In July of 2007, J.K. Rowling published the final book of her Harry Potter series. It was amazing conclusion to a fantastic series, but it was also difficult for fans to come to terms with the fact that the series was now over. Four years later, Rowling brought new hope to her fans with the launch of Pottermore – an online database of her never-before-seen writing about characters, places and plots.
As Lev Manovich points out in The Language of New Media, databases are typically thought of as a radical departure from the narrative form, as they are searchable and arbitrarily organized. However, the original Pottermore site brought narrative form to the database by requiring users to move through a Hogwarts storyline to unlock database objects. For example, if you wanted to know more about where Rowling drew inspiration in creating Professor McGonagall, you had to attend transfiguration class and click on McGonagall rather than simply searching for her. To unlock further levels and progress through the site, you had to get sorted into a house and play flash games. This created a more stimulating user experience than simply clicking through a collection of wiki entries containing Rowling’s thoughts.
While many younger people found this organization of the site entertaining, adults often found the simple flash games a nuisance that stood between them and immersion in the real lifeblood of the Harry Potter universe, Rowling’s writing. As such, Pottermore has since been reorganized into a more traditional, wiki-style database, albeit a beautiful and extremely well designed database.
How do you listen to music? Back in the day, one could have either purchase cassettes and play the songs he/she wanted, or he/she could have given up the opportunity to choose and tuned to a radio station. The way people listen to music has changed tremendously throughout the years. However, some patterns remain even in today’s digital world. Consider a platform like Spotify. One can either purchase the premium plan and obtain access to any song from the database, or just choose to listen to songs that are of the similar genre as the desired one.
I have never closely paid attention to how the delivery of music has changed. Lev Manovich’s article, however, got me interested by pointing out the contrast between databases and narratives. Within the article Manovich pointed out the cultural transition to a world based on databases rather than narratives. The contrast between a radio station in the early 2000s and the free version of Spotify access, perfectly fits within Manovich’s claim. Instead of a radio station DJ playing songs that he/she likes and wants you to hear, you are now listening to songs that are chosen from a huge database by a computer algorithm. At first glance, both of these methods might sound the same, however there is an underlying difference. When a person chooses the song, he/she is affected by things like mood, personal experiences, and even the current weather. The computerized algorithm, however, bases its decisions on certain captured common trends and other previously collected data. Even though a listener might not notice much of a difference, the underlying world is constantly evolving.
Manovich offers an artistic definition of a database and a few specific applications of the data structure, but I want to discuss the fundamentals of the technology alongside very popular sources of databases and the ethical, and slightly nerdy, importance of databases — the qualities of which carry physical affects and digital applications that require computational care while sometimes perpetuating moral questions.
What is a database?
In its simplest form a database is a sequence of rows and columns whose rows correspond to elements or packets of information, be it a person, tweet, google search result, etc. and whose column corresponds to a piece of the information: name, author, date posted, etc.
One of the most popular forms of databases is an SQL database. (SQL = “Structured Query Language”) Wherein the data exists as a table with columns the user can sort, alter and make queries or selections/filters to to get information out.
Where do we encounter databases? In addition to video games, museums, and the generalized “Web” mentioned in Manovich’s work, there are a few increasingly popular examples of databases which have large impacts on the modern digital world.
Google: When we use the word ‘google’ we are simply referring to the interface used to access the database that the company Google has collected. “Spiders” or, as Google sometimes puts it, ‘web crawlers’ visit the entirety of the generally accessible ‘Internet’ and gather information which Google stores in their database. Users then query the data stored for information like articles, images, documents, webpages, etc. Google’s Search Algorithm holds similar structure to SQL databases is in its filtering and sorting of data by its diverse variables.
Facebook uses databases in its collection of human information. Which, of course, raises the digital-age old moral question: is it ethically sound to be collecting ‘personal’ data? That is, data from a vast group of people. The question stems less from the concept of the structure, as data is meant to be stored, and more from the extent and subject of the data that is being collected. See this previous blog post I made about the ethical dilemma of Facebook’s sometimes unsolicited collection of “private” data.*
Why are they important?
Beyond the artistic, cultural value that Manovich mentions, databases occupy physical space and computing power — something we’ve discussed in the past with cloud computing. Databases can easily be neglected as a computational ‘thing’ that collects data and exists purely in our digital ‘cloud’. Take google’s data center for example. There is no magical cloud that information floats across. It, instead, lies in the ones and zeroes of physical hard drives and memory devices that exist in factories sprinkled all across the world leading to real world impacts.
In the modern world this constant spread and collection of information has come to be a big part of our progress being made in the digital world today. The constant moral questions being asked, from Facebook’s collection of personal information to Trump’s proposed “database for muslims“, are all raising an equally important question of how, why, and for what should we use databases?
*Also, see this post for additional thoughts on data collection as a whole.
Wow this article was confusing. I may not have the prior knowledge to fully follow all of Manovich’s points, but one point that did stick was the one on video games. Highly academic of me I know. I Manovick has the beginnings of a decent argument when it comes to narrative masking the algorithm of games. He is correct that because of the story we often overlook how the game itself functions. This a true point and a bizarre point. It seems obvious that the narrative is suppose to take our primary attention. I don’t think that it takes away from the actual experience of the game itself at all.
I don’t really see his point in this section though as he more just states facts. Yes, there are different kinds of games, that is why we have created different genres for them. Manovich goes on about the differences between algorithms, narrative games and logic games, but doesn’t really say why. The differences seem fairly straightforward. To add onto that I think he actually simplifies games down too much to fit his groups. Plenty of games have little mini games built into them. One example is hacking in fallout 4. The hacking system is a very straightforward word creating game that would fit into Manovich’s algorithm category. But fallout as a whole is a very different style of game.
Manovich could’ve made the argument that we often overlook the important aspect of games themselves. He could’ve said that video games are not as free and expressive as we like to think they are. That in reality we are following these codes and simply tricking ourselves into thinking we have some sort of freedom through the context of the narrative. That is a perfectly valid point that he starts to make, but never fully says. Instead he jumps to the next topic. I understand he wasn’t focused on this per say but I felt like he did this in many other sections where he’d simply start a point and move onto the next without creating any closure.
If you’re anything like me, the experience of grocery shopping at Harris Teeter is akin to navigating a database. Harris Teeter’s aisles serve as categories (Produce, Dairy, International, etc.) that contain lists of items (parsley, eggs, salsa). Of course, I choose the order in which I engage with these categories (I usually go to Produce first, then make my way across the store—maybe this is my own algorithm of sorts), but my experience could hardly be construed as narrative. Manovich points out that an arbitrary linear sequence does not on its own constitute a narrative. So perhaps grocery stores appeal to database logic?
Manovich contends that the database is the key form of cultural expression of the computer age, eclipsing the narrative as articulated through literature and cinema. Because this is a blog post and the stakes are relatively low, I’d like to make an ambitious theoretical maneuver: perhaps the database is the favored form of cultural expression because it better coheres with neoliberal ideas of market and consumer.
Indeed, the “storage mania” that Manovich cites seems predicated on the idea of data as property; the accumulation of data is desirable, then, because it corresponds with the accumulation of capital. In this paradigm, narrative becomes undesirable insofar as it is a smaller container than a database. I admit that this assumption is tenuous: Are fewer data stored in a novel than in an encyclopedia? I don’t know.
Similarly, consumerism relies on paradigmatic ways of thinking and rejects syntagmatic ones. The paradigmatic generates consumer desire by underlying the accessibility of choice and infinite possibility. I can, for example, browse a dozen different online retailers (databases) to find the perfect pair of shoes. Because the syntagmatic emphasizes what is present, rather than alternate possibilities, it is less compatible with consumer ideals.
These are obviously some big ideas with a lot of assumptions that should be unpacked, but I think the connection between databases and market capitalism is worth exploring.
Databases and narratives are interesting to compare to each other because of how they differ, but also how similar they are. Let’s think about the ways in which they are similar to each other. Databases are made as an encyclopedia of different sources, whether it be pictures, words, letters, or anything that can be categorized. Meanwhile, narratives take the elements that are used in a database and makes sense out of them.
It’s comprehensible to seethe benefits of each of these categories of forms of literature (databases and narratives) Starting with the database, a list of items make up a database for no real reason at all except to inform the user base of an encyclopedia for example. In an English encyclopedia, one can find the meanings, etymologies, function, and pronunciation of a word. This is good for learning how to speak, read, and write in English. However one might want to see these words in context, and therefore can go to a narrative, which has those words used in sentences, and are used to drive a certain plot, which I and most other people think is more entertaining and intellectually stimulating than an encyclopedia.
However when thinking about these two categories of literature, we have to acknowledge that databases have ultimately come before narratives. In other words, before people could make rhetoric out of the words they were using, the words would have to have been made, which would have been written down in encyclopedias. Below I have a video posted comparing databases and narratives that could possibly further our conversation of this topic of the language of media.
I found the Manovich article very confusing, and I am not entirely sure that I correctly understood the point of the article. If I am correct, the main point is that interactions with media that used to be “narrative” or “story” based have now lost their narrative element due to the nature of databases and mass media.
Manovich uses the “antinarrative logic of the web” as one example, stating “If new elements are being added over time, the result is a collection, not a story. Indeed, how can one keep a coherent narrative or any other development trajectory through the material if it keeps changing?” (Manovich 2010). As a counter example to Manovich’s argument, simply look at the ancient Greek oral storytelling tradition. The Trojan War occurred around 1200 BCE, yet the Homerian epics were not written until the 700s BCE.
Prior to Homer, the story of the Trojan War was recounted solely through spoken word, with little additions and subtractions to the story occurring frequently. One can argue that the factuality of the story suffered from this, but to say that the Homerian epics did not “keep a coherent narrative or any other development trajectory” before Homer wrote them down would be a foolish claim. Narratives can maintain consistent storylines even with constant additions, meaning that websites can maintain a narrative feature in spite of their malleable nature.
I am not claiming that all websites are always consistent, indeed, the inclusion of The Undefeated on ESPN’s website marked a change in the direction of their narrative. But some websites remain unchanging, ever faithful to their story and their narrative.
Manovich, Lev. The Language of New Media. MIT Press, 2010.
My source of knowledge about the Trojan War is my Classics 280 course.
“The Database” by Lev Manovich left me wondering what it is I had just learned about. For me, the entire piece was confusing, probably due to my extremely limited understanding of databases and “new media” to begin with. But one thing that left me particularly confused was the relationship between databases and narratives.
Essentially, I understood that a database was a collection, while a narrative was a story. Manovich explains that “the database represents the world as a list of items, and it refuses to order this list. In contrast, a narrative creates a cause-and-effect trajectory of seemingly unordered items (events)” (pg 224). Because of these definitions, he says, databases are enemies with narratives. This dichotomy made sense to me.
That is until Manovich says that “regardless of whether new media objects present themselves as linear narratives, interactive narratives…they are all databases” (pg 228). How can a narrative be both a database and an enemy of a database?
The relationship became even more confusing when Manovich began discussing databases and narratives in terms of paradigms and syntagms. This description made it seem like the two things were very intertwined, and that one came out of the other’s existence. He says that “the database of choices from which narrative is constructed (the paradigm) is explicit, while the actual narrative (the syntagm) is explicit. New media reverse this relationship” (230).
To me, the author is trying to argue that narratives and databases are simultaneously opposites, symbiotic, and in competition. Is this what he actually meant, or am I missing the link between all of these relationships?
This image of a crocodile and a bird somewhat illustrates this confusion. It is a symbiotic relationship, but the two animals seem like they would actually be enemies. Is this what Manovich was trying to say?
The distinction between databases and algorithms in the digital world is often very defined — when we look at the music industry for example, we’re pretty much used to the first in its entirety. That wasn’t always the case.
I remember my first iPod Shuffle. The ability to listen to my music, on the go, and on my own device was an idea that mesmerized me. But I got a little greedy. I loved the iPod Shuffle, but its capabilities as a database were limited. I could load the songs I wanted, but those songs came up in a random order; I couldn’t listen to that “one song” unless I shuffled through the rest.
Fast forward almost 10 years, and we pretty much have everything we could ask for in terms of a music database. Now, for a relatively low monthly price, once can stream all the music desired from a giant online database — Spotify is an example. Again though, the power of this database seems to underwhelm after some time, and subsequently, we desire algorithms again.
We rely on the shuffle button to pick songs for us; the thing that used to be a burden is now an every day function that’s come to be desired. Not just that, but the music industry has created algorithms (like Pandora) that select new songs for us based on what we’ve listened to in the past. We no longer desire music as solely a giant collection of songs in which we have autonomy over what we hear; now, we want algorithms to make selections for us.
It’s odd to see this movement from a simple algorithm to a database and back to algorithms. Back when I had an iPod Shuffle, all I ever wanted was to choose my own song on the device; now, that’s something I take for granted.
There are bots that tweet random sentences, bots that report earthquakes, bots that report journalistically on congress, bots that spread false information, bots that encourage political transparency, bots that do nothing other than appear comically inhuman, and bots that perform so many other varied functions on the internet (particularly twitter). The article “How to Think About Bots” mentions several of these bot species, for lack of a better phrase, in its analysis of the bot infested social media world we now live in. Yet the article does not come up with a seemingly obvious conclusion. If the bot world is so complex and varied, shouldn’t we just deal with them on a case by case basis???
The authors state, “Platforms, governments and citizens must step in and consider the purpose, and future, of bot technology,” as if some legislature or rulebook could possibly cover all possible actions bots will make in the future (Wooley, Boyd, & Broussard 2016). The truth is, it is impossible to predict precisely what semi-autonomous bots will do, and this ambiguity makes any type of preemptive policy pointless. A better solution would simply mirror the steps taken towards the accounts of actual humans who tweet dangerous or libelous things.
If a real person tweets something incredibly offensive or blatantly false, Twitter can simply look at the tweet as a case by case event and delete the tweet. If the real person repeatedly tweets inappropriate material, Twitter can suspend the account. Why not follow the same steps towards bots? If a bot tweets something illegal, Twitter can delete it. If it keeps tweeting illegal things, Twitter can delete the account.
Wooley, Samuel, et al. “How to Think About Bots.” Motherboard, 23 Feb. 2016, motherboard.vice.com/en_us/article/qkzpdm/how-to-think-about-bots.