Return to the MLA Commons
Concepts, Models, and Experiments


Stéfan Sinclair

1 Leave a comment on paragraph 1 0 McGill University | stefansinclair.name

Geoffrey Rockwell

2 Leave a comment on paragraph 2 0 University of Alberta | geoffreyrockwell.com

3 Leave a comment on paragraph 3 0 The official reviewing period for this keyword has ended, and commenting is closed. You may also wish to read the description of the anthology, guidelines on how to comment, and the list of keywords.


4 Leave a comment on paragraph 4 0 Although for many humanities disciplines (literature, history, philosophy, etc.) text tends to be the dominant currency for apprehending and expressing knowledge, data visualizations have a long history and much to offer, particularly when the amount of text exceeds what can be reasonably read and represented by more traditional means. As is argued in two of the artifacts below (“Information Visualization for Humanities Scholars” and “Humanities Approaches to Graphical Display”), interactive visualizations can be a valuable way of interpreting evidence and sharing those interpretations. Further, sharing interactive visualizations allows other to explore evidence and come to their own conclusions.

5 Leave a comment on paragraph 5 0 Given the proliferation of visualizations in online media, especially for exploring big data, it has become important to teach students to treat them critically. One way to do that is to have students fiddle with different types of visualization and reflect on the graphical features and how they might reflect evidence or not. Having students then create their own visualizations is an effective way of encouraging them to leverage their humanities training in the interpretation of a variety of contemporary issues, from the environment to various social inequalities. Visualizations are an eminently shareable form of communication and students can be empowered to communicate through visualizations, sharing results via social media.

6 Leave a comment on paragraph 6 0 In a pedagogical context we tend to approach visualization with four related sets of questions:

  1. 7 Leave a comment on paragraph 7 0
  2. Presence: Where do we see visualizations? What are they designed to communicate? Who is designing them and for what audience?
  3. Literacy: How can we read visualizations? How can we be better informed and more critical consumers of visualizations? What are visualizations showing us and what are they hiding? What features are based on the evidence and what come from the designer? What are some of the common pitfalls of visualizations?
  4. Rhetoric: How can we communicate effectively with visualizations? Can we imagine new ways of using visualization in humanistic interpretation?
  5. Visual Traditions: What is the history of different genres of visualization? Where do types of visualization like the bar chart come from? How do traditions of interpretation influence how visualizations are read?

8 Leave a comment on paragraph 8 0 The first set of questions is designed to make students aware of the variety of visualizations they encounter in everyday life from HUDs (Heads Up Displays) in a videogame to business graphics on news sites. There are lots of web sites with examples (see Related Sites for galleries), but also books with reproductions of interesting visualizations like Tufte’s The Visual Display of Quantitative Information (1983).

9 Leave a comment on paragraph 9 0 The second and third sets of questions, how we read (literacy) and how we express (rhetoric) can be taught symbiotically. We can better understand visualizations when we’ve had the experience of creating them and in modelling visualizations we can better understand what other designers were trying to do. That’s why we tend to design our teaching on data visualization in a cross-over pattern: we emphasize theoretical work and exploration of existing data visualizations early on while ramping-up creative practice as the term progresses.

Cross-over of theory and practice during the term

Cross-over of theory and practice during the term

11 Leave a comment on paragraph 11 0 The last set of questions have to do with thinking about visualizations as humanists and asking critical questions about how they can be interpreted. Students should be encouraged to think about visualizations not as objective representations of data, but as ways of making knowledge. Thiking about visualization as a way of interpreting (in the dual sense of interpreting evidence and also creating interpretations) leads to thinking about traditions of visual knowledge production. Students should be encouraged to ask about the conventions of types of visualizations like a social network graphs and how they have been adapted. When labeled nodes are connected with lines in a network graph, what are the conventions for reading into the graph? When the network is a geneaology of emperors how do we know how to read the generations? Johanna Drucker’s Graphesis is a good introduction to the critical understanding of visual knowledge production. Depending on how much time you have there is an essay form of Graphesis from 2010 and a later more developed book from 2014.

Heuristics for Teaching Visualization

12 Leave a comment on paragraph 12 0 Graphical Features: An important part of learning to read and create visualizations is to understand what graphical features like colour, orientation, or location mean. For example, in a word cloud, does the colour of words mean something about the text or is it an aesthetic selection of the programmer? We often start workshops by showing simple visualizations and asking students to identify the features used and then guess at how the visualization uses them to show meaning. This can lead to a discussion of what one could do with graphical features and what graphical features are best suited for representing what types of evidence. See Bertin’s Semiology of Graphics (2010) for an influential discussion of the types of variables from size, position, colour, shape, orientation and texture.

13 Leave a comment on paragraph 13 0 Progression: One way to teach a practice based stream where students use visualizations is to progress from using relatively simple tools (like Infogr.am and Voyant to adapting the data, code and styling of D3 visualizations, using RAW as a bridge.

14 Leave a comment on paragraph 14 0 Questions: Some questions we have found that provide a context for discussion include:

  • 15 Leave a comment on paragraph 15 0
  • Can a visualization stand alone or does it need a text to contextualize it?
  • How is text graphical? How is an outline or a list a visualization?
  • What does interactivity add? How is a serious game a visualization?
  • Does a visualization have to be beautiful to communicate?
  • Do visualizations represent a truth about some phenomenon or do they model something?
  • What is it difficult to show with a visualization? How can visualizations mislead readers?


“What is Visualization?”

VisualSense by Lev Manovich

VisualSense by Lev Manovich

18 Leave a comment on paragraph 18 0 This article provides a useful on-ramp for defining some aspects of information visualization, or infovis as it is commonly abbreviated. Manovich situates infovis in relation to other fields such as scientific visualization and information design, while also recognizing that the distinctions are sometimes fuzzy. Two core principles of information visualization are discussed in more depth: 1) reduction (ignoring details of individual items in favour of representing patterns from a subset of characteristics); and 2) spaciality (using variables such as position, size, shape, and movement). Manovich argues that the explosive development of computer graphics during the past two decades has enabled visualization without reduction, or what he calls “direct” or “media” visualization: items individual items are represented in some recognizable form instead of abstract representations like dots on a graph.

19 Leave a comment on paragraph 19 0 We ask students to navigate through several galleries of visualizations (see “Related Materials”) and identify 5 examples of direct visualizations while thinking about the advantages and disadvantages of this technique.

“Humanities Approaches to Graphical Display”

Complex and multi-faceted bar graph by Xárene Eskandar

Complex and multi-faceted bar graph by Xárene Eskandar

22 Leave a comment on paragraph 22 0 Johanna Drucker’s article is an excellent way of framing epistemological issues of visualization in the humanities. She urges us to rethink the notion of data as what is given and instead think of capta as what is taken and constructed. Drucker argues that this move will lead us to forms of graphical expression that are more nuanced and truer to humanistic perspectives on knowledge. By providing examples of how to reconceptualize visualizations such as bar charts, timelines, and maps, Drucker shows how every aspect of visualization is subject to interpretation, even though most visualizations mask the uncertainty and the decision-making processes.

23 Leave a comment on paragraph 23 0 In discussing this article it may be useful to provide some philosophical context for subjectivity and epistemology, especially with respect to cultural interpretation. A useful exercise is to provide students a conventional example of data visualization and have them imagine how it might be reworked to expose how the interpretative act of visualization—how the data was captured, manipulated, by who and for who.

“Information Visualization for Humanities Scholars”

Mandala Browser by Sinclair and Ruecker

Mandala Browser by Sinclair and Ruecker

26 Leave a comment on paragraph 26 0 This article explores information visualization for the specific purposes of humanities scholarship. Given that the humanities value original and persuasive arguments, we can assess the value of individual visualizations by determining how well they promote the proliferation of perspectives. This is partly why interactive interfaces can be so enriching for humanities scholarship: they’re conducive to exploration and co-creation. Based largely on the authors’ visualization prototyping work, the article reviews a range of visualization archetypes including 1) Browsing by Grouping; 2) Revealing Features; Time and Space; Typographic Form; and Interactive Glyphs. The article focuses on humanities scholarship, it can be interesting to ask students to think through how applicable the article is to other disciplines and/or outside of academia.

“Visualizing Information for Advocacy”

Screenshot of visualisingadvocacy.org

Screenshot of visualisingadvocacy.org

29 Leave a comment on paragraph 29 0 This is a rich website that provides a wide range of resources from guidance on working with data to a list of visualization tools. There is also an open access book that discusses visual rhetoric and—based on several case studies—guides the reader through the stages of a project from getting an idea and constructing a dataset to developing a visualization and disseminating it. Though the book may not place as much emphasis on interpretation as Drucker (see previous item), it does insist on creativity, rhetoric, and audiences. We also appreciate how it bridges visual information design and activism in ways that will resonate with anyone interested in the public humanities. We typically ask students to read the book while starting a list of possible social causes that could interest them for a course project.

“The Ethics of Visualization”

Screenshot of video of Chris Alen Sula

Screenshot of video of Chris Alen Sula

32 Leave a comment on paragraph 32 0 This is a video of a talk given by Chris Alen Sula that starts with a brief but useful history of visualization. He makes the point that ethics aren’t often addressed in discussions of visualization, especially in the academic context. Sula proposes that useful groundwork for an ethics of visualization can be provided by 1) speech act theory, 2) role-based morality, and most powerfully 3) general ethics frameworks. The talk unpacks each of these and provides several useful perspectives for thinking about the ethics of visualization, particularly in the context of the Digital Humanities.

“Studies in Communication and Culture: Data”

Screenshot of Laura Klein’s course website

Screenshot of Laura Klein’s course website

35 Leave a comment on paragraph 35 0 Though not solely on visualization, Lauren Klein’s syllabus touches on a many essential topics related to uses of data in the digital humanities. Several topics explore the relationship between facts and data, there’s an overview of major kinds of visualization, and she addresses cultural and social issues that arise from data (from art to surveillance). Interspersed with the academic readings are several excerpts of fiction, such as Minority Report, The Matrix, and Gattaca.

36 Leave a comment on paragraph 36 0 Klein has also explored the way the history of visualization has been presented and alternative histories. A talk she gave to the 3DH project is here where she talked about the Speculative Designs project which is recovering the work of Elizabeth Peabody. There is a prototype that lets students build Peabody mural charts. This project creates a context for discussing the stories told about visualization.


Screenshot of Infogr.am website

Screenshot of Infogr.am website

39 Leave a comment on paragraph 39 0 Infogr.am is a web-based application that makes it relatively easy to experiment with creating interactive charts and infographics that can be published or embedded in another web page. There are over 35 chart types, including the usual suspects (bar, line, pie, scatter, bubble, wordcloud, treemap, candlestick, etc.). We especially like the pictorial charts for infographics. There’s also powerful mapping functionality that geocodes named locations (a place like “Montreal” is converted to latitude and longitude coordinates).

40 Leave a comment on paragraph 40 0 We usually introduce infographics by discussing the rhetorical style of “The Humanities Matter!” infographic and then ask students to experiment with storytelling in Infogr.am using several different charts and maps, on a topic of their choice. The free version of Infogr.am is usually sufficient for the purposes of creating simple infographics.


Screenshot of RAW website

Screenshot of RAW website

43 Leave a comment on paragraph 43 0 RAW says in its tagline that it is “The missing link between spreadsheets and vector graphics”. It may not be the only missing link out there, but it certainly is powerful and user-friendly. Students can choose from one of the sample datasets (cars, movies, music, cocktails), or copy and paste data from their own spreadsheet. Next students can choose from one of 16 interesting chart types and customize which data column should be used for structure, colour, size and other chart dimensions.

44 Leave a comment on paragraph 44 0 RAW provides ample opportunity for students to think about the nature and format of different datasets, the rhetorical baggage of different genres of visualization, and how different visualizations with different options can show the same data very differently. RAW is also an excellent on-ramp for web-based D3 visualizations.

“Voyant Tools”

Screenshot of Voyant’s TextualArc tool

Screenshot of Voyant’s TextualArc tool

47 Leave a comment on paragraph 47 0 Voyant Tools is a web-based text analysis and visualization environment. One of its strengths is in moving quickly from one or more text documents to a wide variety of tools and visualizations for interpretation. Some of the visualizations are more common (like the Cirrus word cloud or the Trends line chart of terms) while others are more unusual and playful (like Knots or TextualArc inspired by the classic TextArc by Bradford Paley).

48 Leave a comment on paragraph 48 0 Voyant Tools can suggest ways of visualizing data when you start with unstructured text (i.e. not tabular data). We ask students to skim through the full list of tools and then to explore Voyant with a corpus of their own essays to see if they can discover unsuspected characteristics of their writing. It also can be used to show how different visualizations can interact in different views that combine tools. Finally, Voyant can export interactive panels that can then be embedded in online essays if you want students to use visualizations in the context of a essay. You can see examples of how we do that in the web site for Hermeneutica (2016).


Screenshot of BatchGeo.com

Screenshot of BatchGeo.com

51 Leave a comment on paragraph 51 0 BatchGeo is a user-friendly and free resource for experimenting with mapping geographical data. The user can add tabular data (by uploading a spreadsheet or pasting rows into a box), define relevant columns and generate an interactive map. One of the more useful features of BatchGeo is that it tries to automatically resolve addresses and locations to geographical coordinates (though it’s worth pointing out the limitations of such automation and the potential for ambiguity and errors). Generated maps can be shared by URL and embedded in web pages. Students could be encouraged to look for local sources of open data or search through one of many dataset portals such as Datahub.


52 Leave a comment on paragraph 52 0 Below is a list of visualization galleries. We find that having students travel through the galleries is a good way of familiarizing thems with the variety of data visualizations out there (even if the vast majority have little to do with humanities scholarship). We ask students to compile an annotated set of their favourites, which can often be a source of inspiration for their own work.


54 Leave a comment on paragraph 54 0 Bertin, J. (2010). Semiology of Graphics: Diagrams, Networks, Maps. Reprint from Esri Press.

55 Leave a comment on paragraph 55 0 Drucker, J. (2010). “Graphesis: Visual Knowledge Production and Representation.” Poetess Archive Journal. 2:1. PDF Available.

56 Leave a comment on paragraph 56 0 Drucker, J. (2014). “Graphesis: Visual Forms of Knowledge Production.” Harvard University Press.

57 Leave a comment on paragraph 57 0 Rockwell, G. and S. Sinclair (2016). Hermeneutica: Computer-Assisted Interpretation in the Humanities. MIT Press. See also Hermeneutica web site.

58 Leave a comment on paragraph 58 0 Tufte, E. (1983). The Visual Display of Quantitative Information. Cheshire, CT, Graphics Press. See also Tufte’s web site.

Page 64

Source: https://hcommons.org/keywords/visualization/