Picturing Science: Design Patterns in Graphical Abstracts

  • Jessica HullmanEmail author
  • Benjamin Bach
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10871)


A graphical abstract (GA) provides a concise visual summary of a scientific contribution. GAs are increasingly required by journals to help make scientific publications more accessible to readers. We characterize the design space of GAs through a qualitative analysis of 54 GAs from a range of disciplines, and descriptions of GA design principles from scientific publishers. We present a set of design dimensions, visual structures, and design templates that describe how GAs communicate via pictorial and symbolic elements. By reflecting on how GAs employ visual metaphors, representational genres, and text relative to prior characterizations of how diagrams communicate, our work sheds light on how and why GAs may be distinct. We outline steps for future work at the intersection of HCI, AI, and scientific communication aimed at the creation of GAs.


Graphical abstract Diagram Information visualization 


  1. 1.
    Arnheim, R.: Art and Visual Perception: A Psychology of the Creative Eye. University of California Press, Berkeley (1954)Google Scholar
  2. 2.
    Arnheim, R.: Visual Thinking. University of California Press, Berkeley (1969)Google Scholar
  3. 3.
    Bach, B., Wang, Z., Farinella, M., Murray-Rust, D., Henry Riche, N.: Design patterns for data comics. In: Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI) (2018, to appear)Google Scholar
  4. 4.
    Bauer, D., Fastrez, P., Hollan, J.: Spatial tools for managing personal information collections. In: Proceedings of the 38th Annual Hawaii International Conference on System Sciences, p. 104b. IEEE (2005)Google Scholar
  5. 5.
  6. 6.
    American journal Experts: How to make a good graphical abstract (2016).
  7. 7.
    Gentner, D., Loewenstein, J., Thompson, L.: Learning and transfer: a general role for analogical encoding. J. Educ. Psychol. 95(2), 393 (2003)CrossRefGoogle Scholar
  8. 8.
    Hegarty, M., Just, M.A.: Constructing mental models of machines from text and diagrams. J. Mem. Lang. 32, 717–742 (1993)CrossRefGoogle Scholar
  9. 9.
    Heiser, J., Tversky, B.: Diagrams and descriptions in acquiring complex systems. In: Proceedings of the Meetings of the Cognitive Science Society (2002)Google Scholar
  10. 10.
    Heiser, J., Tversky, B.: Arrows in comprehending and producing mechanical diagrams. Cognit. Sci. 30(3), 581–592 (2006)CrossRefGoogle Scholar
  11. 11.
    Johnson, M.: The Body in the Mind: The Bodily Basis oOf Meaning, Imagination, and Reason. University of Chicago Press, Chicago (2013)Google Scholar
  12. 12.
    Kadoury, S., Labelle, H., Paragios, N.: Automatic inference of articulated spine models in ct images using high-order Markov random fields. Med. Image Anal. 15(4), 426–437 (2011)CrossRefGoogle Scholar
  13. 13.
    Krauss, R.E.: The Originality of the Avant-Garde and Other Modernist Myths. MIT Press, Cambridge (1986)Google Scholar
  14. 14.
    Lakoff, G.: Women, Fire, and Dangerous Things: What Categories Reveal About the Mind. Cambridge University Press, Cambridge (1990)Google Scholar
  15. 15.
    Larsen, P.O., Von Ins, M.: The rate of growth in scientific publication and the decline in coverage provided by science citation index. Scientometrics 84(3), 575–603 (2010)CrossRefGoogle Scholar
  16. 16.
    Lee, B., Srivastava, S., Kumar, R., Brafman, R., Klemmer, S.R.: Designing with interactive example galleries. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 2257–2266. ACM (2010)Google Scholar
  17. 17.
    Lofland, J., Lofland, L.H.: Analyzing Social Settings. Wadsworth Publishing Company Belmont, Belmont (2006)Google Scholar
  18. 18.
    Margolis, E., Pauwels, L.: The Sage Handbook of Visual Research Methods. Sage, Thousand Oaks (2011)CrossRefGoogle Scholar
  19. 19.
    Mayer, R.E.: Multimedia learning. Psychol. Learn. Motiv. 41, 85–139 (2002)CrossRefGoogle Scholar
  20. 20.
    Moriarty, S.: Visual semiotics theory. In: Handbook of Visual Communication: Theory, Methods, and Media, vol. 8, pp. 227–241 (2005)Google Scholar
  21. 21.
    O’Donovan, P., Agarwala, A., Hertzmann, A.: DesignScape: Design with interactive layout suggestions. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 1221–1224. ACM (2015)Google Scholar
  22. 22.
    O’Donovan, P., Lībeks, J., Agarwala, A., Hertzmann, A.: Exploratory font selection using crowdsourced attributes. ACM Trans. Graph. (TOG) 33(4), 92 (2014)Google Scholar
  23. 23.
    O’Donovan, P., Agarwala, A., Hertzmann, A.: Learning layouts for single-pagegraphic designs. IEEE Trans. Vis. Comput. Graph. 20(8), 1200–1213 (2014)CrossRefGoogle Scholar
  24. 24.
    Pferschy-Wenzig, E.M., Pferschy, U., Wang, D., Mocan, A., Atanasov, A.G.: Does a graphical abstract bring more visibility to your paper? (2016)Google Scholar
  25. 25.
    Cell Press: Cell press graphical abstract guidelines (2016).
  26. 26.
    Romans, B.: Are graphical abstracts a good idea? (2011).
  27. 27.
    Shahaf, D., Guestrin, C., Horvitz, E.: Metro maps of science. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1122–1130. ACM (2012)Google Scholar
  28. 28.
    Strobelt, H., Oelke, D., Rohrdantz, C., Stoffel, A., Keim, D.A., Deussen, O.: Document cards: a top trumps visualization for documents. IEEE Trans. Vis. Comput. Graph. 15(6), 1145–1152 (2009)CrossRefGoogle Scholar
  29. 29.
    Adobe Systems: Adobe Spark Post (2017).
  30. 30.
    Tufte, E.R.: Envisioning information. Optom. Vis. Sci. 68(4), 322–324 (1991)CrossRefGoogle Scholar
  31. 31.
    Tversky, B.: Some ways that maps and diagrams communicate. In: Freksa, C., Habel, C., Brauer, W., Wender, K.F. (eds.) Spatial Cognition II. LNCS (LNAI), vol. 1849, pp. 72–79. Springer, Heidelberg (2000). Scholar
  32. 32.
    Tversky, B.: Spatial schemas in depictions. In: Spatial Schemas and Abstract Thought, pp. 79–111 (2001)Google Scholar
  33. 33.
    Tversky, B.: Visuospatial reasoning. In: The Cambridge Handbook of Thinking and Reasoning, pp. 209–240 (2005)Google Scholar
  34. 34.
    Tversky, B.: Visualizing thought. Topics Cognit. Sci. 3(3), 499–535 (2011)CrossRefGoogle Scholar
  35. 35.
    Tversky, B., Kugelmass, S., Winter, A.: Cross-cultural and developmental trends in graphic productions. Cogn. Psychol. 23(4), 515–557 (1991)CrossRefGoogle Scholar
  36. 36.
    Tversky, B., Zacks, J., Lee, P., Heiser, J.: Lines, blobs, crosses and arrows: diagrammatic communication with schematic figures. In: Anderson, M., Cheng, P., Haarslev, V. (eds.) Diagrams 2000. LNCS (LNAI), vol. 1889, pp. 221–230. Springer, Heidelberg (2000). Scholar
  37. 37.
    wikiHow Community: How to make a graphical abstract for scientific publication (2016).
  38. 38.
    Winn, B.: Charts, graphs, and diagrams in educational materials. Psychol. Illus. 1, 152–198 (1987)CrossRefGoogle Scholar
  39. 39.
    Winn, W.D.: A theoretical framework for research on learning from graphics. Int. J. Educ. Res. 14(6), 553–564 (1990)CrossRefGoogle Scholar
  40. 40. Word press themes directory (2017).
  41. 41.
    IEEE Xplore: Graphical abstract description and specifications (2015).
  42. 42.
    Yoon, J., Chung, E.: An investigation on graphical abstracts use in scholarly articles. Int. J. Inf. Manage. 37(1), 1371–1379 (2017)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of WashingtonSeattleUSA
  2. 2.University of EdinburghEdinburghUK

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