semantic web

Treaty of Greens: Generate this! (Reflections)

Treaty of Greens (generative poem)

Reflection 1

As a person who isn’t that into traditional poetry, I was less than enthused with an assignment that was labeled as “generative poetry.” In traditional poetry, I typically pick a specific subject or mood and run with that, so I did the same approach with this assignment. At the beginning of this assignment, I was in the process of writing a theorized letter to my CEO (at Walgreens), where I argued the lack of love for cashiers. I was feeling pretty passionate about my job, so that’s how I stumbled upon Walgreens as my subject matter. I planned on creating a poem that showed the virtues and triumphs of cashiers, until I had a terrible day at work. My goal evolved into showing the “dark side” of Walgreens.

The word choice part was pretty easy, at least in comparison to traditional poetry. I decided to have one group of words that portrayed more to my job title, and another category of words that portrayed to the customer. I decided to capitalize words that would show anger or aggression, or other words that could relate to such a subject. For example, I capitalized ASSHOLES because that’s typically something cashiers scream in their head at rude customers. In a different light, I capitalized PATIENCE because it’s something most customers seem to lack. I think by capitalizing certain words this emphasizes certain points in the poem, which seems to add a nice touch. Furthermore, this creates contrast. The verbs were a little bit more difficult to come up with, for some reason I cannot explain. I think part of it is because I was trying too hard to think of unique verbs. I felt that most of the verbs I managed to scrounge up were rather boring and didn’t paint a picture, but I wanted the verbs to relate to Walgreens. I did manage to get a few odd verbs in there as “engulf”, “defecates”, and “delegate”. These are still loosely tied to the job of a cashier, especially at my store, and I think it really puts a twist on the generative poem.

As mentioned previously, I wasn’t crazy about traditional poetry before this, so I wasn’t too excited for this assignment. While I didn’t love this assignment, I did enjoy that I could essentially have a computer create a poem for me, only each time it would magnificently different than the previous time. This poem definitely challenged me to rethink how poetry is composed in general. By creating poetry in this way, through code, it really changed what poetry can be. It helped me see that poetry, whether through code or traditional, follows some type of pattern with words. However, the generative poetry really expands poetry. Instead of having a traditional sentence, that most people would write, generative poetry can create these crazy, enlightening sentences that one would never think of creating. It’s this aspect that has challenged me to really rethink poetry; maybe I didn’t like traditional poetry because of all of the constraints and limitations. This generative poem has helped me see that anything can be poetry; I don’t need to conform to certain poetry idealism’s in order to create a great poem. Furthermore, this assignment has helped me to start to consider that code itself is poetry; it follows a certain pattern, adheres to certain rules, and creates meaning in something.

Reflection 2:

There are many people in society today who don’t believe that this very assignment on generative poetry is not a true form of literature; we could even argue that there is one of those nonbelievers among our graduate course (cough Jason cough). It’s understandable for most readers to first assume that generative poetry is unlike traditional poetry and literature in general, but after studying it and learning the essence behind codes, it can be argued that there really is no difference at all.

In Perspectives on Ergodic Literature Espen Aarseth (1997) argues that cyber text focuses on the “mechanical organization of the text, by posting the intricacies of the medium as an integral part of the literary exchange,” (p. 1). In simpler terms, the computer is not just the medium, it’s part of the text too.  Aarseth further argues that cyber text is no different from other texts because all literature is different for every reader, the reader has to make choices in order to make sense of the text, and a text can only be read in one sequence at a time (p. 2) All three of these standards apply to both the generative poem assignment, as well as traditional poetry or literature in general.

Generative poetry and electronic literature challenges traditional text, but that doesn’t mean that the newly invented literatures don’t qualify as literature. Aarseth writes that “text is something more than just marks upon a surface,” (p. 12), meaning that text is something that creates meaning and allows for the flow and exchange of ideas. In The Semantic Web Revisited, Nigel Shadbolt, Wendy Hall, and Tim Berners-Lee (2006) claim that the Web consists of “documents for humans to read to one that included data and information for computers to manipulate,” (p. 96).  Even if computers are manipulating the text, much like in the generative poem, meaning is still being made by the reader, or even, humans. And then, the same argument occurs: there is a difference between paper and computer texts. But what is the difference? Aarseth argues that “the real difference between paper texts and computer texts is not very clear,” (p. 10) and it is true; other than the medium, what is the difference?  There are obvious subtle differences, like computers run on electric and the words are coded to appear on a screen, but the argument is that this code is literature too. How? Code uses a certain language and follows a pattern in order to create something meaningful to the reader. Codes can change the color of a text or background, among millions of other things. In comparison, the human hand and mind can write poetry with a certain rhythm that displays different emotions. The medium is still literature.

Since we can consider generative poetry as a type of literature with the evidence presented, we must consider what this means for the composition and structure. Aarseth writes that cyber text “centers attention on the consumer, or the user, of the text,” (p. 1), which changes the way that we compose. Instead of composing a poem for a traditional reader, we must begin to consider other options. For example, readers can be users or even co-authors. We must write in such a way that can account for that; the text must be more interactive to allow for the co-authorship. However, this poses a bit of a threat for the “reader”. Aarseth argues that the cyber text reader “is not safe” which means we can argue that “they are not a reader,” (p. 3). Most books are predictable and allow for full control, but with these newly developed ways of writing, more risks are available for the reader. The reader can fail at understanding how to navigate through the text which leads to a lack of understanding.

Understanding then, is linked to interpretation. But not interpretation as we know it. In “What does it mean to ‘interpret’ code,” a blogger writes that interpretation is no longer what it used to be; it’s not that “search for what the author secretly meant,” but rather it is the exploration of “semiotic objects in order to explore culture and systems of meaning.” This definition changes how we view literature; it’s not about that problem or climax, it’s about the meaning behind the text, and the interaction the text has with the medium to create that meaning. Just as words work together on a page to create a narrative, or within a Haiku to show imagery and emotion, words work behind the screens of a screen with code and the computer to create meaning.

Resources:

Aarseth, E. (1997). Introduction: Ergodic literature. In Cybertext: Perspectives on Ergodic            Literature. Baltimore, MD: Johns Hopkins University Press. Retrieved from            http://cv.uoc.edu/~04_999_01_u07/aarseth1.html.

Berners-Lee, T., Hall, W., Shadbolt, N., (2006). The semantic web revisited.

What does it mean to ‘interpret’ code? (n.d.) Critical Cod Studies.

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Categories: Alphabetic Text Analysis, class activities, elit, ergodic literature, evidence, generative poem, images, information architecture, mapping, semantic web, technology | Tags: , , , , , , , , , | Leave a comment

#iamondays How to Write E-Lit

On Twitter, Devon posted this:

blogpost4a

Which is a link that leads us to this:blogpost4

The “Fun da mentals” of e-lit. A very old image to teach us how to do something new. When I first saw this picture, I was immediately reminded of Robinson and his book The Story of Writing, and for some reason, the fossils reminded me of the section about “rebuses”. And with good reason, I think. These fossils are rebuses, and they relate to e-lit because most often, e-lit uses pictorial images. It’s crazy to think that we are still using techniques from the middle ages. But then again, everything we know has developed from something in the past. For example, the computer, and it’s many components (such as the internet, hypertext, and cyber text).

Hypertext is e-lit. But first, let’s look at the actual structure of this page that Devon posted. In my own opinion, it’s quite simplistic and bare. In fact, it even seems to resemble a piece of paper, which still shows that we’re relating how we write today to how we once used to write. However, the website seems to do a nice job of incorporating grids, as we learned about from Lupton. If we just browse at the first page, there is a cornucopia of blue. Blue, of course, is hypertext.  As Nelson wrote, hypertext means “forms of writing which branch or perform on request,”; in other words, any of the blue links that we see daily.

But how do these links happen? How can you possible think of making all of the connections? There are ways, tutorials, and even webpages that will do it for you, so it’s really not a question of how. It’s actually, more of a why. But the why is in the purpose of this blog post: electronic literature.

Now then, first we must learn to understand electronic literature. It’s unlike traditional literature, it’s not bound by specific outcomes and there’s no specific beginning or ending. So how can we learn about it with the idea of traditional reading and writing lodged in our noggins? With practice and coherence, it can be done.

Fun da mentals actually offers some interactive ways to learn and become familiar with electronic literature, which is something that Nelson writes is a good thing. There is a “hornbook” which helps students begin to understand how to read electronic literature. The hornbook teaches about nodes and paths, but also provides exercises that allow the students to get involved. By clicking on the “reader” section we can learn how electronic literature let’s us explore it. This section is headlined by “This sentence is false” and then teaches how different nodes (clickable parts of a sentence) can develop different stories or ideas, much like in The Jews Daughter.

The most interesting part of Fun da Mentals is the “Coloring book” link. As the only way to learn how to color is by practicing, at some point you learn that you’re doing it right when you color inside the lines. Students learn about creating electronic literature by doing similar exercises to that of a coloring book. It involves navigation by clicking.

Speaking of navigation by clicking, the Fun da Mentals is almost an example of  e-literature. Yes, it’s obvious that the page is full of hypertext, but what makes e-lit is that the reader is in control. He or she can click around and expand the story on their own. For instance, once I begin reading the description of “the coloring book” I see that the word “anatomy” is a link, in which I click it. It takes me to the anatomy interactive portal, which is not directly related to what I was just focusing on. In this same description, there is a clickable word that says “electronic tool”. I am compelled to find out what an electronic tool is, so I click on it. I read about electronic tools. However, here is where there’s an issue: Each page that I’ve clicked on, they’ve offered other links, but none of them seem to take me back to the original story line. Therefore, we could argue that this is not electronic literature.

Electronic literature can be complex, especially when we’ve grown up and only been exposed to one type of literature (traditional). It takes time and practice to learn a new trade. As Fun da Mentals is attempted to do, it’s important to constantly practice and enrich yourself into what you’re trying to learn in order to better adapt.

Categories: #IAMondays, Alphabetic Text Analysis, class activities, evidence, images, information architecture, mapping, pictorial images, semantic web, technology | Tags: , , , , , , , , , | 3 Comments

It’s time to transform with creative thinking

You’re currently reading words that are floating around on cyberspace. You’re not viewed as a reader, but as Aerseth writes, you are on your own adventure, taking risks. So, while we’re taking risks and exploring, Nelson mentions that most of us don’t actually understand the computer.  At first I thought that this meant we don’t understand how computers work, or even, how to operate computers and I expected to read something like a computer manual. Don’t get me wrong, Computer Lib / Dream Machine is certainly a manual of some type, but not the traditional manual.

Everything we’ve been reading and learning about recently has been quite the opposite of the traditional things we’re used to. I even though about writing this blog post in a different way, against the grain, but I had no idea where to even start; we must take baby steps. As Nelson argues, we learn most things by beginning with “vague impressions” (p. 303).  The first step in understanding the computer is to learn that it is a media that provokes emotions and helps us write, think, and show (Nelson, p. 306).

Now, the key word is help. It’s not the writer itself, nor it solely just the delivery method. For example, in Taroka Gorge (and the others too), a real human being came up with the basic structure: the main idea and the words. The computer put together the form and structure: how the words appeared to the audience. In the poems we read, there’s a feedback loop that keeps using the same words and creating different outcomes. I’m going to attempt to do so myself, but I have a hunch it’s much easier when a computer does it.

Roscoe retaliates to grab my banana whole heartedly.

My banana retaliates.

Roscoe grabs.

My whole banana.

My heartedly banana grabs Roscoe.

I think you get the point. Something that took me a few minutes to do would take a computer seconds to do. So in essence, it can be argued that computers essentially think for us, but not without the correct input.

But how do we learn what the correct input is? Well, as Nelson shows from the article,  “No more teachers’ dirty looks”, it’s beginning next to impossible to teach. Schools are focusing so much on standardized this and standardized that, that creativity is thrown out the window. Surely this is displayed in any type of creative situation, but especially in computers. How can the youth of the future learn how to be creative when computer classes are tailored to very specific tasks and are very standardized?  Furthermore, it can be said that the education system is behind in change. Literature teachers are teaching poems from a long history ago, yet they seem to glide over the current period of poems: e-lit at its finest.

Last week, we struggled, or at least I struggled, to understand the electronic literature we were required to read. We learned that it was difficult for us to tailor our traditional style of reading because it was all that we had known. If schools spend time teaching electronic literature, alongside traditional literature, students would become accustomed and be better able to code switch from one to the other.  As Nelson argues, “students should develop through practice, abilities to think,  argue, and disagree intelligently (p. 310).  But instead of this, students spend countless hours learning about topics that bore them to tears. One that I can recall, from both high school and community college, is the basic computer class that teaches you how to use Microsoft programs. Why is that a real class? And even more, it strictly taught and tailored the projects we would do. The whole class had to create an excel spread sheet from the same baseball statistics. How boring and inconclusive. And even more, these classes started the rave for PowerPoint, and we all know how Tufte feels about PowerPoint (which I think goes for all of us as well). I think it’s time the school systems caught up to the technology that is vastly developing.

The question about all of this, which Nelson asked as well ,is how will we use these creations? (p. 117). This is something that could truly be in our hands, yet it might also slip away if not treated carefully. School systems, and society, need to recognize these new ways of writing and creative thinking as a real possibility, and they need to begin to educate on them.  The time for transformation is now.

Categories: class activities, images, information architecture, mapping, semantic web, technology, Uncategorized | Tags: , , , , , | 4 Comments

Tweetping and the Semantic Web

Recently, recurring birthday girl Devon tweeted about  Tweetping, a website tracking world-wide tweet counts. Tweetping may be the first step to realizing a Semantic Web. The term, developed in the 1960s, describes a web network that enables machine-read metadata to recognize relationships between webpages and web searches and attempts to establish these links in order for users more accurately and conveniently access the web.

I’ve had tweetping open for maybe ten minutes now and I’ve watched the number of tweets rise exponentially. What the site does-recording tweets by characters used, by hashtag (by another word, folksonomies-organically developed content retrieval tags instigated by small groups or individuals , words, mentions, place of origin, is the beginning of the Semantic Web. These ontologies -a set of data within a domain (of discourse)-touch at the possibilities of a Semantic Web.

The computer/algorithm is tracking data, but to be part of the Semantic Web, data needs to be relatable. Tweetping may track hashtags and @mentions, but offers no way of viewing the amount of times any given hashtag was used, or who/where/when the hashtag was used. In Semantic Web terms, this is provenance. Provenance is an important aspect of the Semantic Web because it can show what information is available to different areas of the globe, the density of information/technology availability (Africa has noticeably fewer tweets than other inhabited areas), and how inhabitants in the area feel about the information.  Archiving is an important function in the Semantic Web, as it is through archiving that metadata relationships can be recognized.

Moving towards a Semantic Web changes conceptions of websites and what counts as data. Twitter is an ideal example, as the social media platform is often derided for user’s tweets being thin-largely irrelevant posts (i.e. “oh snap”). But authors Tim Berners-Lee, Nigel Shadbolt and Wendy hall would argue that twitter is a a great example for Semantic Web development-given the websites tendency towards shared conceptionualization and peer-to-peer protocols. Twitter has changed how information is recorded, communicated, and archived. Twitter users have the ability to list information via topic, or group information in any way they want to. These lists can also be shared, altered, etc.

While tweetping is an imperfect example of the Semantic Web, it is a step in the right direction. However, it can easily be adapted. It would not take much to expand Tweetping to track tweet posts by topic, area, etc. As stands, it is an interesting look at how machine-and not humans-track data. It also stands as an interesting contribution to web science, a science that seeks to develop an understanding of how information systems (both human and machine) operate on a global scale.

Tweetping offers an interesting look a global data trends-though again, only through seeing repeated hashtags in this version. As users of the Semantic Web, we must be aware that we are not just tweeting, not just blogging, not just idly surfing the web. We are contributing to the global information database.

Categories: #IAMondays, information architecture, mapping, semantic web, twitter | Tags: | 2 Comments

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