Author: georginanugentfolan

I’m just back from a few days in Liverpool, where I attended the “Ways of Being in a Digital Age” review conference at the University of Liverpool. This was the TCD working group’s first trip abroad for KPLEX dissemination, and my first ever trip to Liverpool.

UoL’s “Ways of Being in a Digital Age” was a a massive scoping review on how digital technology mediates our lives, and how technology and social change co-evolve and impact on each other. This conference came at the conclusion of the project, and invited participation in the form of papers that addressed any of the seven project domains: Citizenship and politics, Communities and identities, Communication and relationships, Health and wellbeing, Economy and sustainability, Data and representation, Governance and security. Naturally we hopped right into the “Data and Representation” category.

I was presenting a paper I co-wrote with Jennifer (Edmond, KPLEX’s PI) and, like most of my KPLEX activities thus far, I also used the platform as an opportunity to include as many funny data memes as I could reasonably fit into a 20 minute Powerpoint presentation. Which, by the way, is A LOT.

Our paper was titled “Digitising Cultural Complexity: Representing Rich Cultural Data in a Big Data environment” and in it we drew on many of the issues we’ve discussed thus far in the blog, such as data definitions, on the problems brought about by having so many different types of data, all classified using the same term (data), on data and surveillance, data and the humanities, and the “aura” of big data and how the possibilities of big data are manipulated and bumped up, so that it seems like an infallible “cure all,” when in fact it is anything but. And most importantly, on why complexity matters, and what happens when we allow alternative facts to take precedence over data.

The most exciting thing (from my perspective) was that we got to talk about some of our initial findings, findings based off of interviews I conducted with a group of computer scientists who very generously gave me their some of their time over the summer, and a more recent data mining project that is still underway, but that is producing some really exciting results. After all this desk research and talk about data over the last 9 months or so, the KPLEX team as a unit are in the midst of collecting data of our own, and that’s exciting. Below is a photo montage of my experience of the WOBDA conference, which mainly consists of all the different types of coffee I drank while there, along with some colossal pancakes I had for breakfast. I also acquired a new moniker, from the hipster barista in a very lovely coffee shop that I frequented twice during my two day stay. On the receipt, the note she wrote to find me was “Glasses lady.” 🙂

In 2003 James Frey, a twenty-something American and recovering alcoholic and drug addict, published his memoir A Million Little Pieces. The memoir recounts his experience of addiction and rehabilitation, often in brutalist and unsparingly graphic detail. Two scenes in particular have stayed with me to this day, one involving a trip to the dentist for un-anaesthetised root-canal treatment (the horror), the other something altogether worse involving a woman and the things people in the grips of an addiction will do for drugs.

In 2005 Frey hit the big-time and A Million Little Pieces was selected for the Holy-Grail of Book Clubs, Oprah’s Book Club, an act that virtually guaranteed massive sales. Not long after the book topped the New York Times’s best sellers list, as Oprah’s Book Club choices tend to do, and there it remained for some 15 weeks, selling close to four million copies. Not bad for a former addict, eh?

Except Frey wasn’t all he claimed to be. And his memoir wasn’t entirely factual. To give but one example. Instead of being in jail for a respectable 87 days, Frey was in jail for just a few hours. The Smoking Gun published an article titled “A Million Little Lies” that opened with the amusingly melodramatic statement “Oprah Winfrey’s been had” (gasp!) and proceeded with an article outlining how Frey’s book had circumvented the truth and taken Winfrey along for the ride:

Police reports, court records, interviews with law enforcement personnel, and other sources have put the lie to many key sections of Frey’s book. The 36-year-old author, these documents and interviews show, wholly fabricated or wildly embellished details of his purported criminal career, jail terms, and status as an outlaw “wanted in three states.”

In an odd reversal, Frey’s lack of jail time and status as a not-so-delinquent former delinquent led to outrage and culminated in a massively dramatic face-off with Winfrey that is referred to by Winfrey herself as among her most controversial interviews:

Oprah: James Frey is here and I have to say it is difficult for me to talk to you because I feel really duped. But more importantly, I feel that you betrayed millions of readers. I think it’s such a gift to have millions of people to read your work and that bothers me greatly. So now, as I sit here today I don’t know what is true and I don’t know what isn’t. So first of all, I wanted to start with The Smoking Gun report titled, “The Man Who Conned Oprah” and I want to know—were they right?

So Frey’s memoir was fictional, or if we are being very (very) generous, semi-autobiographical. He lied and blurred the lines between autobiography and real-life; using narrative to distort not only his personal data, but to distort the lives of others. It made for a pretty interesting (if graphic) novel, but this additional layer and awareness that, in addition to struggling with their own addictions, the figures in this novel (many of whom were now dead) had, on top of everything else, now been chewed up and spat out by Frey, was abhorrent. In particular I have always been repulsed by his crude appropriation and exploitation of the altogether dire narrative of a vulnerable female companion and love interest called Lilly, whose eventual suicide Frey “tweaks” both in terms of how and when it was enacted, presenting himself as a proto-saviour for Lilly, one who tragically arrives a few hours two late (this didn’t happen, Lilly’s suicide did not coincide with the day Frey arrived to “save her”).

What was marketed as a memoir narrative, that is to say a narrative wherein the data correlates with and can be backed up by real-world events, was in fact a fictional narrative, that is a narrative wherein the data is used to intimate real-world events. As Jesse Rosenthal points out in “Narrative Against Data” (2017), in these situations data is exploited to give the impression of truth or believability, and “the narrative relies for its coherence on our unexamined belief that a pre-existing series of events underlies it.” Frey’s manipulation of the rules of genre then, together with his exploitation of the co-dependence of data and narrative, was what was so unforgivable to Oprah and her readers. A Million Little Pieces would have been fine as fiction, but as a memoir, it was manipulative, rhetorical with the truth, and deeply exploitative. It was not the narrative that undid Frey’s web of manipulations, then, but the data that should have worked as their foundations, that should have been there to back his story up.

Frey’s hardly the first to do this. Philip Roth’s been skirting the lines that separate fiction and autobiography for decades. Dave Eggers’s 2000 work A Heartbreaking Work of Staggering Genius set the marker for contemporary US “good-guy” memoir-lit. More recently, Karl Ove Knausgård’s six-part “fictional” novel series provocatively titled My Struggle (in Norweigan: Min kamp) establishes the same tenuous, flirtatious relationship with the fictions and facts surrounding the life of its author. But while Knausgård’s work has certainly caused controversy in Sweden and his native Norway for the way it exposes the lives of his friends and family, this geographically localised controversy has served rather to fuel ongoing international interest and fascination with the novel series and its apparent real-life subject, Karl Ove himself, and his relentless mining of his autobiography to fuel these supposedly fictional narratives.

But the reaction to Frey’s twisting of the truth was altogether different. Why?

It seems you can alter facets of your memoirs if you label them as fictional to begin with (as Knausgård has done, an act that in itself is no doubt infuriating to the so-called “fictional” peoples exposed by his writings),  or if your modifications are relatively benign and done for stylistic reasons or dramatic effect (as Eggers has admitted to doing, and indeed as Barack Obama has done in his autobiographies).  But certain narratives, if declared truthful, must be verifiable by facts, evidence, and data. This extends beyond the realm of memoir and into present-day assertions of self. The intense push for President Trump to testify before Congress, for example, the implicit understanding (or hope, this is Trump after all) being that, much like in an autobiographical account of self, a narrative under oath must correlate to something tangible, to something real. It cannot simply turn out to be fictional scaffolding designed to dupe and distort the relationship between fact, fiction, narrative, and data.

We need to talk about data. And narrative. In fact, data and narrative need to talk to each other, work some issues out, attend relationship counselling, try to recapture that “spark,” that “special something” that kept bringing them together, that has made them, at times, seem inseparable, but also led to some pretty fiery clashes.

So, what’s the deal? What is the relationship between data and narrative? What role does narrative play in our use of data? What role does data play in our fashioning of narrative? How much of what we have to say about each is determined by pre-established notions we have about either one of these entities? Why did I instinctively opt, for example, while writing the previous two sentences, to refer to data as something that is “used” and narrative as something that is “fashioned”? And further still is it correct to refer to them as wholly distinct? Can we have a narrative that is bereft of data? And are data or datasets wholly bereft of narrative?

Data and narrative are presented by some as being irreconcilable or antithetical. Lev Manovich presents them as “natural enemies”[1] whereas Jesse Rosenthal, speaking in the context of the relationship between fictional narratives and data, observes how “the novel form itself is consistently adept at expressing the discomfort that data can produce: the uncertainty in the face of a central part of modern existence that seems to resist being brought forward into understanding.”[2] Todd Presner argues that data and narrative exist in a proto-antagonistic relationship wherein narrative begat data, and data begat narrative. I use antagonistic here in the sense of musculature, with the relationship between narrative and data being analogous to why you’re not able to flex your biceps and your triceps at the same time, because for one to flex, the other must relax or straighten.

Presner situates database and narrative as being at odds or somehow irreconcilable

because databases are not narratives […] they are formed from data (such as keywords) arranged in relational tables which can be queried, sorted, and viewed in relation to tables of other data. The relationships are foremost paradigmatic or associative relations […] since they involve rules that govern the selection or suitability of terms, rather than the syntagmatic, or combinatory elements, that give rise to narrative. Database queries are, by definition, algorithms to select data according to a set of parameters.[3]

So databases are not narratives, and while narratives can contain (or be built on data), they are not data-proper. This means there is a continual transference between data and narrative in either direction, a transference that is all the more explicit and controversial in the transition from an analogue to a digital environment. This transition, the extraction of data from narrative, or the injection of data into narrative, is a process that has significant ethical and epistemological implications:

The effect is to turn the narrative into data amenable to computational processing. Significantly, this process is exactly the opposite of what historians usually do, namely to create narratives from data by employing source material, evidence, and established facts into a narrative.[4]

Rosenthal also presents data and narrative as operating in this interrelated but tiered manner, with narrative being built on data, or data serving as the building blocks of narrative. And while Rosenthal focuses on fictional narratives, this is the case irrespective of whether the narrative in question is fictional or non-fictional because, after all, non-fictional narrative is still narrative.[5] Whereas Presner focuses on the complications surrounding the relationship between narrative and data in digital environments, Rosenthal’s engagement is more open to and acknowledging of the established and dynamic nature of the relationship between narrative and data in literature: “Narrative and data play off against each other, informing each other and broadening our understanding of each.”[6]

Data and narrative could be said to exist in a dynamic, dyadic relationship then. Indeed, Kathryn Hayles argues that data and narrative are symbiotic and should be seen as “natural symbionts.”[7] So their relationship is symbiotic, rather than antagonistic; they intermingle and their relationship is mutually beneficial, with data perhaps adding credence to narrative (fictional or otherwise) and narrative helping us understand data by making clear to us what the data is saying, or has the capacity to say (in the eyes of the person working with it). That said, if they are symbionts, what is the ratio of their intermingling? Is it possible for a narrative become data-heavy or data-saturated? Does this impede the narrative from being narrative?  Would a data-driven narrative read something along the lines of Data’s poem to his pet cat Spot from Star Trek The Next Generation (TNG) Season Six Episode Five:

Ode To Spot

Felis catus is your taxonomic nomenclature,

An endothermic quadruped, carnivorous by nature;

Your visual, olfactory, and auditory senses

Contribute to your hunting skills and natural defenses.

I find myself intrigued by your subvocal oscillations,

A singular development of cat communications

That obviates your basic hedonistic predilection

For a rhythmic stroking of your fur to demonstrate affection.

A tail is quite essential for your acrobatic talents;

You would not be so agile if you lacked its counterbalance.

And when not being utilized to aid in locomotion,

It often serves to illustrate the state of your emotion.

O Spot, the complex levels of behaviour you display

Connote a fairly well-developed cognitive array.

And though you are not sentient, Spot, and do not comprehend,

I nonetheless consider you a true and valued friend.

This “ode” is an example of a piece of writing so data-laden[8] that the momentum of the narrative is hampered, or rather the lyricism necessary to bring Data’s sweet ode to his cat into Shakespeare territory is seriously lacking. And what do I mean by lyricism? Well, the answer to that is relatively simple, just take a look at Shakespeare’s “Sonnet 18”:

Shall I compare thee to a summer’s day?

Thou art more lovely and more temperate.

Rough winds do shake the darling buds of May,

And summer’s lease hath all too short a date.

Sometime too hot the eye of heaven shines,

And often is his gold complexion dimmed;

And every fair from fair sometime declines,

By chance, or nature’s changing course, untrimmed;

But thy eternal summer shall not fade,

Nor lose possession of that fair thou ow’st,

Nor shall death brag thou wand’rest in his shade,

When in eternal lines to Time thou grow’st.

     So long as men can breathe, or eyes can see,

     So long lives this, and this gives life to thee.

In contrast to the Data-ode, and to the lyrical Shakespearian ode, would a narrative that is almost entirely bereft of data (and arguably also bereft of narrative, but let’s not go there) read something like a Trump rally speech?

A few days ago I called the fake news the enemy of the people. And they are. They are the enemy of the people.

(APPLAUSE)

Because they have no sources, they just make ’em up when there are none. I saw one story recently where they said, “Nine people have confirmed.” There’re no nine people. I don’t believe there was one or two people. Nine people.

And I said, “Give me a break.” Because I know the people, I know who they talk to. There were no nine people.

But they say “nine people.” And somebody reads it and they think, “Oh, nine people. They have nine sources.” They make up sources.

They’re very dishonest people. In fact, in covering my comments, the dishonest media did not explain that I called the fake news the enemy of the people. The fake news. They dropped off the word “fake.” And all of a sudden the story became the media is the enemy.

They take the word “fake” out. And now I’m saying, “Oh no, this is no good.” But that’s the way they are.

So I’m not against the media, I’m not against the press. I don’t mind bad stories if I deserve them.

And I tell ya, I love good stories, but we don’t go…

(LAUGHTER)

I don’t get too many of them.

But I am only against the fake news, media or press. Fake, fake. They have to leave that word.

I’m against the people that make up stories and make up sources.

They shouldn’t be allowed to use sources unless they use somebody’s name. Let their name be put out there. Let their name be put out.

(APPLAUSE)

“A source says that Donald Trump is a horrible, horrible human being.” Let ’em say it to my face.

(APPLAUSE)

Let there be no more sources.[9]

And now, by means of apology and for some brief respite, I offer you a meme of Data.

But are these our only options? Are narrative and data really at odds in this way? Is there a way to reconcile narrative and the database? Perhaps it is time to stop thinking of data and narrative as being at odds with each other; perhaps it is necessary to break down this dyad and facilitate better integration?

Traditionally, narrative driven criticism took the form of “retelling,” what Rosenthal calls an “artful,” or “opinionated reshaping” of the underlying evidence (aka the data) whereas more contemporaneous data driven criticism largely takes the form of visualisations that attempts to, as Rosenthal puts it, “let the data speak for itself, without mediation.”[10] This turn to the visual is driven by a hermeneutic belief akin to Ellen Gruber Garvey’s assertion that “Data will out.”[11] But this is something of a contradiction of terms considering elsewhere we are told (by Daniel Rosenberg) that data has a “pre-analytical, pre-factual status,”[12] that data is an entity “that resists analysis,”[13] but can also be “rhetorical,”[14] that “False data is data nonetheless”[15] and that “Data has no truth. Even today, when we speak about data, we make no assumptions about veracity.”[16] Borgman elaborates, stating that “Data are neither truth nor reality. They may be facts, sources of evidence, or principles of an argument that are used to assert truth or reality.”[17] That’s a lot of different data on data.

Fictional narratives can be built on supposedly reputable data, this helps the reader to suspend their disbelief and “believe in” the fictions they encounter within the narrative. Supposedly non-fictional narratives, such as presidential speeches, can be based on tenuously obtained, fabricated data, or can make reference to data that is not proffered, and may not even exist, rather like dressing a corgi up in a suit and asking it for a political manifesto.

What we’ve looked at today concerns the evolving discomfiture of our difficulties outlining the relationship between narrative and data. In the interplay between analogue and digital, different factions emerge regarding the relationship between data and narrative, with narrative and data variously presented as being anathematic, antagonistic, or symbiotic, with data presented as something one can be either “for” or “against” and with distinct preferences for one or the other (either narrative or data) being shown on a discipline specific, researcher specific, author specific level. At the same time, irrespective of which of these positions you adopt, it is clear that data and narrative are intricately linked and deeply necessary to each other. The question is then, how can one facilitate and elucidate the other best in a digital environment?

[1] Lev Manovich, The Language of New Media, 2002, 228.

[2] Jesse Rosenthal, “Introduction: ‘Narrative against Data,’” Genre 50, no. 1 (April 1, 2017): 2., doi:10.1215/00166928-3761312.

[3] Presner, in Fogu, Claudio, Kansteiner, Wulf, and Presner, Todd, Probing the Ethics of Holocaust Culture, History Unlimited (Cambridge: Harvard University Press, 2015), http://www.hup.harvard.edu/catalog.php?isbn=9780674970519.

[4] Presner, in ibid.

[5] “Yet the narrative relies for its coherence on our unexamined belief that a preexisting series of events underlies it. While data depends on a sense of irreducibility, narrative relies on a fiction that it is a retelling of something more objective. […] The coherence of the novel form, then, depends on making us believe that there is something more fundamental than narrative.” Rosenthal, “Introduction,” 2–3.

[6] Ibid., 4.

[7] N. Katherine Hayles, “Narrative and Database: Natural Symbionts,” PMLA 122, no. 5 (2007): 1603.

[8] And of course it’s data-laden, it was composed by Data, a Soong-type android, so basically a walking computer, albeit a mega-advanced one.

[9] “Transcript of President Trump’s CPAC Speech,” http://time.com/4682023/cpac-donald-trump-speech-transcript/

[10] Rosenthal, “Introduction,” 4.

[11] Ellen Gruber Garvey, “‘facts and FACTS:’ Abolitionists’ Database Innovations,” Gitelman, “Raw Data” Is an Oxymoron, 90.

[12] Rosenberg, “Data before the Fact,” in Gitelman, “Raw Data” is an Oxymoron, 18.

[13] Rosenthal, “Introduction,” 1.

[14] Rosenberg, “Data before the Fact,” in Gitelman, “Raw Data” Is an Oxymoron, 18.

[15] Rosenberg, “Data before the Fact,” in ibid.

[16] Rosenberg, “Data before the Fact,” in ibid., 37.

[17] Christine L. Borgman, “Big Data, Little Data, No Data,” MIT Press, 17, accessed April 7, 2017, https://mitpress.mit.edu/big-data-little-data-no-data. 

Ambiguity and uncertainty, cultural richness, idiosyncracy and subjectivity are par for the course when it comes to humanities research, but one mistake that can be made when we approach computational technologies that proffer access to greatly increased quanta of data, is to assume that these technologies are objective. They are not, and just like regular old fashioned analogue research, they are subject to subjectivities, prejudice, error, and can display or reflect the human prejudices of the user, the software technician, or the organisation responsible for designing the information architecture; for designing this supposedly “objective” machine or piece of software for everyday use by regular everyday humans.

In ‘Raw Data’ is an Oxymoron Daniel Rosenberg argues that data is rhetorical.[1] Christine Borgman elaborates on this stating that “Data are neither truth nor reality. They may be facts, sources of evidence, or principles of an argument that are used to assert truth or reality.”[2] But one person’s truth is, or can be, in certain cases, antithetical to another person’s reality. We saw an example of this in Trump aide Kellyanne Conway’s assertion that the Trump White House was offering “alternative facts” regarding the size of the crowd that attended Trump’s inauguration. Conway’s comments refer to the “alternative facts” offered by White House Press Secretary Sean Spicer, who performed an incredible feat of rhetorical manipulation (of data) by arguing that “this was the largest audience to ever witness an inauguration, period.”

While the phrase “alternative facts” may have been coined by Conway, it’s not necessarily that new as a concept;[3] at least not when it comes to data and how big data is, or can be, used and manipulated. So what exactly am I getting at? Large data can be manipulated and interpreted to reflect different users’ interpretations of “truth.” This means that data is vulnerable (in a sense). This is particularly applicable when it comes to the way we categorise data, and so it concerns the epistemological implications of architecture such as the “search” function, and the categories we decide best assist the user in translating the data into information, knowledge and the all-important wisdom (à la the “data, information, knowledge and wisdom” (DIKW) system). Johanna Drucker noted this back in 2011, and her observations are still being cited:

It is important to recognize that when we organize data into categories (according to population, gender, nation, etc.), these categories tend to be treated as if they were discrete and fixed, when in fact they are interpretive expressions (Drucker 2011).[4]

This correlates with Rosenberg’s idea of data as rhetorical, and also with Rita Raley’s argument that data is “performative.”[5] Like rhetoric and performance then, this means the material can be fashioned to reflect the intentions of the user, that it can be used to falsify truth, or to insist that perceived truths are in fact false; that news is “fake news.” Data provided the foundations for the arguments voiced by each side over the ratio of Trump inauguration attendees to Obama inauguration attendees, with each side insisting their interpretation of the data allowed them to present facts.

This is one of the major concerns surrounding big data research and Rosenthal uses it to draw a nice distinction between notions of falsity as they are presented in the sciences and the humanities respectively; with the first discipline maintaining a high awareness of what are referred to as  “false-positive results”[6] whereas in the humanities, so-called “false-positives” or theories that are later disproven or refuted (insofar as it is possible to disprove a theory in the humanities) are not discarded, but rather incorporated into the critical canon, becoming part of the bibliography of critical works on a given topic: “So while scientific truth is falsifiable, truth in the humanities never really cancels out what came before.”[7]

But perhaps a solution of sorts is to be found in the realm of the visual and the evolution of the visual (as opposed to the linguistic, which is vulnerable to rhetorical manipulations) as a medium through which we can attempt to study of data. Rosenthal argues that visual experiences of data representations trigger different cognitive responses:

When confronted with the visual instead of the linguistic, our thought somehow becomes more innocent, less tempered by experience. If data is, as Rosenberg suggests, a rhetorical function that marks the end of the chain of analysis, then in data-driven literary criticism the visualization allows us to engage with that irreducible element in a way that language would not. As Edward R. Tufte (2001, 14), a statistician and author on data visualization, puts it, in almost Heidegerrian language, ‘Graphics reveal data.’[8]

So “Graphics reveal data,” and it was to graphics that people turned in response to Conway and Spicer’s assertions regarding the “alternative facts” surrounding Trump’s inauguration crowd. Arguably, these graphics (below) express the counterargument to Conway and Spicer’s assertions in a more innately understandable way than any linguistic rebuttal, irrespective of how eloquent that rebuttal may be.

But things don’t end there (and it’s also important to remember that visualisations can themselves be manipulated). Faced with graphic “alternative-alternative facts” in the aftermath of both his own assertions and Conway’s defense of these assertions, Spicer countered the visual sparsity of the graphic image by retroactively clarifying that this “largest audience” assertion incorporated material external to the datasets used by the news media to compile their figures, taking in viewers on Youtube, Facebook, and those watching over the internet the world over. The “largest audience to ever witness an inauguration, period” is, apparently, “unquestionable,” and it was obtained by manipulating data.

[1] Daniel Rosenberg, “Data before the Fact,”’ Gitelman, “Raw Data” is an Oxymoron, 18.

[2] Borgman, “Big Data, Little Data, No Data,” 17.

[3] We can of course refer to Orwell’s 1984 and the “2+2=5” paradigm here.

[4] Karin van Es, Nicolàs López Coombs & Thomas Boeschoten, “Towards a Reflexive Digital Data Analysis” in Mirko Tobias Schäfer and Karin van Es, The Datafied Society. Studying Culture through Data, 176.

[5] Rita Raley, “Dataveillance and Countervailance” in Gitelman, “Raw Data” is an Oxymoron, 128.

[6] Rosenthal, “Introduction: Narrative Against Data in the Victorian Novel,” 6.

[7] Ibid., 7.

[8] Ibid., 5.