Final paper Get Real! / MA New Media and Digital Culture

University of Utrecht

November 2010

DATAVISUALIZATION

INCITING

CONVERSATIONANKE HANS3 6 2 9 4 2 2

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

2. From dataset to potential social object 4

3. Criteria for the sociality of an object 7

Object centered sociality theory 7

Visual elements contributing to the storytelling potential 8 of datavisualization Participatory storystelling 9

4. Flickr: a community evolving around images 10

5. Criteria for the sociality of an object revisited 11

6. Analysis of a visualization 12

Conclusion & Discussion 14

Bibliography 16

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1. Introduction

Initially datavisualization technologies have been used by an elite as a tool for data

analysis to 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.

Evidently, with this new type of datavisualization insight can be gained into users’

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

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

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 ‘data-

subjectivity’, 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

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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.

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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).

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).

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Figure 4: Swivel drew on public images from Flickr to decorate visualizations (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 “creates an object that

contains a better overall presentation of the subject matter than any one person could

hope to come up with.” (Macdonald, Stanton, Yuille et al. 2009: 198)

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

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

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

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)

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 –worlds in which the objects are non-human entities– 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

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

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) ».

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 in 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 viewer’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.

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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

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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 an individual moment while the production of

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.

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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,

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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)

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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

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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?

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

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

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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/

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