growing data, changing journalism

8/4/2019 Growing Data, Changing Journalism

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Growing Data, Changing Journalism

An Explorative Inquiry Into The Rise Of Data Journalism

8 July 2011

Eric R. Alberts (3485595)

Coding Culture (200600075)

MA New Media & Digital Culture

Mirko T. Schfer & Nikos Overheul

2010-2011


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Eric R. Alberts2

1 Introduction

Hal Varian, chief economist at Google, stated in an interview with McKinsey

Quarterly in 2009 that the next ten years statisticians will have the sexiest jobaround. He motivated this statement by arguing the ability to take data to be

able to understand it, to process it, to extract value from it, to visualize it, to

communicate it [] is going to be a hugely important skill in the next decades

(Manika 2009). When looking at Varians employer it is obvious why he came to

this conclusion. A company that benefits greatly from vast amounts of data is

Google. Every day enormous amounts of data are collected as a by-product of user

interactions with Googles services. From this data new economic value is created.

Google, however, is but one example of how important large data sets have becomeduring the last decade. In an attempt to map the current explosion of data and the

challenges that derive from it, The Economist published a special report in

February of 2010. In this special issue, Joe Hellerstein, a computer scientist at the

University of California, is quoted, naming the current age the industrial

revolution of data (Cukier 2010, 3). The Economist continues by stating that [t]he

effect is being felt everywhere, from business to science, from government to the

arts (ibid.) giving this phenomenon the label of big data.

In this paper an exploratory inquiry is conducted into one specific area in which big

data is also becoming ever more important: journalism. Several interesting news

reports and cases have already emerged, which ensued directly from delving

through large quantities of data. A prime example is the large-scale investigation

into British politicians expenses, invigorating the debate on government

expenditure. It is likely that in the near future similar data-driven news reports

will see the light of day, as large data sets and sophisticated tools, which allow for

journalists to make sense of this data, are becoming more and more dispersed over

the Internet. Access to and the use of databases are no longer proviso to IT-

specialists or investigative journalists conducting expensive research.

According to the European Journalism Centre (EJC), which organized a roundtable

conference on data journalism in Amsterdam last year, [d]eveloping the know-

how to use the available data more efficiently, to understand it, communicate and

generate stories based on it, could be a huge opportunity to breathe new life into

journalism ( Data-driven Journalism 2010, 6). The role of the reporter can even

be expanded or changed to that of sense-maker by digging deep into data, making

journalism more socially relevant (ibid.). This paper critically analyses these


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Growing Data, Changing Journalism 3

opportunities but also discusses the challenges that derive from data journalism.

By critically examining matters such as algorithms, data visualisation and

participatory journalism this paper makes an effort to further contextualise this

new phenomenon.

The inquiry into the properties of data journalism will be conducted on two levels.

First, this paper discusses data journalism on a material level, as databases are

becoming the new valuable sources for journalists. The issue of materiality can be

placed within an already active debate on how the materiality of books is

transforming in the digital age. Companies like Google and Amazon are digitizing

books into data objects, bringing on changes to our relationship with books and

databases. Materiality in this paper also relates to the use of software tools and the

choice of specific algorithms to structure these large amounts of data. Also, visualisation of data is becoming a widely accepted and applied manner for

comprehending the vast and abstract data but not without making decisions that

have consequences for the displayed data.

Second, data journalism will be discussed on a social level as news organisations

are actively involving their readers in analysing large data sets. The practice of

crowdsourcing, for example, has the potential to change traditional producer-

consumer relationships within journalism. The inquiry into the properties of data

journalism on a material and social level will be related to various recently

published examples of data journalism. An inquiry into the opportunities and

challenges that derive from data journalism, however, cannot take place before

giving a theoretical framework. This paper will therefore first embed data

journalism in a larger context, describing how the rise of this new phenomenon can

be seen within an already changing world of journalism under the processes of

media convergence and participatory culture.

This paper is intended to offer an insight into a new journalistic practice, which is

drawing more and more attention to it as digital information is rapidly expanding,

becoming widely available and publicly accessible. This paper contextualizes data

journalism and critically engages assumptions and consequences in an attempt to

offer a nuanced overview of this emerging branch in the already changing field of

journalism in the digital age, which, according to Adam Westbrook, author of The

Next Generation Journalist , is one of the big potential growth areas in the future

of journalism (ctd. in Data-driven Journalism 2010, 3).


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Eric R. Alberts4

2 Theoretical framework of data journalism

As stated above, before discussing the opportunities and challenges it is of

importance to first get a grip of what data journalism is and how this practicerelates to journalism in general and the trends in todays digital culture. Because

data journalism is only recently taking shape it has not been fully theorised yet.

There is, however, extensive theory to be found on participatory journalism, the

blurring of traditional relationships between news media and consumers of media.

In this chapter, data journalism is understood in terms of participatory journalism

but with a much more prominent technological aspect: its reliance on databases.

Data journalism as a practice blends technology and culture in a way that it is not

feasible to separate the technological aspects from its social context. Before this

argument is further elaborated, it is, for the sake of contextualizing, necessary tofirst give an overview of the technological and cultural processes from which

participatory journalism and, thus, data journalism have emerged.

We live in a world that is witnessing a revolution in information technology, a

converging set of technologies, which is penetrating all domains of human activity

(Castells 2000). This revolution, however, is not just a technological process

amplified through digitization, or what Nicholas Negroponte referred to as the

transformation of atoms into bytes (Negroponte 1995). The digital age is also

becoming a unified environment in which computer hardware and software define

possibilities for action and conditions of expression (Rieder & Schfer 2008, 2).

The new human condition is characterized by what Henry Jenkins refers to as

convergence culture, enabling new forms of participation and collaboration

(Jenkins 2006, 245). According to Jenkins [c]onvergence is both a top-down

corporate driven process and a bottom-up consumer-driven process (Jenkins

2004, 37) and is taking place on a global scale in acts of media production and

consumption. Previously set borders between making media and using media, but

also between media industries, continue to blur.

This idea of convergence, the blurring of boundaries set by the conditions of

digitization (Jenkins 2006, 11), was initially enthusiastically welcomed in the field

of journalism by authors like Dan Gillmor (2004) naming it grassroots or

participatory journalism. The proliferation of networked communication

technologies enables people to launch independent news organisations as a direct

response to what were perceived as shortcomings in mainstream news coverage

(Deuze 2008). A few of these alternative websites produced by amateurs/citizens

are Indymedia, Wikinews and Ohmynews, the latter being an alternative to the


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highly conservative mainstream press in South Korea (Kahney 2003). Studies on

these cases show how citizen media offer interesting bottom-up alternatives to

conventional top-down practices of news making (Paulussen & Ugille 2008, 26).

At first glance these success stories back the more utopian beliefs of Dan Gillmor. If

this trend would continue, independent participatory journalism might be able to

replace top-down news media and its traditional news media-user relationships.

Closer analysis of participatory journalism which is still a rather ill defined term

(Hermida 2008) shows, however, that it is fair to say that the impact of weblogs

and citizen media on traditional, professional journalism has thus far been rather

limited (Paulussen & Ugille 2008, 26). This is partially due to the prevailing

tendency among journalists to see themselves as the defining actors in the process

of making news (Heinonen 2011). The main conclusion of a study on thedevelopment of participatory journalism on a global scale conducted by David

Domingo et al. reveals that professional newsrooms appear to be rather reluctant to

open up the news production process to the active involvement of citizens

(Domingo et al. 2008). The primary question posed by researchers such as Wilson

Lowrey (2005) of whether participatory journalism is in a way substituting

professional journalism is thus losing relevance. Instead, the focal point of research

on participatory journalism has shifted towards how mainstream news media are

adopting citizen contributions in the process of news production (Paulussen &

Ugille 2008, 26).

In 2003 J. D. Lasica, senior editor of the Online Journalism Review, also stated

readers want to be part of the news process (Lasica 2003, 74). But Lasica

supplemented this statement by noting that instead of looking at participatory

journalism and traditional journalism as rivals for readers eyeballs, we should

recognize that were entering an era in which they complement each other,

intersect with each other, play off one another (73). He continued by stating we

are starting to see a mixture of commentary and analysis from grassroots as

ordinary people find their voices and contribute to the media mix. Blogs wont

replace traditional news media, but they will supplement them in important ways

(74). Although Lasica wrote this essay almost ten years ago, we can see now that

traditional news media indeed continue to dominate the news media landscape and

are becoming ever more capable to harvest the potential of an active audience. For

instance, in the Netherlands Dutch news organisation NRC integrates a successful

weblog with the physical newspaper NRC Next and the Dutch public news

organisation NOS invites young people to contribute to news on its website NOS op

3 (formerly known as NOS Headlines).


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Eric R. Alberts6

Mark Deuze, a Dutch professor in communication sciences who has shed light on

the professional identity of journalists in the context of convergence culture, makes

a similar observation as J. D. Lasica does. According to Deuze convergence culture-

based participatory journalism is best understood as some kind of co-creative,

commons-based news platform that is produced when a professional media

organisation (top-down) partners with or deliberately taps into the emerging

participatory media culture online (bottom-up) (Deuze 2008, 109). Furthermore,

participatory journalism is very much under construction (ibid.). The

convergence of top-down and bottom-up journalism is a work in progress with

more or less traditional makers and users of news cautiously embracing its

potential which embrace is not without problems both for the producers and

consumers (ibid.). Mark Deuze and J. D. Lasica offer a far more nuanced

consideration of participatory journalism in the context of convergence culture.This contrasts early utopian-like considerations, which were initially all-too-easily

taken for granted (Domingo 2008, 680).

Early studies on participatory journalism have also been criticized because of

underlying technological determinism (Paulussen & Ugille 2008, 28). Changes in

journalism were explained as caused by technological developments influencing

the work of journalists from the outside (Deuze 2008, 110). Pablo Boczkowski,

underscores the limitations of a sole focus on the effects of new technologies by

showing that although technologies do produce effects, they can only be

understood in the dynamics of technology adoption processes (Boczkowski 2004,

208). Technology must be seen in terms of its implementation, and therefore how

it extends and amplifies previous ways of doing things (Deuze 2008, 110). Changes

occurring in the field of journalism are therefore better understood as a mutual

shaping of technological and social developments rather than as the effects of

technological processes (Paulussen & Ugille 2008, 28).

At the beginning of this chapter I stated that data journalism as a practice blends

technology and culture in a way that it is not feasible to separate the technological

aspects from its social context. With the use of the theory on participatory

journalism I would like to argue that data journalism is the gradual outcome of a

converging culture, which introduces a constantly changing mix of features,

contexts, processes and ideas into the work of individual news workers (Deuze

2008, 112). This means that convergence culture in this particular context is not

merely technologically (Negroponte 1995) nor solely socially driven. Data

journalism should rather be seen in line of Paulussen and Ugille, as an outcome of

the mutual shaping of technological and social developments.


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Critical analysis, however, shows that convergence is a slow and problematic

process and that its true effects are rather limited. Independent weblogs have not

replaced news corporations and professional journalists remain to have control

over a news story. In extending Paulussen and Ugilles line of thought I would

therefore argue that convergence regarding participatory and data journalism is

taking place horizontally (between technological and social aspects) rather than

vertically (between top and bottom, between professionals and amateurs). In other

words, if convergence culture is generally seen as the process of blurring borders

then the borders regarding data journalism are blurring between the technological

and social contexts. The process of convergence in the case of data journalism

should be captured by a lens that emphasizes actors agency as much as

technologys capabilities (Boczkowski 2004, 210).

At the end of this chapter I would like to extend this lens metaphor by Boczkowski

somewhat further. I believe that this lens can be viewed in terms of Actor-Network-

Theory (Latour 1999) in which human and non-human actants combine to form

hybrid actors. When applying this view to data journalism we do in fact see that in

general the technologies, the data and the software tools, are responsible for larger

parts of the action chains, rendering actions intrinsically hybrid (Rieder & Schfer

2008, 161). The digital environment of the database together with the software

tools that enable access to and structure this environment define possibilities for

action and conditions of expression (160). According to Rieder and Schfer,

software is responsible for extending [] the role that technology plays in the

everyday practices that make up modern life (161). In other words, through the

lens of Actor-Network-Theory data journalism can be seen as a network that

consists of linkage between technological, social and cultural actors making data

journalism a hybrid practice.

3 Exploring the core properties of data journalism

In the context of data journalism as a hybrid practice, a network of human and

non-human actors, we can now explore some of the core elements of data

journalism through the use of different case studies. This chapter tries to flesh out

the elements of data journalism by largely following the chain of value creation (see

illustration 1 below). This chain consists of four properties: raw data, structuring or

filtering data, visualising data and storytelling. As a closure to this chapter and

supplementary to these four elements, the aspect of participation, to which the


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Eric R. Alberts8

theoretic background is given in the prior chapter, will be discussed. It will become

clear that data journalism seems to open up to participatory possibilities in specific

ways.

3.1 Properties of data

It is a truism that the amount of digital data is currently growing faster than

anything else. A 2008 study by marketing research firm International Data

Corporation (IDC) revealed that around 1200 exabytes (1 exabyte is 1 million

terabyte) of digital data was produced that year (Cukier 2010, 5). The majority of

this data consists out of photos, logs, phone calls and other database-to-database

information from which only 5% of the information [] is structured, meaning it

comes in a standard format of words and numbers that can be read by computers

(ibid.). Data and information are epistemologically different, as information ismade up of a collection of data but data and information are increasingly difficult

to tell apart. Raw data is interwoven with todays algorithms and powerful

computers, which can reveal new insights that would previously have remained

hidden (Cukier 2010, 3-4).

Gannett, the holding behind newspapers USA Today and The Indianapolis Star,

has been leader in the area of database applications. Gannett realised early on that

data should be a driving force in online journalism, for a number of reasons. First,

data is evergreen content so its value to users does not end after twenty-four

hours. Second, because of its sheer size, data can be best delivered in a medium

without space constraints. The data is much more valuable if it is accessible and

searchable at the users convenience. Third, Gannett realised that data is much

more applicable to interactive media than, say, in print form. Data is suited for

research and interaction, not so much for passive activities like reading or viewing

(Gordon 2007). Supplementary to Gannetts list of data properties, which are

relevant to journalism, data in general is transmitted and shared in the form of

text, sound, or images without tangible loss. Because of its freedom from physical

constraints data is however easy to manipulate. With a simple click large amounts

of (personal) information can be copied or permanently deleted (Rieder & Schfer

2008, 163).

3.2 Structuring data

In 2002 Wiebke Loosen, assistant lecturer at the Institute of Journalism and

Communications at the University of Hamburg, concluded that the abundance of

information on the Internet, in terms of its storage, management, multiple use and

unlimited possibilities, are challenging journalism regarding its own processes of


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rationalizing information (Loosen 2002, 5). In structuring the vast amounts of

data lies the biggest challenge for businesses, governments and journalists alike.

When structured, data is a potential goldmine. Google is probably one of the most

obvious examples of a company that knows how to generate economic value from

large amounts of data. This is largely the reason why companies like Google and

Amazon choose to also transform physical objects into data objects. Books, for

instance, are being scaled so that various statistical properties can be analysed for

other purposes. Bernhard Rieder calls this computational potential or the value

of the data of millions of scanned books. According to Rieder the book in the age

of the database adds a contemporary wave of new embedded practices and logistics

of what do we read and how we read it (Yudin 2011).

In Rieders view three new practices emerge when books are translated into dataobjects. First, the whole text can be statistically projected that allow various

explorations of the catalogues content. Second, books can be connected with other

books through data, and books can also be connected to other data like the Internet

or Google Scholar. Third, user gestures and practices, such as tagging, clicking,

number of reads, sales and reviews, can be captured through the use of digital

books. In the latter case, user data can be used to create navigational experiences

and opportunities leading to the personalization of reading. In other words, Google

and Amazon, with their systems to digitize books, transform books into

information, and then unbind and rebind it again as an interactive, social and

semantic interface (Yudin 2011).

The transformation of physical books into data objects by Google and Amazon

paves the road to structure information and generate new value from it. In the field

of journalism a similar underlying motive can be found when we look at the recent

investigation by many news organisations into the emails of former governor of

Alaska, Sarah Palin i. The state of Alaska released the emails following a two-and-a-

half year freedom of information process. The emails date from her inauguration as

governor in 2006 through to 2008 and were released in printed form to the news

organisations. The emails had to be digitized in order to successfully structure

them. This is also the case with the documents of British politicians expenses ii. On

The Guardians specially made homepage it says they have 458.832 pages of

documents in their possession and 234.877 pages are yet to be analysed. All of the

nearly 460 thousand pages of receipts and claim forms were uploaded onto The

Guardians servers as images, which then could be structured in the form of

tagging. Yet tagging alone is inadequate to distillate a news story out of data.


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3.3 Visualising data

Mirko Lorenz, EJC-member and project leader of the Data Driven Journalism

initiative (DDJ), states that raw data needs to be transformed into something

meaningful. As a result the value to the public grows, especially when complex facts

are boiled down into a clear story that people can easily understand and

remember ( Data-driven Journalism 2010, 12). Illustration 1 shows besides

structuring or filtering the raw data, visualisations play an important role in

generating value as well.

Illustration 1: Data-driven journalism as a process.

According to mash-up artist Tony Hirst an important thing to remember about

data is that it can be used to tell stories, and that it may hide a great many patterns.

Some of these patterns are self-evident if the data is visualised appropriately

(Townend 2009). For data journalism visualisation is an important shackle in thechain of value creation.

An example of how raw data can be visualised and contribute to journalism is The

New York Times visualisation of President Obamas 2011 budget proposal and how

it is spent iii. The interactive squares on their website immediately show how the

Obama administration has planned to spend their budget and how each part of the

budget relates to other parts. Another example is a visualisation by David

McCandless for The Guardian, depicting the emergency budget proposal by British

Chancellor George Osborne iv . McCandless also did a visualisation of the data


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gathered from opinion polls during the general elections of 2010 in Britain v .

Another visualisation that has received a lot of attention is the so-called Homicide

Map by The LA Times, showing Los Angeles County homicide victims vi. The Google

Maps mash-up shows groups of homicides based on the number of homicides in an

area. When clicked on a specific homicide the reader is automatically referred to

the article in the LA Times reporting on the murder. Of course also the British MP

expenses are being visualised by The Guardian, offering a clear-cut overview of

what the newspaper has found so far. It is likely that The Guardian will do the same

when more data about the Sarah Palin emails trickles in.

The importance of visualisation within data journalism raises the question what

visualisation exactly is and what risks it brings along. Lev Manovich defines

information visualisation as a mapping between discrete data and a visualrepresentation (Manovich 2010, 2). He does, however, state that this definition

does not cover all aspects of information visualisation such as the distinctions

between static, dynamic (i.e. animated) and interactive visualization [sic] (ibid.).

While these differences are very important, I would like to follow Manovich in his

argument that the core idea of visualisation has not changed when we switched

from pencils to computers (Manovich 2010, 5). So whether the visualisation is

static or interactive, the core idea still evolves around mapping some properties of

the data into a visual representation (ibid.).

With the use of present-day software it is possible to generate visualisations of

much larger data sets than previously possible. As stated above, this does not mean

that at its core, visualisations have changed over the last three hundred years.

Manovich defines two key principles underlying commonplace information

visualisations: reduction and space. Reduction includes the use of graphical

primitives, such as points and lines, to reveal patterns and structures in the data.

The price being paid for this extreme schematization is the loss of %99 of what is

specific about each object to represent only %1 in the hope of revealing patterns

across this %1 of objects characteristics (Manovich 2010, 5-6). The use of spatial

variables, such as position, size and shape, is another core element typical for

information visualisation. These spatial variables have long been preferred over

other symbols such as color, tone and transparency.

Edward R. Tuftes book Visual Explanations (1997) reveals a case that exemplifies

how reduction and spatial preferences in visualisations can be problematic. The

case is about the cholera epidemic in London in 1854 and shows how the choice of

different intervals to display the data gathered by dr. John Snow give very different


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Eric R. Alberts12

representations of this data. If Snow would have chosen a different interval or had

not been so aware of the data and as thorough in his logical thinking he might have

never discovered the origin of the epidemic. This case also shows how popular

journalisms choice to aggregate or over-compress data can lead to misleading

graphical representations. In their article How Not To Lie With Visualisations

Bernice Rogowitz and Lloyd Treinish demonstrate how different representation of

a MRI scan of a human head can influence the interpretation of the data. They

argue that [i]n order to accurately represent the structure in the data, it is

important to understand the relationship between data structure and visual

representation (Rogowitz & Treinish 1995, 4). They conclude by stating that

although nowadays non-experts can create meaningful representation of their data

it is still not easy enough because the visual effects are not well understood by the

user (Rogowitz & Treinish 1995, 14).

Lev Manovich, however, emphasises that new visualisation techniques and projects

developed since the middle of the 1990s seem to no longer strictly take data that is

not visual and map it into a visual domain (Manovich 2010, 11). According to

Manovich the development of computers and the progress in their media capacities

has made it possible to visualise data without reduction: While graphical

reduction will continue to be used, this no longer [sic] the only possible method

(23). This new method of visualisation or direct visualisation can be exemplified

by the use of tag clouds. The tag cloud is an example of a reorganisation of data into

a new representation that preserves its original form: text remains text (12). A good

example of a tag cloud used in journalism is the word cloud by John Schwenkler, at

the time a graduate student in philosophy at the University of California, which got

published in The Boston Globe vii. The cloud revealed that the official weblog of

John McCain, the republican candidate for presidency, used the word Obama

more often than any other word. Even more than Obamas own official blog.

With the use of direct visualisation patterns in the data can be highlighted without

having to reduce or spatially arrange the data with the use of abstract graphical

elements. However, in the case of information visualisation, direct visualisation is

still not that common as in scientific, medical and geovisualisation. During the

1990s and 2000s the speed and processing power of personal computers

progressively increased, but still information visualisation remained to depend on

static vector graphics. Only very recently are sophisticated tools allowing for

interactive constructions of direct visualisation appearing. Manovich concludes

that the ability to show artefacts in full detail is crucial to humanities, as it helps


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the researcher to understand meaning and/or cause behind the pattern she may

observe, as well as discover additional patterns (23).

One can say that this ability is crucial to journalism as well. Visualisation is a key

element for revealing patterns in raw or structured data and making it

understandable for a large audience. For journalists and their employers it is, for

the sake of objectively informing their audience, crucial that these visualisations

display the actual facts. As Manovich has shown, however, information

visualisation is not the same as scientific visualisation and it has a long history of

reducing data to graphical primitives and specific spatial preference. Incorrect

visualisations, which give a distorted view of the actual data, could have large-scale

negative consequences. Direct visualisation, as introduced by Lev Manovich, seems

to offer a solution to this problem. Now it is possible to visualise large quantities of data without reduction and the software tools that make these direct visualisations

possible are rapidly dispersed across the Internet. For instance, ManyEyes,

Tableau, Yahoo Pipes, the University of Amsterdam, Open Calais, and of course

Google offer (free) tools for data visualisation, paving the road for objective data

journalism.

3.4 Storytelling with data

A large part of the EJC roundtable conference in Amsterdam focused on how to tell

stories with data. Surprisingly none of the speakers really questioned if data

necessarily needs to tell a story at all. Adrian Holovaty, a pioneer in data-driven

journalism with a background in both journalism and computer programming,

does question that, suggesting newspapers need to make an important shift and

stop the story-centric worldview (Holovaty 2006). Holovaty claims the daily

processes of journalists are, in practical terms, inefficient, wasting too much of the

powerful raw data at the root of the stories. Instead, news should be orientated

toward computers thereby hoping journalists and data will meet in the middle

(Kiss 2008). If so, structured data remains structured and no longer has to be

deconstructed for the purpose of writing a traditional news story. From his

experience as a journalist Holovaty knows that newspaper organisations

traditionally already collect lots of information, which is relentlessly structured. It

just takes somebody to start storing it in a structured format (ibid.).

Holovatys argument is best understood through the use of examples. For instance,

Faces of the Fallen is a public and searchable database of all the U.S. service

members who died in Operation Iraqi Freedom and Operation Enduring

Freedom viii

. Reporters at The Washington Post already were keeping a detailed


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Eric R. Alberts14

database of the deceased service members but this data was most of the time sitting

around unused. In two weeks time Holovaty and his co-workers built the data into

a powerful tool for the public and it was a catalyst for further reporting and used by

activist groups to protest against the war (Kiss 2008). Holovaty also created a

public and searchable database named Everyblock which made it possible to find

crimes committed in the city of Chicago ix. The data comes from CLEARMap, the

crime mapping website of the Chicago Police Department and includes information

on where and when each crime occurred, thereby again using available but unused

data.

Although Holovatys manifesto for computer orientated journalism has inspired

many, including the founder of Pulitzer Prize winning website Politifact x which

compares political statements with actual facts (Waite 2007), there are examples where news organisations use data more in the classical journalistic tradition.

Examples are the news stories based on the Afghanistan War Logs xi, which were

made available by independent organisation WikiLeaks to several news

organisations. Meanwhile the documents have all been structured and are available

through news organisation websites. The New York Times, however, primarily uses

this data to bring regular news stories. Reporters Cynthia OMurchu and Carola

Hoyos of The Financial Times seem to have stayed somewhat closer to Holovatys

view, as they produced several interactive graphics, including an interactive chart

on oil and gas chief executives and their salaries xii. In turn, the graphics serve as the

basis for traditional (follow-up) news stories. These examples show that there seem

to be different views among large news organisations when it comes to

implementing and using data. Holovaty-like data journalism is praised and

sometimes pursued, but also often questioned. Given the fact that Holovaty-like

examples are quite scarce it is fair to say data mainly stands in service of the news

story.

3.5 Participatory aspects of data journalism

Chapter 2 elaborated on the potential change of traditional news media-user

relationships under the process of convergence, the blurring of boundaries set by

the conditions of digitization. Whether this potential is called citizen, grassroots or

participatory journalism, it all boils down to the emergence of bottom-up initiatives

as counterweight to the large top-down news organisations. Comparison between

early writings on participatory journalism and its current status reveals that

participatory journalism should not be regarded as replacement of top-down news

organisations but rather as collaboration between these organisations and their

audiences. News organisations have learned and continue to learn to optimally


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utilise new media affordances and to tap into the desire of readers to be part of the

news making process. Data journalism can be considered as an outcome of this

utilisation and as a testing ground for further collaboration between news

organisations and consumers. In the specific case of data journalism citizens are

not replacing journalists but they are adding to the chain of value creation as they

canalise raw material, such as documents, videos or photos and help journalists

tackle the problem of structuring the vast amounts of data.

Crowdsourcing, a term coined by Jeff Howe in an article for Wired, is something

with which news organisation are increasingly experimenting and can best be

described as tapping into the latent talent of the crowd (Howe 2006) or using

the crowds as an investigative ancillary force (Howe 2009, xxiv). For instance, in

April of 2009 The New York Times release a press release in which it invited theirreaders to comb through the full schedules of Timothy F. Geithner when he was

president of the Federal Reserve Bank of New York xiii. Also, in February of that year

The Huffington Post called upon its readers to help dig through the U.S. Senate

stimulus bill xiv . Other prime examples are, again, the British politicians expenses

scandal and most recently the investigation of the Sarah Palin emails. In all of these

examples news organisations use the combined analytical strength of their

audience with the aim to generate stories out of large data sets. News organisations

use their audience for investigative work, to swift through piles of documentation.

The journalists role in this process is to collate and analyse the findings, making

the journalist the central point of direction.

As Alfred Hermida points out there are also examples of crowdsourcing without

central direction (Hermida 2010). One of these examples is the Kenian open source

platform Ushahidi xv , which was founded in 2008 by a group of bloggers who

wanted to give a response to the wave of ethnic violence sweeping the country in

the wake of elections (Buntling 2011). Ushahidis next project, Huduma (Swahili

for service), will use crowdsourcing in Kenya to monitor the effectiveness of

services such as health and education (ibid.). Hermida also refers to social network

Twitter allowing crowdsourcing to happen on a distributed, asynchronous

manner, with individuals acting independently yet collectively at the same time

(Hermida 2010). An example where the mass collaboration of total strangers on

the web (ibid.) worked was when multinational Trafigura legally banned The

Guardian from reporting on the alleged dumping of toxic waste off the shores of

Ivory Coast. Trafigura became a trending topic on Twitter as the topic was widely

discussed and in less than 24 hours Tragifura backed down (ibid.).


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Eric R. Alberts16

The latter example shows how crowdsourcing can be beneficial for journalism in

other ways than for investigative work but does not necessarily apply to data

journalism specifically. When looking at the given data-driven examples, audiences

are primarily used to contribute to information structuring. The Guardian does

however also outsource visualisation tasks. In a specially made group on photo

community Flickr, users can post graphical translations of large data sets, which

can be downloaded from The Guardians Datastore xvi. It remains the question,

though, if crowdsourcing data and data visualisations means data journalism is

intrinsically participatory. News organisations are increasingly implementing so-

called data desks to the work floor as extension to the editorial office. Eric Ulken, a

former reporter of The LA Times, published an article in which he describes the

process of assembling the data desk. According to Ulken the data desk can be seen

as a cross-functional team of journalists responsible for collecting, analysing andpresenting data online and in print (Ulken 2008). Furthermore, the report of the

EJC roundtable conference shows data journalism can profit greatly from applying

the know-how of graphic designers and IT-specialists ( Data-driven Journalism

2010). Adding multiple disciplines to the data desk may imply that participation of

the public in the process of creating news stories is just as likely to stagnate.

4 Conclusion

Questioning if data journalism in intrinsically participatory is one of many

questions still open for debate concerning a new form of journalism, which is

slowly taking form under continuously changing conditions set in a world that is

increasingly relying on technology and digital information. This paper has tried to

give context to this new phenomenon and has explored its core properties using a

variety of examples. At this point, however, it is too difficult to tell what the

implications of data journalism will be. The assumption that a website such as

Politifact, which checks U.S. politicians if their statements are based on facts, will

increase the publics trust in, say, journalism, politics or democracy, is yet to be

proven. For instance, the University of Michigan found in a series of research that

misinformed people, who were exposed to corrected facts in news stories, rarely

changed their minds. Political partisans particularly became even more strongly set

in their beliefs. Facts can make misinformation even stronger (Keohane 2010).

Instead of focussing on possible implications, this paper has tried to place data

journalism within a broader context and has tried to flesh out its core properties in

order to further comprehend this new phenomenon. The theoretical framework


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tells us that data journalism can be placed against the background of journalism

wherein traditional borders have continued to blur over the last decade. Set by the

conditions of digitization, readers have also become users that are able to add value

in the process of news making. This process is, however, a slow process and unlike

the ideas posed at the beginning of this century, participatory journalism has not

yet been able to crumble the power large news organisations. This does not mean

the voice of the public is not being heard. The dispersion of increasingly

sophisticated and free-to-use software and data sets enables people to contribute to

journalism in a new way. Top-down journalism is in some aspects meeting bottom-

up, grassroots journalism but it remains to be work in progress that often offers

more questions than answers.

Against the backdrop of convergence culture I have argued data journalism can beregarded as the outcome of the mutual shaping of technological and social

developments. Besides vertical top-down-meets-bottom-up, convergence is also

taking place on a horizontal axis, between the technological and social contexts of

journalism. Technological aspects are becoming inseparably intertwined with social

aspects, as reporters are coming to rely on databases as fertile soil for the creation

of news stories. In terms of Actor-Network-Theory these human and non-human

actants combine to form hybrid actors. In general the technologies, the data and

the software tools, are responsible for larger parts of the action chains, rendering

actions intrinsically hybrid. Data journalism can therefore be regarded as a hybrid

practice.

Exploration of the core properties of data journalism amplifies its relation with

data and shows the path journalists have to take in order to distillate a story out of

data. On the one hand structuring and visualising data can be crucial shackles in

getting from raw data to story. Sophisticated software tools make it easier than ever

to structure large quantities of data and to visualise data without reducing crucial

data. On the other hand these shackles are not part of a fixed chain or the only

road to deriving news stories from data. Moreover, journalist and computer

specialist Adrian Holovaty argues that nowadays making sense of complicated data

for an audience alone is just as important as telling a story.

Whatever path journalists will walk, whether it is through visualisations, telling

stories, crowdsourcing or building databases, it almost goes without say that the

future for journalism lies in analysing big data. This is a standpoint shared by Sir

Tim Berners-Lee, founder of the World Wide Web. According to Berners-Lee the

responsibility lies with journalists to hold governments, or any one else,


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Eric R. Alberts18

accountable, as information increasingly is made available on the Internet (Arthur

2010). How long it will take before the interdisciplinary data desk, with computer

specialists, graphic designers and journalists working together, becomes a full-

grown and respected part of the editorial office remains to be seen. Whatever the

implications will be, as databases keep on growing, culture and technology keeps

on converging and audiences keep on participating, there will be a role for data

journalism out there, somewhere.

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Examples of data journalism used in this paper

i The Guardian Crowdsourcing the Sarah Palin emails

.


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ii The Guardian British MP expenses

.

iiiThe New York Times Obamas budget and how it is spent

.

iv The Guardian - Emergency budget proposal 2010

.

v The Guardian General election opinion polls 2010

.

vi The LA Times The Homicide Report

.

vii The Boston Globe Portrait of the candidate as a pile of words

.

viii The Washington Post Faces of the fallen

.

ix Everyblock Make your block a better place

.

x Politifact Sorting out the truth in politics

.

xi The New York Times The Afghan war logs

.

xii The Financial Times Oil and gas chief executives

.


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xiii The New York Times The schedules of Timothy F. Geithner

.

xiv The Huffington Post The Senate stimulus bill

.

xv Ushahidi - information collection, visualization and interactive mapping .

xvi The Guardian Data store on Flickr

.

growing data, changing journalism

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