Digital Humanities 510

The merge of data and literature is definitely a funky concept. I think that finding the data out of a large text although interesting can be at times very confusing. If you are not someone who is really intently looking for something in particular you are more taking in the information grasping at whatever reasoning you can to understand what is going on. These visualization tools help us to pick up things we wouldn't necessarily find if it were just close reading we were doing. For example, we can find common trends, ideas, word choice, and tone in a reader through these tools. It helps us to better understand an author and their "type" of writing. Thanks to data texts we are able to find traditional literary texts within sites that we can use to determine and examine through distant reading. It can help us to discover if the type of book they have written is comedy or drama, and it can tell us their consistency in word choice. It is helpful because a lot of the time th

       After reading chapters 6 and 7, visualization is a graphic that corresponds with the data being associated with it. It allows for people to interpret large amounts of data, without being lost in so many numbers or facts. In digital humanities projects, many home pages are extremely long with so much text. That makes it hard for the general public to sit and read it fully through and analyze it. Adding a visualization can make the article intriguing and desirable to keep reading.      Data mining and text analysis "is used for analysis of literary and aesthetic objects has promoted many immediate and strong responses, such as the claim that 'literature is not data"(Lamarche 2012). I always thought that literature and humanities could not be data as well. I realized after reading this chapter, that data mining is analysis that looks at patterns and extracts information in digital files. That mean it filters information not in a number form.      In the digital projec

In Chapter 6 of The Digital Humanities Coursebook , the concept of information (data) visualization was introduced and subsequently expanded upon. In the most simple of terms, data visualization is the way that project creators are able to portray their findings in some form of visual form, such a chart, graph or image. Johanna Drucker describes data visualization as the following: "The visualizations are often more easily consumed than the complex research data on which they depend... Anything that can be quantified (given a numerical value) can be turned into a graph, chart, diagram, or other visualization" (Drucker 86). Graphs and the plotting of data has been engrained into educational systems for decades, and so the concept itself is not new. However, the usage of visualized data allows a larger group of people to view chunks of data, as many people may be unable to understand or see the meaning behind the data at its initial value. Yesterday, Today, and Tomorrow does a

  I love the idea of being able to interpret data easier by visualizations. As we all have learned so far data is an endless wonder of information and that can get confusing. Chapter six discussed different forms of visualisation data like graphs, charts and diagrams. It also discusses the different important variables that graphics need to be interpreted correctly/easier like ize generally indicates quantity, but can signal importance, particularly with typography. Color, like shape, is very legible and makes distinctions highly visible, as does texture"(Drucker 98).  Speaking of interpreting data more easily, another thing aI learned about was data mining. In chapter seven, it talks about how data mining can be helpful when recognising large amount of data. It did however specify that " Data mining only takes place on the information literally in the file, so clarification about the process is essential" (Drucker 110) which makes sense with how big and complex we know

 While reading chapters six and seven in the  Digital Humanities Coursebook  I was able to learn what data visualization is along with data mining. First off, I found out what the two terms mean. Data visualization is information that is portrayed through various charts, graphs, and images (Drucker). Chapter seven focused on data mining. I understood data mining to be a way to comb through an abundant amount of data in a relatively fast way. Data mining is relevant in humanities because “It has become a part of research methods in text, music, sound recording, images, and multimodal communications studies with tools customized for this purpose” this allows data mining to become a positive tool for digital humanities research (Drucker 110). These two new terms broadened my definition of digital humanities yet again.        When I was looking at Yesterday, Today, and Tomorrow I was able to see data mining in action. I saw data mining in this project due to the way that the tweets were or

 In reading chapters 6 & 7 of The Digital Humanities Coursebook , I was able to extract new information to further expand my knowledge (thus simultaneously losing myself further in the abyss of all digital humanities can be), particularly concerning the topics of data visualization and mining. In terms of data visualization, I found the name itself to be fairly self-explanatory, however the details in its construction and representation provided a lot of information I didn't know. For example, I learned that there are two components to visualization: metrics and graphics. Through these components, information and data can be represented in numerous ways, and a choice between which visual representation to use can be made to best aid readability and consumption of the data. It is also noted in the text that one of the best ways to decide what kind of visual to use is to decipher whether the data is discrete or continuous. Before reading chapter 6, I had a rough idea of the benef

 Data visualization is taking different points of information and placing them into an organized chart or graph. What that format looks like depends on the designer's intention. Some graphs, for instance, utilize a continuous graph to show a change in variable over time. Other graphs might use pie chart to display data with percentages. How the data is presented makes a difference in the way it is interpreted. In some cases, certain graphs can exaggerate information, such as Florence Nightingale's hospital chart, that dramatized the radius of operations. In other cases, data visualization can be ineffective or uncomprehendable due to poor graph choices or point display.  In Six Degrees of Francis Bacon, the map demonstrates a spiderweb of first and second degree connections. Meanwhile, Yesterday, Today, and Tomorrow, used similar format of Tweet concentrated bubbles. These provide great examples different ways to map data. They also show how data mining can be used. Data mining

Chapters 6 and 7 taught me a lot of new things in terms of data mining and visualization. To begin, data visualization is putting a given set of data into a graph. They help to see patterns that are happening through different types of graphs such as; bar, line, bubble, and pie charts. The important part about data visualization is how you choose to express it, as said in the text "The challenge is to understand how the information visualization creates an argument and then make use of the graphical format whose features serve your purpose" (90). The key thing to note when it comes to rhetorical graphs is questioning the creator of the content as sometimes it can be deceptive. I also learned about networks and the complexion and how it "is that the development of the system cannot be predicted-- because the processes are nonlinear and/or non-deterministic from a statistical standpoint.  Data Mining as defined in the book "is an automated analysis that looks for patt

Metadata is a system of organization on a digital site. It allows for the site to be easy to access data and materials. It has titles and subpages so people can find what they are looking for. It designs titles, size, and formate of files. The biggest thing that stood out to me was how it specifies and organize so much information. The chapter used the example of a digital library a lot to help the readers understand how many different forms or sources are categorized.  Database is the organization of numbers. Spreadsheets and tools are used to make sure the site works properly. To what I understand, a database is what makes everything work. Digit humanities needs metadata to have a site work and be presentable to everyone. Databases also make sure there is a source to begin with. Both work cohesively so the information and resources can be seen. It is relevant to my project because the Vogue website has many subpages and is very visually appealing. There are many graphs used along wit

 After reading Chapters 4 and 5 of the textbook I learned the meaning of metadata and I got to better understand what it is. At the beginning of the chapter, it says "Think of metadata as the information about a resource or digital asset" (Drucker, 52) What this tells me is this all the information behind a file, all the very precise details behind it is what metadata contains. Metadata is part of every type of resource too, it isn't just the information behind one specific type of file. The only documents that do not need metadata besides books and bibliographies. Metadata connects the information of something with a description of sorts to be able to better understand and analyze it. Once again, metadata is very much crucial for humans to be able to find and use.  Metadata is essential to my research project because my whole website is a database of different information from books. Without metadata on my website, there would be absolutely no way of finding these docume

 From my understanding in my reading of chapters 4 and 5 from The Digital Humanities Coursebook, metadata can take many different forms, being descriptive, administrative, and operational. To quote the book, "...metadata is information used to describe data, objects, or records" (Drucker, 53). Alternatively, the text also provided me with my own understanding of databases, which are essentially a means of managing data (i.e. in a table or a spreadsheet). This management aids in keeping information more "consistent and error-free" (Drucker, 71). Databases specifically are designed in many different formats to collect and manage content in the most effective manner for the data at hand. In terms of where they fit into my own ever-evolving understanding of Digital Humanities, metadata provides context to the organization and formatting of information in DH, whereas databases provide background as to how the data is managed in the first place, which leads to the develop

I n the previous unit of the  Digital Humanities Coursebook , I felt extremely comfortable with the concept and depth of data, due to my previous knowledge and experience with what data is. During the metadata unit, I was significantly less comfortable and accustomed to what it is.  The textbook provided a great, but lengthy, description of what metadata is, saying, " Metadata performs many functions. Most often, as in the example of 'Get Info' just given, it is descriptive . Metadata can also be administrative , help- ing to organize the data in large sets of records. In addition, it can be operational , giving data a role or task, such as the relation of one file to another...  To reiterate, metadata is information used to describe data, objects, or records. Metadata can be attached to objects or records, but it also stands in as a surrogate " (Drucker 52, 53.) Metadata is essentially data about the data, providing as much description about the data as possible. Met

After reading chapters four and five I was able to learn more about metadata and databases. The definition of metadata in the book is defined as "Metadata is used to classify, describe, organize, and connect records to artifacts and documents to each other" (Drucker 60). I understand metadata as an info center that organizes all the information and presents it to you. I believe that metadata and databases go hand and hand with each other. Databases are also a collection of data that can be found online. A specific example in the book that helped me understand databases more was the example of a spreadsheet. Databases and metadata add onto my understanding of digital humanities due to these two being able to store the data that makes up digital humanities. Without these two collections of data we would not be able to easily access information in an organized way.  I believe that metadata is relevant to the current website I am analyzing. The website I am analyzing contains dif

  After reading chapters four and five in our digital humanities textbook, I learned that metadata is basically just specified data. It tells you specific information on different digital characters such as the format and size of the file you are looking at/ working with. It's interesting on the broad range that it covers from being simply stated to a deeper dive of a description of the file. It reminds me of how broad digital humanities are. Speaking of, metadata fits into the digital humanities because digital humanities are made up of digital data, and the text book makes a good point about metadata and data. It said, "Without metadata, information in files would be like books without covers or title pages on shelves without labels." (Drucker 53). This really is the part that made clear and started to break down what metadata actually is to me.  Metadata is important to my website analysis project because my website basically is a storage site for digital works/project

Just when I thought I had a handle on data, I was introduced to metadata. To say it was complex was an understatement. Essentially data upon data, metadata ranges from a sample of information to broad, complex topics. It encompasses a variety of information and details, regarding who, what, when, and how data was developed. Personally, I thought it was interesting to see just how discussion revolves around terms in metadata. For instance, the point about different terms being used for ‘creator’, and ‘author’ was very interesting to think about. It definitely makes it clear why the topic is so detailed.   It was also interesting to see how database designs are constructed. There is a lot of detail that goes into database development, and even the simpler forms require some effort. Since the creation of a database involves multiple factors, such as security, it means that a lot of tasks in its production result in various individuals or teams contributing to it. It also takes a lot of ti

       Before reading chapters 2 and 3, I thought digital humanities was a very broad term and many people have different perspectives of it. I believed digital humanities is having information, sources, and data online in a categorized formate. After reading chapters 2, and 3, I noticed the idea that data is all information. It can be structured or unstructured but it can all be found online. That showed me that digital humanities is even more broad which I did not think was possible after last weeks readings. The chapter talked about categorizing information in an organized way. I did not realize there were so many rules and criteria's for structuring data. In short, data is just information that needs to be organized properly or it will not be useful to the attended audience. In chapter 3, "language" was used to describe tools used in formatting the information on the web. I thought that was ironic because it is the best word to connect digital humanities together.  I

After reading Chapters 2 and 3 of the textbook I have gotten to dive deeper into the meaning behind Digital Humanities. To begin, data is really hard to describe but it is the "characters" of a certain analysis put into a physical form. Before the data of something had been retrieved and accessed it did exist did not hald any physcial value although it was still technically existent. For example, there is a certain percentage of people that like oranges over apples, but before there was any data on the percent ratio from apples to oranges it wasn't existent of actual value, even though it was still existent. As said in the book "These are acts of remediation by which some feature of an already existing phenomenon is abstracted into a value"(Drucker, 19). There has been plenty of data work done with the project I am analyzing, for example, the whole textbase itself is filled with literary scholars, which is a whole list of data being gathered under one database. 

While I did have some background knowledge on data and the vastness that it is, chapter 2 of The Digital Humanities Coursebook by Johanna Drucker just further expanded on what I thought I already knew about data and the digitization of materials for digital projects.   One passage of the textbook that gave me some new insight data was on the first page of the chapter, where the difference between unstructured and structured data was elaborated upon. Drucker wrote, “A distinction is made in digital work between structured or unstructured data. Structured data is composed of entities that are explicit, discrete, and unambiguous—like numbers or true/false statements. Unstructured data, like natural language, is sometimes ambiguous and unclear—like a picture of a mother holding a child which can be described in many ways” (Drucker 19.) While a newcomer into data may assume that data is strictly numerical digits or embedded digital codes, data can take numerous forms and sizes, which adds

In reading chapters 2 and 3 of Johanna Drucker's The Digital Humanities Coursebook , my understanding of digital humanities was certainly furthered (as to whether or not it became more clear is up for debate... it seems as though the more you learn about DH, the more ambiguous the definition becomes). Chapter 2 of the text was centered around the topic of data modeling, which provided insight as to how data is embedded in a digital format. To paraphrase the book, data modeling is the process in which information is abstracted to produce data in a new way. To directly quote Drucker, "Humanities 'data' are produced by taking documents or artifacts and abstracting from them certain features that can be represented explicitly" (Drucker, 19). Furthermore, the process of consuming said content means extracting the data by "analyzing the categories into which the information has been organized" (Drucker, 21). This really put my own definition of DH into perspec

                   Digital Humanities              Prior to reading chapters 2 & 3 of the Digital Humanities Coursebook, I had a very generalized view of what data consisted of. Personally, I always thought of data vaguely as a broad set of numbers and charts that usually applied to math and science. According to the book however, the composition of data can be broken into individualized groups. For instance, unstructured data consists of written texts such as manuscripts or historical ledgers. By contrast, structured data takes the form of the more traditional graph or icon. Understanding the differences has made me more aware of the depth of the realm of Digital Humanities. What defines data and project labels is greatly determined by the materials used.   Chapter 3, meanwhile, addressed the protocol and format for adapting and assembling materials. HTML provides an example of this process. The majority of all online material is formatted in HTML, which programs specific function

  The section on data helps and relates to my project for analysis because now that I have a better understanding of what is is I can find more things to analyse from my site. Data (like digital humanities) is a lot broader of a subject than I initial thought it was. It's not all about the obvious numbers like you'd automatically assume, it can include things like "text, beats in a measure, pixels on a screen, and distances on a map can all be turned into quantitative data," (Drucker, 19). This very helpful as a guide for what to focus on/analyse on my website.  The checklist for creating a data model was very helpful, I like that it breaks down with instructions. Data and digitalisation play a key role in digital humanities by being the large part of what makes it up. They apply to the website I'm analysing especially the digitalisation because my site is composed of a bunch of imported files to journals and projects. These chapters gave a dive into these compone

       While reading chapters two and three of The Digital Humanities Coursebook, by Johanna Drucker I was able to further my definition of digital humanities. While reading these chapters helped develop my definition it also broadened it. I did not realize just how many specific concepts fall under it. The second chapter dived into the data portion of the definition. This chapter talked about all the different ways that data can be used whether it was through structured or unstructured data. My main takeaway from this chapter is that "Data are the basic units of almost all digital works" (Drucker 27). In chapter three we expanded on the formats that digital humanities can be developed into, which could range from creating HTML with online tools to films and sound recordings. In this chapter I learned more about building websites and the standard protocol to do so.      After reading these two chapters I was able to apply the information gathered, onto my digital humanities p

  After reading all the assigned excerpts it is clear that digital humanities does not have one clear definition. Everyone has their own interpretation of it and the topic embraces these meanings, as said in The Digital Humanities Manifesto 2.0 "digital Humanities is not a unified field but an array of convergent practices that explore a universe" proving that it doesn't belong to one solid definition. I was not all that aware of what digital humanities was before reading these texts, my assumptions were based on the words themselves; digital, meaning the up-and-coming technology combined with humanities, meaning the study of human behavior. At all odds, my description wasn't too far off from Johanna Druckers who said, "digital humanities work is done at the intersection of computational methods and humanities materials." There are so many components to digital humanities it would be almost unfair to simplify it under one meaning. You have the process of cre

I believe that the question of what exactly digital humanities is proves itself to be quite subjective. The question in and of itself holds no true “right” answer. Instead, it lends itself to be a brain-teaser of sorts, a means of evoking thought. For myself, I see digital humanities as a field of study where humanities and digitalization intersect. It brings more of a modern approach into the otherwise familiar study of humanities alone. Seeing as how digitized media relations and technology in general are becoming increasingly prevalent with each generation, digital humanities serve to somewhat preserve the study of humanities, or at the very least make it more palatable to an ever-evolving audience. Johanna Drucker in The Digital Humanities Coursebook describes digital humanities as a sort of formula— “MATERIALS + PROCESSING + PRESENATION” (Drucker). What sets apart the digital humanities from standard humanities are exactly these elements, where the materials in question, the proce

The phrase ‘digital humanities’ may be one of the broadest blackholes I have ever found myself trying to refine. While reading the select introductory excerpts, along with additional research, I have noticed a pattern in which most definitions are either extremely simple, or longwinded. One of the simplest, yet potentially most effective, definitions of digital humanities is that “Digital Humanities is not a unified field but an array of convergent practices” ( The Digital Humanities Manifesto 2.) The digital humanities encompass a large plate of end-results, that it feels exclusive to narrow down a definition to one sentence. Digital humanities, to me, is “the process in which physical media is presented in a digital format.” While the digital humanities can include numerous methods and results, I have found that most definitions of digital humanities tackle these aspects.   One of the aspects of digital humanities that tends to get lost in the collective of numerous definitions is t

 After reading the textbook overview, DH Manifesto 2.0, and What is Digital Humanities, I noticed all the sources did not give a set definition. From my perspective, digital humanities is having information, sources, and data online in a categorized website. I had little to no knowledge for what it was before the readings. Randi Junus said, "u sing computational technologies for analysis and making them more readily available for access and allowing others to examine, reuse, and discuss the artifact"( What is Digital Humanities). This quote was very interesting because I believed it explained digital humanities in a simple form. Most definitions given were hard to break down for me, especially because I had no previous knowledge. I read in the textbook overview that digital humanities does not have to be online so I was wondering if a magazine like Vogue could be categorized as digital humanities. It does have material, processing, and presentation. It can be seen as less ela

 I consider digital humanities to be a very broad term that encompasses various components. When I first thought about the definition of digital humanities, I believed it was the analyzation of humans through a digital perspective. After reading the Digital Humanities Coursebook I learned that the term is even broader than I had interpreted and covers more ground than I had realized. Digital Humanities takes the art, music and literature form of humanities and turns it into a digital component (Drucker, pg.1). While the definition is broad, I did learn from the Digital Manifesto that digital humanities is not just one field that happens to combine components from different fields  ( Digital Manifesto , pg.2) . The reason it is not just one field is due to the unique ways you can use digital humanities to create something new in more than one specific field. In the Digital Manifesto they refer to digital humanities as "an array of convergent practices" which I believe is one o

  Kaitlin Carroll     When I think of the d igital humanities the first thing that pops into my head is a computer. Whether thats accurate or not it's what pops into my brain. Digital obviously makes me think about electronics, and then following it with humanities make me think of how people interact/express themselves within those electronics. After playing around with the blog and reading some of the Digital Humanities course book, the definition of digital humanities can be interpreted to be combining humanities properties with computational methods. (Drucker, pg 1). The components that Johnna Drucker discussed in her book of digital humanities were most helpful at breaking that subject down for me. In the manifesto, it is explained that it is hard to limit what can be classified as digital humanities because the subject is wide with various allowances of what counts as the category. I like this because then digital humanities is a perfect way to be expressive in a persons own

 What is Digital Humanities? Humanities, in the simplest terms, is the discipline of art and literature. While there could be further speculation of what that entails, there is a general consensus regarding the general field of humanities. By contrast, digital humanities is a broader term—and a more ambiguous one at that. Combining creativity, technology, and analytics, digital humanities explore the Arts in innovative new ways. From algorithm programmed poetry to virtual archives, the possibilities of design are endless. Digital humanities opens up the world to an entire new realm of invention.     The endless opportunities, however, make it difficult to define the extent of digital humanities. The Digital Humanities Manifesto attempts to do just that; compiling a lengthy 14 page discussion of the subject. According to the Manifesto, the phrase ‘digital humanities’ has  “use‐value to the degree that it can serve as an umbrella under which to group both people and projects seeking to r