Visualising the Uncertain in Heritage Collections: Understanding, Exploring and Representing Uncertainty in the First World War British Unit War Diaries


  • Johannes Liem Danube University Krems, Austria
  • Aidan Slingsby City, University of London, UK
  • Eirini Goudarouli The National Archives, UK
  • Mark Bell The National Archives, UK.
  • Cagatay Turkay University of Warwick, UK
  • Charles Perin University of Victoria, Canada
  • Jo Wood City, University of London, UK


Uncertainty, representation, visualisation, cultural heritage, collections, data.


This paper argues that cultural heritage data is inherently ambiguous and may involve different types and levels of uncertainty. Using a variety of examples based on The National Archives (UK)’s Unit War Diaries collection unveiling stories of the British Army and its units on the Western Front in the First World War, we discuss the ways in which visualisation can help us approach heritage collections as data, enabling their visual representation in a constructive and informed way. It also aims to open up the discussion about the theoretical and methodological challenges that uncertainty, which is often hidden, can bring to the understanding of ambiguous heritage data.In brief, we discuss ways in which uncertainty appears in cultural heritage collections, either as something innate in the collections or resulting from the data extraction and narrative construction process. We identify three main types of uncertainty: inaccuracy, incompleteness and ambiguity, with the latter then subdivided into inconsistency, imprecision and non-specificity. Distinguishing, considering and quantifying these different types of uncertainty can help understand the level of confidence that we can have in narratives, source data and the extraction process. This can then enhance the discoverability of cultural heritage collections that involve high levels of uncertainty.In this way, we suggest that cultural heritage organisations should strategically focus on improving the understandability and discoverability of their digital collections by exposing and embracing uncertainty in cultural heritage collections and by innovating in its visual presentation to researchers and the public.


Bach, B., Riche, N.H., Carpendale, S. and Pfister, H. (2017) ‘The Emerging Genre of Data Comics.’ IEEE Computer Graphics and Applications, 37(3), pp. 6-13.

Bertin, J. (1983) Semiology of Graphics. University of Wisconsin Press.

Boukhelifa, N., Bezerianos, A., Isenberg, T. and Fekete, J.-D. (2012) ‘Evaluating Sketchiness as a Visual Variable for the Depiction of Qualitative Uncertainty.’ IEEE Transactions on Visualization and Computer Graphics, 18 (12), pp. 2769-2778.

Bushell, S. (2012) ‘The Slipperiness of Literary Maps: Critical Cartography and Literary Cartography.’ Cartographica: The International Journal for Geographic Information and Geovisualization, 47, pp 149-160.

Bushell, S., Butler, J.O., Hay, D. and Hutcheon, R. (2022) ‘Digital Literary Mapping: I. Visualizing and Reading Graph Topologies as Maps for Literature.’ Cartographica: The International Journal for Geographic Information and Geovisualization, 57(1), pp. 11-36.

Bushell, S., Butler, J., Hay, D., Hutcheon, R. and Butterworth, A. (2021) ‘Chronotopic Cartography: Mapping Literary Time-Space.’ Journal of Victorian Culture, 26(2), pp. 310-325.

Collins, C., Penn, G. and Carpendale, S. (2009) ‘Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations.’ IEEE Transactions on Visualization and Computer Graphics, 15(6), pp. 1009-1016.

Cooper, D., Donaldson, C. and Murrieta-Flores, P. (eds) (2016) Literary Mapping in the Digital Age. London: Routledge.

Dai Prà, E. and Gabellieri, N. (2021) ‘Mapping the Grand Tour Travel Writings: a GIS-Based Inventorying and Spatial Analysis for Digital Humanities in Trentino-Alto Adige, Italy (XVI-XIX c.).’ Literary Geographies, 7(2), pp. 251-274.

Goudarouli, E., Sexton, A. and Sheridan, J. (2019) ‘The Challenge of the Digital and the Future Archive: Through the Lens of The National Archives UK.’ Philosophy & Technology, 32(1), pp. 173-183.

Grayson, R.S. (2016) ‘A Life in the Trenches? The Use of Operation War Diary and Crowdsourcing Methods to Provide an Understanding of the British Army’s Day-to-Day Life on the Western Front.’ British Journal for Military History, 2(2), pp 160-185.

Hones, S. (2022) Literary Geography. Routledge.

Klir, G. and Wierman, M. (1999) Uncertainty-Based Information: Elements of Generalized Information Theory. Studies in Fuzziness and Soft Computing. 2nd edition. Physica-Verlag Heidelberg.

MacEachren, A.M., Roth, R.E., O’Brien, J., Li, B., Swingley, D. and Gahegan, M. (2012) ‘Visual Semiotics Uncertainty Visualization: An Empirical Study.’ IEEE Transactions on Visualization and Computer Graphics, 18(12), pp. 2496-2505.

Mayr, E. and Windhager, F. (2018). ‘Once upon a Spacetime: Visual Storytelling in Cognitive and Geotemporal Information Spaces.’ ISPRS International Journal of Geo-Information, 7(3), 96.

Murrieta-Flores, P., Donaldson, C. and Gregory, I. (2017) ‘GIS and literary history: Advancing digital humanities research through the spatial analysis of historical travel writing and topographical literature.’ Digital Humanities Quarterly, 11(1).

Olston, C. and Mackinlay, J.D. (2002) ‘Visualizing data with bounded uncertainty.’ In IEEE Symposium on Information Visualization, 2002. INFOVIS 2002, October 2002. pp. 37-40.

Padilla, L., Kay, M. and Hullman, J. (2021) ‘Uncertainty Visualization.’ In Wiley StatsRef: Statistics Reference Online. American Cancer Society. pp. 1-18.

Perin, C., Vuillemot, R., Stolper, C.D., Stasko, J.T., Wood, J. and Carpendale, S. (2018) ‘State of the Art of Sports Data Visualization.’ Computer Graphics Forum, 37(3), pp. 663-686.

Potter, K., Rosen, P. and Johnson, C.R. (2012) ‘From Quantification to Visualization: A Taxonomy of Uncertainty Visualization Approaches.’ In Dienstfrey, A. M. and Boisvert, R. F. (eds) Uncertainty Quantification in Scientific Computing. Berlin, Heidelberg: Springer. pp. 226-249.

Reuschel, A.K. and Hurni, L. (2011) ‘Mapping Literature: Visualisation of Spatial Uncertainty in Fiction.’ The Cartographic Journal, 48(4), pp 293-308.

Shneiderman, B. (1996) ‘The eyes have it: a task by data type taxonomy for information visualizations.’ In Proceedings 1996 IEEE Symposium on Visual Languages. September 1996, pp. 336-343.

Smithson, M. (1989) Ignorance and Uncertainty: Emerging Paradigms. New York: Springer-Verlag.

Stell, J.G. (2019) ‘Qualitative Spatial Representation for the Humanities.’ International Journal of Humanities and Arts Computing, 13(1-2), pp. 2-27.

Taylor, J.E., Donaldson, C.E., and Gregory, I. N., and Butler, J. O. (2018) ‘Mapping Digitally, Mapping Deep: Exploring Digital Literary Geographies.’ Literary Geographies, 4(1), pp. 10-19.

Thacker, A. (2005) ‘The idea of a critical literary geography.’ New Formations, 57, pp. 56-73.

Thomson, J., Hetzler, E., MacEachren, A., Gahegan, M. and Pavel, M. (2005) ‘A typology for visualizing uncertainty.’ Visualization and Data Analysis 2005. International Society for Optics and Photonics, 5669, pp. 146-157.

Wood, J., Isenberg, P., Isenberg, T., Dykes, J., Boukhelifa, N. and Slingsby, A. (2012) ‘Sketchy Rendering for Information Visualization.’ IEEE Transactions on Visualization and Computer Graphics, 18(12), pp. 2749-2758.

Yuill, R.S. (1971) ‘The Standard Deviational Ellipse; An Updated Tool for Spatial Description.’ Geografiska Annaler: Series B, Human Geography, 53(1), pp. 28-39.






Special Issue Articles