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Bibliometrische visualisaties voor het bijhouden van wetenschappelijke literatuur

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Bibliometrische visualisaties voor het bijhouden van wetenschappelijke literatuur

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Het is van essentieel belang dat onderzoekers een actueel overzicht hebben van de literatuur in hun onderzoeksveld. Gegeven het enorme aantal publicaties dat wekelijks in wetenschappelijke tijdschriften verschijnt kan het bijhouden van alle relevante literatuur en het verkrijgen van een goed overzicht van een onderzoeksveld echter een uitdaging zijn en veel tijd kosten. Bibliometrische visualisaties ondersteunen deze taak. Dit soort visualisaties bieden een intuïtief overzicht van de relevante literatuur in een onderzoeksveld. Zo kunnen onderzoekers een beter inzicht krijgen in de structuur en de ontwikkeling van een veld en een indruk krijgen van de belangrijkste bijdragen in het veld.

Het is van essentieel belang dat onderzoekers een actueel overzicht hebben van de literatuur in hun onderzoeksveld. Gegeven het enorme aantal publicaties dat wekelijks in wetenschappelijke tijdschriften verschijnt kan het bijhouden van alle relevante literatuur en het verkrijgen van een goed overzicht van een onderzoeksveld echter een uitdaging zijn en veel tijd kosten. Bibliometrische visualisaties ondersteunen deze taak. Dit soort visualisaties bieden een intuïtief overzicht van de relevante literatuur in een onderzoeksveld. Zo kunnen onderzoekers een beter inzicht krijgen in de structuur en de ontwikkeling van een veld en een indruk krijgen van de belangrijkste bijdragen in het veld.

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Bibliometrische visualisaties voor het bijhouden van wetenschappelijke literatuur

  1. 1. Bibliometrische visualisaties voor het bijhouden van wetenschappelijke literatuur Nees Jan van Eck Centre for Science and Technology Studies (CWTS), Leiden University VOGIN-IP-lezing 21 oktober 2021
  2. 2. About myself • Master in computer science • PhD thesis on bibliometric mapping of science • Senior researcher at CWTS – Bibliometric network analysis and visualization – Bibliometric data sources – Bibliometric indicators • Head of ICT 1
  3. 3. Centre for Science and Technology Studies (CWTS) • Research center at Leiden University • Science and technology studies, with a considerable emphasis on scientometrics • About 50 staff members • Our mission: Making the science system better! • Full access to large bibliographic database (Web of Science, Scopus, Dimensions, PubMed, PATSTAT, etc.) 2
  4. 4. Centre for Science and Technology Studies (CWTS) • Basic research: – Quantitative science studies – Science and evaluation studies – Science, technology and innovation studies • Commissioned research: – Bibliometric studies for universities, funding organizations, governments, scientific publishers, etc. – Mostly done using the in-house databases of CWTS 3
  5. 5. Program • Introduction • Hands-on assignments – Data collection – VOSviewer: • Co-authorship maps • Citation-based maps • Term maps 4
  6. 6. Introduction 5
  7. 7. Explosive growth of scientific literature 6 “A new scientific paper is published every 30 seconds and there are 10,000 updates to PubMed every day” “It is impossible for humans alone to process all of the complex information potentially available to them for the advancement of scientific research” James Chandler, November 2016, BenevolentAI
  8. 8. Bibliographic data sources 7
  9. 9. Bibliographic data sources 8 Web of Science Scopus Dimensions Journals 20,000 25,000 50,000 Publications 60 million 50 million 110 million Citations 1.4 billion 1.5 billion 1.2 billion
  10. 10. Bibliometric networks 9 WoS Scopus Dimensions Lens MAG Semantic Scholar PubMed Europe PMC Crossref Citation network of pubs / journals / authors / orgs / countries Co-authorship network of authors / orgs / countries Co-citation network of pubs / journals / authors / orgs / countries Co-occurrence network of keywords / terms Bibliographic coupling network of pubs / journals / authors Bibliographic data source
  11. 11. VOSviewer 10
  12. 12. VOSviewer • Focus on visualization of scientometric networks • Support for large number of data sources • Text mining functionality • Advanced visualization features • Relatively easy to use • Limited analysis options • Developed at CWTS 11
  13. 13. Users of VOSviewer • Researchers • Research institutions • Research funders • Scientific publishers • Industry 12
  14. 14. 13
  15. 15. 14
  16. 16. Text mining 15 JOI Scientometrics JASIST
  17. 17. Development of VOSviewer 16
  18. 18. Types of networks supported by each data source 17 Co-authorship Co-occurrence Citation Bibliographic coupling Co-citation Web of Science      Scopus      Dimensions      PubMed      Crossref      Europe PMC      Lens      Microsoft Academic      Semantic Scholar      OCC / COCI      Wikidata     
  19. 19. Data access 18 Download
  20. 20. Interactive querying 19
  21. 21. 20
  22. 22. 21
  23. 23. 22
  24. 24. Data collection 23
  25. 25. Data access 24 Download
  26. 26. Downloading Web of Science data Pay attention to the following: • Use the Web of Science Core Collection database • Use the Full Record and Cited References option • Use a suitable file format: – VOSviewer supports both the plain text and the tab-delimited format – Tab-delimited files can be easily processed using spreadsheet software • We use the tab-delimited format 25
  27. 27. 26 Downloading Web of Science data
  28. 28. Downloading Web of Science data 27
  29. 29. Downloading Web of Science data 28
  30. 30. Downloading Scopus data • Use the CSV export option, not the Download option! 29
  31. 31. Downloading Scopus data 30
  32. 32. Downloading Scopus data 31
  33. 33. Downloading Scopus data 32
  34. 34. Downloading Dimensions data • Make sure to create a user account! • Extract the CSV file from the downloaded ZIP file 33
  35. 35. Downloading Dimensions data 34
  36. 36. Downloading Dimensions data 35
  37. 37. Downloading Dimensions data 36
  38. 38. Downloading Lens data • Create a user account if you want to export more than 1,000 search results 37
  39. 39. Downloading Lens data 38
  40. 40. Downloading Lens data 39
  41. 41. Demonstration + Data collection assignment 40
  42. 42. Co-authorship maps 41
  43. 43. Co-authorship map of researchers 42
  44. 44. Co-authorship map of organizations 43
  45. 45. Co-authorship map of ASMS members 44
  46. 46. Co-authorship map of research organizations 45
  47. 47. Demonstration + Co-authorship map assignments 46
  48. 48. Citation-based maps 47
  49. 49. Determining relatedness based on citation data • Determining relatedness of publications, journals, authors, etc. based on citation data: – Direct citation relations – Bibliographic coupling relations – Co-citation relations • VOSviewer supports all three types of citation-based relations • Another tool, CitNetExplorer, is focused entirely on direct citation relations 48
  50. 50. Direct citation relations 49 P1 P2 P1 and P2 are related because P1 has cited P2 (i.e., P2 appears in the reference list of P1)
  51. 51. Bibliographic coupling relations 50 P2 P3 P4 P1 Citing papers Cited papers P1 and P2 are related because they have cited P3, P4, and P5 in their reference list P5
  52. 52. Co-citation relations 51 P2 P3 P1 Citing papers Cited papers P1 and P2 are related because they are co-cited in the reference lists of P3, P4, and P5 P4 P5
  53. 53. Direct citation network of publications 52 P1 P2 P3 P4 P5 P6 Citation network (directed) Citation network (undirected) P1 P2 P3 P4 P5 P6
  54. 54. Bibliographic coupling network of publications 53 P1 P2 P3 P4 P5 P6 P1 P2 P3 P4 P5 P6 2 1 1 1 Citation network Bibliographic coupling network
  55. 55. Co-citation network of publications 54 P1 P2 P3 P4 P5 P6 P1 P2 P3 P4 P5 P6 2 1 1 1 Citation network Co-citation network
  56. 56. Comparison of different types of citation-based relations • Direct citation relations: – Focus on recent publications – Stable (direct citation relations won’t change in the future) – Some publications may have no direct citation relations • Bibliographic coupling relations: – Focus on recent publications – Stable (bib. coupling relations won’t change in the future) – Publications almost always have bib. coupling relations • Co-citation relations: – Focus on older publications – Unstable (co-citation relations may change in the future) – Some publications may have no co-citation relations 55
  57. 57. Journal citation map 56
  58. 58. Journal co-citation map
  59. 59. Interpretation of a citation-based map • Size: – The larger an item (e.g., author or journal), the larger the number of publications of the item • Distance: – In general, the smaller the distance between two items, the higher the relatedness of the items, as measured by citations, bibliographic coupling or co-citations – The horizontal and vertical axes have no special meaning; maps can be freely rotated and flipped • Colors: – Colors indicate clusters of strongly related items 58
  60. 60. Citation-based maps supported by VOSviewer • Citation and bibliographic coupling maps: – Publications – Journals – Authors – Organizations – Countries • Co-citation maps: – Cited references – Cited journals – Cited authors (first author only in the case of Web of Science) 59
  61. 61. Demonstration + Citation-based maps assignments 60
  62. 62. Term maps 61
  63. 63. Term co-occurrence network
  64. 64. Interpretation of a term map • Size: – The larger a term, the higher the frequency of occurrence of the term • Distance: – In general, the smaller the distance between two terms, the higher the relatedness of the terms, as measured by co-occurrences – The horizontal and vertical axes have no special meaning; maps can be freely rotated and flipped • Colors: – Colors indicate clusters of closely related terms 63
  65. 65. Term co-occurrence network: Journal overlays
  66. 66. Term co-occurrence network: Time trend overlay
  67. 67. Term co-occurrence network: Citation impact overlay
  68. 68. Term map of Dutch biomedical research 67
  69. 69. Term map of Dutch biomedical research: Activity overlay LUMC 68
  70. 70. Term map of Dutch biomedical research: Activity overlay VUmc 69
  71. 71. Term map of Alzheimer research: Overlay based on publication year 70
  72. 72. Term map of clinical neurology research: Citation overlay 71
  73. 73. Demonstration + term map assignments 72
  74. 74. Wrap-up 73
  75. 75. Aim of bibliometric maps • To provide an overview of the structure of the scientific literature in a certain domain or on a certain topic • Applications: – To identify the main research areas within a scientific field – To get insight into the size of the different areas – To see how the areas relate to each other • Bibliometric maps are especially useful when one has to deal with a relatively large body of literature 74
  76. 76. Bibliometric mapping process 75 research question bibliographicd ata bibliometric map results data collection data processing analysis interpretation revision
  77. 77. Use of scientometric visualizations • Visualizations can be used to make complex information more accessible • Visualizations need to be used in combination with expert knowledge: – Confirm expert knowledge – Challenge expert knowledge – Draw expert’s attention to interesting information • Be aware of information loss and methodological sensitivity • Visualizations can also be used pragmatically to attract attention and to ‘sell a message’ 76
  78. 78. Do it yourself! 77 www.vosviewer.com www.citnetexplorer.nl
  79. 79. Course: Visualizing Science Using VOSviewer • January 25-28, 2022 • 4 half-day online sessions • Participants are introduced into the main techniques for visualizing science • Special attention is paid to applications in a research evaluation and research management context • The course has an interactive format and the small group size allows participants to practice extensively with the VOSviewer software • www.cwts.nl 78
  80. 80. Thank you for your attention! 79
  81. 81. Further reading 80
  82. 82. Further reading 81

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