Datavisualization inciting conversation by Anke Hans

DATAVISUALIZATION INCITING CONVERSATION ANKE HANS 3 6 2 9 4 2 2

Final paper Get Real! / MA New Media and Digital Culture University of Utrecht November 2010

Abstract A new type of datavisualization is emerging, allowing everyone to upload their personal data, to visualize it and share it with others in a social network. This paper investigates the social potential of this democratized datavisualization by looking at the way datavisualizations give rise to conversation. Several factors appeared to play a role. First, a visualization has to be placed as a central element in a social interaction. Second, sociality can be facilitated by visual narrative tactics and narrative structure tactics. Furthermore, a visualization should have the potential be shaped by a user. The analysis of the way Flickr has created a community around digital photographs added the comment, note and annotation functions to the criteria for sociality of datavisualizations. Several of these criteria were encountered by analyzing a visualization from Manyeyes.com. The charge of the comments to visualizations however, does not seem to be fully explained by these criteria alone. It is plausible that this can be explained by the incongruence between the many assumptions underlying the process of datavisualization and the semblance of objectivity and truth that datavisualiations seems to spread.

Contents

1. Introduction

2. From dataset to potential social object

3. Criteria for the sociality of an object

Object centered sociality theory

Visual elements contributing to the storytelling potential of datavisualization Participatory storystelling

8 9

4. Flickr: a community evolving around images

5. Criteria for the sociality of an object revisited

6. Analysis of a visualization

Conclusion & Discussion

Bibliography

1. Introduction Initially datavisualization technologies have been used by an elite as a tool for data analysis

fulfill

scientific

and

businesslike

purposes.

Recently

however,

datavisualization tools have become accessible to a general public by the development of internet-based visualizations. This democratization of visualization has caused the emergence of social purposes to datavisualization. For on several websites anybody can upload and visualize their data these days. Figure 1 shows an example of such a visualization, created and uploaded on Many Eyes by rpnabar. It represents the financial aid per capita that different countries donated to Haiti in response to the massive earthquake that shook this country in January 2010.

02 Figure 1: A visualization of the world aid to Haiti, made by rpnabar, created at January 25 2010 (Manyeyes.com)

Evidently, with this new type of datavisualization insight can be gained into usersâ&#x20AC;&#x2122; personally collected data. By means of comment functions implemented on Many Eyes, others can also respond to the visualization. Figure 2 shows two comments on the

Figure 2: Two comments to the visualization of the world aid to Haiti (Manyeyes.com)

visualization in Figure 1. As can be seen, the first user asks the visualizator where Cuba is located in the image and the second user suggests that it would have been nice if the European Union would have been included as a uniform body. So by means of this new type of datavisualization users are enabled to personally express themselves and socially interact with others through the visualization (Kosara, Rosling, Sack et al. 2007: 129). With regard to this development, Manovich (2003) wonders: “If daily interaction with volumes of data and numerous messages is part of our new ‘datasubjectivity’, how can we represent this experience in new ways?” (p. 9) Segel&Heer (2010) also address the question of a new type of datavisualization by stating: “Currently, most sophisticated visualization tools focus on data exploration and analysis. [..] It remains an open question how the design of such tools might be evolved to support richer and more diverse forms of storytelling.” (Segel&Heer 2010: 1) A partial answer to these questions already exists, namely by means of several websites dedicated to employ the social potential of datavisualization. As Segel&Heer (2010) state: “Many have observed the storytelling potential of data visualization.” (p. 2) Gapminder.org is a good example. Gapminder places large amounts of worldwide public health data at the disposal of “an informed and interested general public, rather than visualization researchers” for them to animate and submit to many different forms of analysis. (Kosara, Rosling, Sack et al 2007: 128; Macdonald, Stanton, Yuille et al. 2009: 193) Manyeyes.com is an even better example, for it allows users to upload personal data and to create interactive visualizations that provide its creator with insights about those data. The underlying goal of Many Eyes is to create a medium that stimulates discussion with other users about the results of the analyses, called ‘asynchronous collaboration’. (Kosara, Rosling, Sack et al. 2007: 129) Gapminder and Many Eyes constitute a first step towards representing experiences in a new way, but it does not yet embody a satisfactory answer to Manovich and Segel&Heer. There is however, an intention to extend the work of the aforementioned pioneers, which will be discussed in section 2 of this paper. The research in this paper is aimed at deepening the social potential of datavisualization, a subject that has been stirred by some theorists but not yet shaken. The research question therefore is formulated as follows: How do datavisualizations give rise to conversation? I will be looking at the elements in datavisualizations which lead users to comment on it. In doing so, I adopt the perspective of the reader who is moved to talk by means of a visualization. What makes this subject particularly intriguing to investigate is, in the words of Sculey&Pasanek (2007) who speak of the dangers accompanying data exploration “... that a distorted artifact, a picture, may be

mistaken for an underlying truth.” (p. 2) For the new datavisualization revives the discourse about the truth claim surrounding datavisualization. For the end of this research, datavisualization is defined as ‘a representation of a data-set, which affords conversation around different aspects of the data and visualization method’. (Macdonald, Stanton, Yuille et al. 2009: 195) Conversation then, is defined as ‘comments from which can be concluded that the visualization is understood by the viewer after which the viewer can add his own meaning to it.’ The present paper is structured as follows. First I will cover sections 2 and 3 describing multiple relevant theories concerning sociality and datavisualization. Then I will present Flickr as a succesful example of a community which evolves around digital images. Section 4 consists of an overview of the criteria for sociality which will have been encountered on the way. In Section 5 I will then test these criteria on the basis of a datavisualization from Many Eyes. This part is followed by the conclusion and a critical reflection on the conclusion and the research in general.

2. From dataset to potential social object In their article “The Social Life of Visualization”, Macdonald, Stanton, Yuille et al. (2009) provide an integral reaction to the thoughts of Manovich and Segel&Heer as described in the introduction. They propose a three staged process for the design of an information visualization interface which they consider to be apt to let users interact with visualizations to such a degree that it encourages the use of datavisualization as a storytelling medium. The goal of this interface is defined as follows: “...shared storytelling through visualization with the ability to create knowledge artifacts around data.” (p. 195) The principle behind the design is the positioning of the visualization between the original dataset and the user. Figure 3 offers an illustration of the design process.

Figure 3: The three stage process for the design of an information visualization interface as proposed by Macdonald, Stanton, Yuille et al. (2009)

The first of the three steps in the process is CREATE which is split up in a part called MAPPING

and a part called DECORATION. Mapping helps the possibly unexperienced

visualizer to choose a visualization technique which suits his communication goals. Then the visualization is being decorated, meaning that it is assigned an identity in order to make it a recognizable entity in a digital social network. As people can make themselves recognizable by uploading an avatar or creating an online profile, visualizations can be given a title, a description and/or an avatar. Swivel for example, drew on public images from Flickr to decorate visualizations (see Figure 4).

05 Figure 4: Swivel drew on public images from Flickr to decorate visualizations (Macdonald, Stanton, Yuille et al. 2009)

The second step in the design process is INTERPRET, consisting of a part called TWEAKING

and a part called ANNOTATION. When a visualization becomes tweakable, the

dynamic nature of the visualization is being put forward. A user should be able to affect a visualization by means of direct manipulation of parameter values which causes the visualizator to better understand the relationship of the parameters to the whole visual analysis (see Figure 5).

Figure 5: The interface of Gapminder is tweakable (Macdonald, Stanton, Yuille et al. 2009).

Annotation then, should enable users to comment on or draw attention to specific elements of the visualization. This aspect of the interface works on the collaboration and collective intelligence principle that combining knowledge â&#x20AC;&#x153;creates an object that contains a better overall presentation of the subject matter than any one person could hope to come up with.â&#x20AC;? (Macdonald, Stanton, Yuille et al. 2009: 198)

Figure 6: The annotation system of Wikinvest (Macdonald, Stanton, Yuille et al. 2009)

The last step in the design process is to CAPTURE UNDERSTANDING: the user has to be able to record his understanding of the visualization after having edited it, by taking a snapshot of it. When placing a comment related to the visualization it should be made

possible to add this same snapshot to the comment so that others can see what the user saw in editing the visualization. This stimulates the understanding of and the communication around the visualization. (p. 193-199) (see Figure 7)

Figure 7: Many Eyes stores snapshots of users alongside comments (Macdonald, Stanton, Yuille et al. 2009)

3. Criteria for the sociality of an object How can we know if this framework as proposed by Macdonald, Stanton, Yuille et al. will work? Are there criteria for sociality which can serve as a basis to test it? The work of several theorists from different scientific fields can serve as a mirror to the social potential of the new datavisualization.

Object centered sociality theory Sociologists Knorr-Cetina&Bruegger (2000) treat changing social relations as a consequence of digital technology in their postsocial model of sociality. According to them, digital technology has caused an increased presence and relevance of object worlds â&#x20AC;&#x201C;worlds in which the objects are non-human entitiesâ&#x20AC;&#x201C; in the social world. This influx of object worlds into the social world coincides with changing patterns of human relations. (p. 141-142) For in postsocial sociality there are major classes of individuals who tie themselves to relationships with objects. (Knorr-Cetina 1997: 1) These new kinds of bonds between humans and objects change the structure of relationships and our conception of sociality. (Knorr-Cetina&Bruegger 2000: 143) Sociality can now arise through objects if they are being placed as a central element in a social interaction,. For objects around which discussion takes place, helps to focus and start conversation between people. (Macdonald, Stanton, Yuille et al. 2009: 194) In our case the object is a visualization in a network of users. By prioritizing the visualization rather than the relations between people in the network -as is proposed by the model in section 2- the

object becomes a social artefact of which people can take possession briefly and add their own meaning to it by writing comments or annotation, resulting in conversation. The added meaning then becomes part of the shared history of the social artefact as it exists within the object-centered social network (Macdonald, Stanton, Yuille et al. 2009: 194) Âť. In short, object centered sociality theory attributes the following criterion for sociality of an object: an object has to be placed as a central element in a social interaction.

Visual elements contributing to the storytelling potential of datavisualization Segel&Heer

(2010)

have

researched

narrative

storytelling

visualization

environments. Being part of the Standford Visualization Group, they wrote a paper called Narrative Visualization: Telling Stories with Data, in which they investigated the way that visual elements directly contribute to the storytelling potential of datavisualization. Segel&Heer found that there are two types of features which facilitate narrative structures of datavisualizations. First there are visual narrative tactics. Visual narrative tactics can be subdivided in three sections, of which the following two are relevant to this research. The first is visual structuring, which are mechanisms that communicate the overall structure of a narrative to the viewer and allow him to identify his positions within the larger organization of the visualization, for example by providing a consistent visual platform or a timeline slider. Highlighting, then, refers to visual mechanisms that help direct the viewerâ&#x20AC;&#x2122;s attention to particular elements in the display. This can be achieved by increasing the salience of an element relative to its context, by use of color, motion, framing and size for example. The second type of features are narrative structure tactics, which also assist and facilitate the narrative. Narrative structure tactics can be subdivided in three sections, of which again two are relevant to this paper. The first is called interactivity, referring to the different ways a user can manipulate the visualization (for example by means of filtering, selecting, searching and navigating) and also to how the user learns those methods (by explicit instruction, tacit tutorial or initial configuration). Interactivity allows the visualization to be manipulated by the viewer. Messaging, then, refers to the ways a visualization communicates observations and commentary to the viewer. This can be realized by short text fields providing observations and explanations about the images in forms like labels, captions, headlines or annotations (p. 7-8). Visual structuring and highlighting constituting visual narrative tactics and interactivity and messaging constituting narrative structure tactics can be added as criteria for sociality of objects.

Participatory storytelling The new datavisualization which enables users to express themselves, their thoughts and their experiences by means of digital techniques can be sided with what Jenkins (2006) calles participatory culture: … a culture with relatively low barriers to artistic expression and civic engagement, strong support for creating and sharing one’s creations, and some type of informal mentorship whereby what is known by the most experienced is passed along to novices. A participatory culture is also one in which members believe their contributions matter, and feel some degree of social connection with one another (at the least they care what other people think about what they have created). (p. 3)

After all, the democratization of datavisualization equals the lowering of barriers to engagement of users who create, interpret and share their visualizations with others. The engagement incites comments from the reader to the visualizator which creates a social connection between the two. Within participatory culture, the new datavisualization falls under a shift towards an inclusive production process called cultural convergence which Jenkins (2004) defines as “a process of altering relationships between technologies, industries, markets, genres and audiences.” (p. 34) Cultural convergence is characterized by average people being given tools at their disposal to archive, annotate and recirculate content. (Jenkins 2004 according to Deuze 2005: 10) This is literally the case for the new datavisualization: everybody can create, store and share their visualizations. With the emergence of participatory culture come new forms of literacies, which Jenkins calles new media literacies: cultural competencies and social skills that are needed in the new media landscape. There are two new media literacies that are relevant to this research. The first is distributed cognition: the ability to interact meaningfully with tools that expand. Datavisualization is a tool that is expanding as we speak and therefore requires new ways of interactions with this tool. The second kind of literacy is collective intelligence: the ability to pool knowledge and compare notes with others toward a common goal. (Jenkins 2006: 4) The concept of collective intelligence has already been treated in section 2, describing the function of annotation as part of the design process of an information visualization interface. Applying this concept to the new datavisualization, knowledge is pooled by the placement of comments constituting conversation towards the common goal of sociality and knowledge expansion. What we can distill from Jenkins’ theory on participatory culture and convergence culture, still continuing our quest for criteria for sociality of objects is: the

object has to have the potential to be shaped (archived, annotated and recirculated) by the end-user.

4. Flickr: a community evolving around images Let us now have a look at an example of an established community which succesfully evolves around images. Flickr, a populair online social network aimed at sharing digital photos, constitutes such an example: Flickr has become a collaborative experience: a shared display of memory, taste, history, signifiers of identity, collection, daily life and judgement through which amateur and professional photographers collectively articulate a novel, digitized (and decentralized) aesthetics of the everyday. (Murray 2008: 149)

In the words of Knorr-Cetina the digital photos uploaded on Flickr function as objects of sociality. The object that the Flickr community evolves around –digital photos– is different from the object that is central to the new datavisualization –visualizations. Photos

directly

represent

individual

moment

while

the

production

datavisualizations is layered. For in order to share the visualization with others, the data first has to be collected and then visualized through software. The image that results from this process seems to represent more than what is represented, namely objectivity. In short: photos and visualizations represent different visual genres. But what Flickr and the new datavisualization have in common, is the image inciting conversation from users and that mere fact makes it worthwile paying attention to Flickr. So how are comments elicited around photos in the Flickr community? Murray (2008) clarifies this question and distinguishes three social features related to representation in Flickr. The first is the comment function, which as long as a photo is marked ‘public’, enables every member to comment on a photo. According to Murray, this develops community bonds but also serves a greater purpose of “building a shared aesthetic and negotiating the limits of judgment.” (Murray 2008: 158) In the second place, community is created through the use of a tagging system: The tagging system employed by Flickr – which is obviously a different function t h a n commenting, but is one of the ways that people find one another’s photos o u t s i d e o f pools and contacts – is a bottom-up classification system that not only decentralizes control over many collections and pools, but also contributes to the development of a non-hierarchical community aesthetic. (Murray 2008: 159)

At last, users can write comments on other peoples photos by the use of notes. See Figure 8 for an illustration of these features.

11 ` Figure 8: A visualization uploaded on Flickr showing the note function (upper middle), the tag system (middle right) and the comments (lower left) (Flickr.com)

In the words of Segel&Heer as discussed in the previous section, we can state that these features Flickr has created to grow a community fall under the narrative structure tactic called messaging: the ways a visualization communicates observations and commentary to the viewer. For the comment function and the note function however, this tactic is reversed. The reversal consists of a change of roles of the visualizator and the viewer. It is not the visualizator who places annotations on the image in order to communicate observations to the viewer, but the viewer who does so.

5. Criteria for the sociality of an object revisited Several criteria for the sociality of an object have moved past. The formulation of these criteria is necessary to make the sociality of datavisualizations tangible. Before looking at some datavisualizations to see if and how these criteria have been applied in practice,

let us therefore recapitulate these criteria. Knorr-Cetina postulated the object centered sociality theory, stating that objects can require sociality if they are placed as a central element in a social interaction. Segel&Heer formulated several concrete tactics which contribute to the sociality of objects: visual structuring and highlighting as visual narrative tactics and interactivity and messaging constituting narrative structure tactics. Jenkins speaks of participatory culture and convergence culture and submitted the quality of an object of having the potential to be shaped by a user. The way the Flickr community is constructed has, among other things, to do with the implemented comment function, note function and annotation function. These functions regard the narrative structure tactic of messaging by Segel&Heer. It has to be noted that the tactics as defined by Segel&Heer proceed from the perspective of the visualizator. In the case of Flickr however, it is not the visualizator who places comments and notes on objects, but the viewer who does so.

6. Analysis of a visualization The criteria that were distilled from the work of several theorists can now be applied to practice. Let us take a closer look at the visualization from the Introduction concerning the world aid to Haiti (Figure 1). Figure 9 depicts some more comments that were made to this visualization. This visualization clearly has incited a lot of comments. Some of them simply repeat what was visualized, such as spaidy stating “Canada has its capacity is very big, I just found out that this information is very useful and helpful.” Others take it one step further and add their opinion to the result of a visualization, as Vickey31 does: “I am really surprised that the United States hasnt given more to Haiti. I know we were there for a long time. I think this is sad and if everyone pitched in we could fix these problems.” Anonymous expresses positive emotion after having seen the visualization: “Way to CANADA! This is hat we should be doing instead of following the USA war.” What about the visualization made these users produce these comments? First of all, the visualization is prominently placed on the centre of the Many Eyes website, with the menu, information about the visualization and the comments concerning the visualization being placed on the sides and below the visualization. The visualization is thus placed as a central element in the social interaction, conforming Knorr-Cetina’s object centered sociality theory. Second, there is a comment function implemented implying the narrative structure tactic called messaging, as defined by Segel&Heer. Another form of messaging is the title of the visualization as provided by the visualizator explaining something about the image. Furthermore all of the comments carry with them small alternative versions of the visualizations on the left side, which are snapsnots of revisions of the visualization by the particular users before

13 Figure 9: A part of the comments for the visualization of the world aid to Haiti as visualized in Figure 1 (Manyeyes.com).

adding their comments. These snapshots inform other readers about the way the visualization was understood at the time the comment was created. In the words of Jenkins, the object has been shaped by the user , recirculated to be more precise, before a comment was created. Segel&Heer denote this as a narrative structure tactic called interactivity, since it allows the user to manipulate the visualization. Located just below the visualization is a bar with three variables which the user can adjust to tweak the visualization. For example, the bubble size can be chosen to represent ‘¢ per person’, ‘population’ or ‘Funding, committed and uncommitted, ¢’. This feature is a mechanism that helps orient the user in the organization of the visualization and can therefore be identified as visual structuring, a visual narrative tactic. This is as far as all the criteria discussed in this paper apply to the visualization from Many Eyes. Does this cover the charge of the comments? Or is there more?

Conclusion & Discussion Datavisualization tools are no longer extraordinary and doomed to be used by scientists only; they have been democratized so that everyone is now able to upload data and visualize it by means of free software on websites as Many Eyes. This has given rise to sociality in datavisualization. The research in this paper was aimed at deepening the social potential of datavisualization by investiging the way datavisualizations give rise to conversation. In short, there are several factors which contribute to the social potential of datavisualizations, which in the context of this paper were called objects. First, object centered sociality theory requires a social object to be placed as a central element in a social interaction. Sociality can be facilitated by visual narrative tactics (visual structuring and highlighting) and narrative structure tactics (interactivity and messaging). Furthermore, an object has to have a potential to be shaped by a user, by means of archiving, annotating and recirculating it. Finally, Flickr developed comment, note and annotation functions to stimulate conversation between users. The analysis of a visualization from Many Eyes confirmed the practical use of the following criteria: object centered sociality theory, messaging, interactivity, the potential of an object to be shaped and visual structuring. As touched in the introduction and the analysis of a visualization, one can ask oneself if these criteria for sociality cover for the charge of the comments. There seems to be more to datavisualization. What makes it fascinating in the first place? Kosara, Rosling, Sack et al. (2007) talk about the powerful nature of datavisualization: “What makes datavisualization powerful in the first place is its compelling visual nature, which makes it much more interesting and impressive than reading a table with numbers.” (p. 128) This is nothing new. But now that datavisualization is transforming into a social medium there is a renewed interest for the functions of datavisualization. With this comes a renewed and intensified discussion of an old matter which has always played part in the discours around datavisualization which is the claim to meaning, or: the truth claim. Datavisualizations in a sense are, as was discussed in the section about the sociality of digital photographs on Flickr, nontransparant images because of the assumptions that are hidden in the techniques that are needed in order to produce a visualization. In the process of datacollection there always is a selection bias of the investigator reducing the data to content and in the visualization software there always are tuns of assumptions about the underlying structure of the data, which significantly impacts the final results. But these assumptions cannot be seen. Yet visualizations emanate a semblance of objectivity and truth which –as we have seen discussing the Many Eyes visualization– can incite a range of different comments around visualizations. (Sculley&Pasanek 2007: 1-2) What is important in discussing

datavisualizations including the new type of datavisualization that has been the subject to this paper is to always be conscious of the processes that preceded these images and make balanced claims about the meaning of datavisualizations. If we do so, I do not see any dangers in the development of a new, social datavisualization.

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> World aid to Haiti example : http://www-958.ibm.com/software/data/ cognos/manyeyes/visualizations/world-aid-to-haiti-aid-per-capita

(retrieved

November 1 2010). Murray, S. (2008). Digital Images, Photo-Sharing, and Our Shifting Notions of Everyday Aesthetics. Journal of Visual Culture 7: 147-163. Sculley, D. & Pasanek, B. (2007). Meaning and Mining: the Impact of Implicit Assumptions in Data Mining for the Humanities. Digital Humanities 2007, University of Illinois, June 3-7, 2007. Segel, E. & Heer, J. (2010). Narrative Visualization: Telling Stories with Data. EEE Trans. Visualization & Comp. Graphics (Proc. InfoVis).