Scientific.

  13. Cantú-Ortiz, F. J. (2017). Research Analytics: Boosting University Productivity and Competitiveness through Scientometrics. Auerbach Publications.

  14. Chiesa, V., & Frattini, F. (2009). Evaluation and performance measurement of research and development: techniques and perspectives for multi-level analysis: Edward Elgar.

  15. Cronin, B. (1984). The citation process: the role and significance of citations in scientific communication: Taylor Graham.

  16. Cronin, B., & Atkins, H.B. (Eds.). (2000). The Web of Knowledge: A Festschrift in Honor of Eugene Garfield: Information Today Inc.

  17. Cronin, B. & Sugimoto, C. (Eds). (2014) Beyond Bibliometrics : Harnessing Multidimensional Indicators of Scholarly Impact. Massaschussets, MIT Press.

  18. Cronin, B. & Sugimoto, C.R., (Eds.) (2015). Scholarly metrics under the microscope. Medford, NJ: Information Today.

  19. De Bellis, N. (2009). Bibliometrics and Citation Analysis: From the Science Citation Index to Cybermetrics. Lanham: Scarecrow Press.

  20. Devarajan, G. (1997). Bibliometric studies: Ess Ess Publications.

  21. Diodato, V.P. (1994). Dictionary of bibliometrics: Haworth Press.

  22. Egghe, L. (2005). Power Laws in the Information Production Process: Lotkaian Informetrics: Emerald Group Publishing Limited.

  23. Egghe, L., & Rousseau, R. (1990). Introduction to informetrics: quantitative methods in library, documentation and information science: Elsevier Science Publishers.

  24. Eom, S. (2009). Author cocitation Analysis: Quantitative Methods for Mapping the Intellectual Structure of an Academic Discipline. Hershey: Information Science Reference.

  25. érdi, P. (2019). Ranking - The Unwritten Rules of the Social Game We All Play. New York: Oxford University Press.

  26. Evered, D., & Harnett, S. (1989). The Evaluation of Scientific Research: Wiley.

  27. Gingras, Y. (2016). Bibliometrics and Research Evaluation: Uses and Abuses, Cambridge, MA: MIT Press.

  28. Geisler, E. (2000). The metrics of science and technology: Quorum Books.

  29. Harzing, A.W. (2010). The Publish Or Perish Book: Your Guide to Effective and Responsible Citation Analysis: Tarma Software Research.

  30. Hasan, N. (2010). Mapping the dynamics of world agricultural research output: A scientometric study LAP LAMBERT Academic Publishing.

  31. Hjerppe, R. (1980). An outline of bibliometrics and citation analysis, Royal Institute of Technology Library.

  32. Holden, G., Rosenberg, G., & Barker, K. (2006). Bibliometrics in social work: Haworth Social Work Practice Press.

  33. International Survey of Research University Faculty: Use of Bibliometric Ratings, Identifiers & Indicators (2017). Primary Resource Group.

  34. Leydesdorff, L. (2001). The Challenge of Scientometrics: The Development, Measurement, and Self-Organization of Scientific Communications: Universal-Publishers.

  35. Moed, H.F. (2017). Applied evaluative informetrics, Springer.

  36. Moed, H.F. (1989). The use of bibliometric indicators for the assessment of research performance in the natural and life sciences: aspects of data collection, reliability, validity, and applicability: DSWO Press.

  37. Moed, H.F., Glänzel, W., & Schmoch, U. (2004). Handbook of quantitative science and technology research: the use of publication and patent statistics in studies of S & T systems: Kluwer Academic Publishers.

  38. Nicholas, D., & Ritchie, M. (1978). Literature and bibliometrics: C. Bingley.

  39. Okubo, Y. (1997). Bibliometric indicators and analysis of research systems: methods and examples: OECD.

  40. Pǎces, V., Pivec, L., & Teich, A.H. (1999). Science evaluation and its management: IOS Press.

  41. Raan, A.F.J. (1988). Handbook of quantitative studies of science and technology: North-Holland.

  42. Raan, A.F.J., Nederhof, A.J., & Moed, H.F. (1989). Science and technology indicators: their use in science policy and their role in science studies: select proceedings of the First International Workshop on Science and Technology Indicators, Leiden, The Netherlands, 14-16 November 1988: DSWO Press, University of Leiden.

  43. Rana, M.S. (2010). Scientometric Study of Wild Mammal Research in India: Authorship, Distribution and Research Trend: LAP Lambert Academic Publishing

  44. Rao, I.K.R. (2010). Growth of Literature and Measures of Scientific Productivity: Scientometric Models, Ess Ess Publications.

  45. Roemer, R. C. & Borchardt, R. (2015). Meaningful Metrics: A 21st Century Librarian's Guide to Bibliometrics, Altmetrics, and Research Impact, ACRL.

  46. Rousseau, R., Egghe, L., & Guns, R. (2018). Becoming metric-wise: A bibliometric guide for researchers, Chandos Publishing.

  47. Santo, A.E. (1978). A measure of the dimensions of interdisciplinarity of two applied sciences: a scientometric model: University of Wisconsin.

  48. Sinha, S. C. & Zhiman, A. K. (2001). Citation Analysis of Research Field and Information Technology Development. ESS ESS Publications.

  49. Sooryamoorthy, R. (2020). Scientometrics for the Humanities and Social Sciences, Routledge.

  50. Sugimoto, C.R., & Larivière, V. (2017). Measuring research: what everyone needs to know. Oxford: Oxford University Press.

  51. Tattersall, A. (editor) (2015). Altmetrics: A practical guide for librarians, researchers and academics, Facet Publishing.

  52. Thelwall, M. (2016). Web indicators for research evaluation: A practical guide. Synthesis Lectures on Information Concepts, Retrieval, and Services. San Rafael, CA: Morgan &  Claypool Publishers.

  53. Tijssen, R.J.W. (1992). Cartography of science: scientometric mapping with multidimensional scaling methods: DSWO Press, Leiden University.

  54. Tijssen, R.J.W., Leeuwen, T.N., & Raan, A.F.J. (2002). Mapping the scientific performance of German medical research: an international comparative bibliometric study: Schattauer.

  55. Todeschini, R., & Baccini, A. (2016). Handbook of bibliometric indicators: quantitative tools for studying and evaluating research. Wiley-VCH..

  56. Vinkler, P. (2010). The Evaluation of Research by Scientometric Indicators. Oxford: Chandos.

  57. Wang, D., Barabási, A. (2021). The Science of science. Cambridge University Press.

  58. Whitley, R., & Gläser, J. (2007). The changing governance of the sciences: the advent of research evaluation systems: Springer.

  59. Zhao, D. & Strotmann, A.(2015). Analysis and Visualization of Citation Networks, Morgan & Claypool Publishers.



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