Digital Humanities 610

 In all honesty, I don’t enjoy distant reading and can’t find any real use in it for small scale, college projects and papers. When practicing with “The Nose” in Voyant Tools, I could tell you very little about the plot. I got a sense for the time period but that was about it. Now that I have close read and distant read “The Tell-Tale Heart” by Edgar Allen Poe, I found it easier going into the distant read knowing what the story was about. It helped me better interpret the information presented in Voyant tools but still, I feel the information wasn’t too useful for me. I was able to pick out the eerie and gothic wording as well as see trends between the words used within the text and the formatting of the story. But I also feel I could have picked all of this out on my own. After reading “Quantifying Literature”, I feel I have a slightly better understanding of how distant reading can be used. I find it interesting and cool that he was able to pick up on trends in Dicken’s works an...

  I found the content of the assigned chapters especially relevant to the DH project I am currently analyzing. These chapters touched on both data mining and information visualization, two key aspects of what it means to translate humanities into the digital world. Data mining is a type of analysis that looks for patterns and extracts meaningful information from digital files. The practice of ‘data mining’ has been incorporated into the general study of humanities in a multitude of ways - on both small scales and for larger projects. Data mining has become an extremely useful tool for researchers who want to analyze digitized text, music, recordings, images, etc. Information visualization is a concept that I have already been familiar with without realizing there was a term to necessarily describe this as a practice. This is the concept of designing graphics/visuals by translating data into clear and readable visual formats. As the chapter describes, visualization in this sense is ...

A section of Chapter Six that stood out to me focused on data mining and explained it in more detail. The textbook describes data mining as a process in which technology automatically identifies patterns in digital data. In digital humanities, we can use it to uncover details humans or authors may have overlooked. In chapter seven, a main idea that stood out to me was visualization. Visualization turns quantitative project information into visual data that's easier for readers to digest. It also allows us to analyze more data. These chapters are all about details. When we read a text, we often miss small details; in these chapters, the textbook explains how the technology digital humanists use scans our projects to find the details the human mind misses and turns those details into a simpler understanding.  In the Six Degrees of Francis Bacon website and the Yesterday, Today, and Tomorrow website, we see these ideas in the small connecting lines and dots that make the connections l...

 I personally take much more interest in distant reading than close reading. I always found close reading to be very tedious and not overly helpful towards creating a thorough understanding of what I'm reading. I find it to be more busy work than helpful towards improving my understanding, and it always felt like more of a chore than a helpful method. Distant reading to me is a lot more helpful because. according to "The Mechanical Muse - What is Distant Reading?", it focuses a lot more on the bigger picture stuff. While I do agree with Schulz's evaluation that distant reading can oversaturate and over evaluate a text when sometimes texts are meant to be enjoyed and comprehended in a simpler manner, I think that in a general sense the exercise of evaluating text for its deeper, more complex meaning is a healthy activity for promoting literary comprehension. I found the concept of data mining in The Digital Humanities textbook to be very interesting. While I do not nec...

     What stuck out to me most from Chapters 6 & 7 and the distant reading articles is how much changing our scale alters how we approach literature. In standard English classes, we are taught to focus almost entirely on close reading, dissecting specific lines, tone, and individual word choices up close. Distant reading basically flips that on its head. By zooming out to look at huge chunks of text or metadata all at once, you can pick up on broad patterns that you would never spot just reading page by page. But as "Problems of Scale" points out, there is a real trade-off: when you zoom out that far, it is really easy to lose the small physical details and context that give a piece its actual meaning.      You can see this dynamic playing out in network tools like Six Degrees of Francis Bacon and sentiment maps like Yesterday, Today, Tomorrow. Six Degrees maps out historical ties into visual webs of nodes and lines, which makes seeing connections betwe...

What I found most interesting about distant reading is that it changes what it means to “read” something. Instead of paying close attention to one passage or text, distant reading lets us look for patterns across a much larger amount of material. At first, that felt a little strange to me because I normally think of reading as actually working through the words on a page. The readings and the Coursebook chapters made me realize that looking at patterns, connections, and visualizations can reveal things that would be difficult to notice through close reading alone. At the same time, there’s a tradeoff. The larger the scale becomes, the easier it is to lose some of the individual details and context that give the material meaning.  Six Degrees of Francis Bacon helped me understand this idea more clearly. Instead of learning about early modern people one biography at a time, we can see people and their relationships as a network. Looking at the information this way makes certain conne...

Chapters 5 and 6, as well as the essays on multimodal analysis, data mining, information visualization, and distant reading have enabled me to see how Digital Humanities can take a vast quantity of information and make it easier to detect patterns. Distant reading is particularly interesting because rather than closely examining a single text, the researcher looks at a large number of texts and employs digital tools to identify patterns that would be difficult to spot on an individual basis. At the same time, the essay entitled Problems of Scale showed me that working with larger amounts of data does not necessarily lead to more accurate or significant results. In fact, the scale of the data can introduce new problems because researchers have to decide which information is important and how it should be presented. This idea is very closely related to Six Degrees of Francis Bacon . The project involves the use of data mining and network visualization in order to reconstruct the relati...

     Data mining is a process that shows patterns within data that would be harder for humans to access or inaccessible without the help of a computer. It helps capture data that can then be reused and repurposed for research. It is a great resource that shows different perspectives of otherwise overlooked and especially marginalized communities and their cultures. But data mining comes with limitations, because it relies on preexisting information it may lack representation and miss information. Too much data mining may even change the results that researchers are looking for      Data mining is a type of distant reading that can be used to analyze text and literature’s metadata. Through distant reading, researchers can study literature using computers, data, and statistical analysis rather than looking at individual books. The process can be described as studying literature as a large collection of data. It is done because Moretti believed that computers ...

The main idea that I got from all of these readings is that each of these concepts is made to make data itself easier to look at and digest. The part I understood the most was the information visualizations. I've used this many times throughout school in things like research papers or responses for labs, so this topic was familiar to me. For me, this is one of the easiest ways to look at and understand data before they are broken down more specifically. I liked reading this section because it was interesting to see the break down of how visualizations like this work. The other topics like data mining, distant reading and API I found a little more confusing.  For distant reading in particular, I understand the concept of it but I don't really understand the point in it. For example, when using it for something like literature I don't really see how it would be helpful, as literature is typically supposed to be looked at in detail. When you write a literary analysis or a resp...

  While reading about data mining, I felt this would be an extremely useful way to collect large amounts of data in a short amount of time. Large websites and databases can be very intimidating and I know for me, it definitely turns me away when doing research. They can be boring and filled with so much information it honestly makes my head hurt! APIs and other data mining software is very intriguing to me and I would love to use some in my own research. Multimodal analysis seemed like a familiar topic for me. I feel that a lot of the data and information we consume today is a combination of images or videos and text. I find that multimodal data can be much easier to interpret and understand than plain text or images.  Distant reading confused me a little bit. Both in chapter 6 and “What is Distant Reading?” I found myself questioning how useful it could truly be. I see the use in it when creating a database or searching for specific information from specific authors or date...

 After reading about Metadata and Database and learning the importance of it in any  digital humanities projects, I found it particularly relevant to my project which is the 9/11 memorial timeline. While there is minimal data itself in my project, what I immediately thought of was all of the audio recordings and unique pictures, as according to page 29, "Metadata can be attached to objects or records." There are so many examples of metadata in this project including ID'ing all of the dates, locations, times, and events themselves and aligning them in a way to tell a story while maintaining its strict chronological structure to maintain emersion and keep the audience in the moment with each key event of the day. If this was not a Digital Humanities project and instead was more of a basis 9/11 project, you would have to log everything as separate entities, but in this case you can use what is described in the book as "Descriptive metadata" which the book says is ...

 Metadata and databases enable scholars to analyze Digital Humanities projects and archives. Metadata, in its most basic form, is the data behind the data, meaning that it is the identification and information about the resource. It makes digital projects searchable and understandable. It describes the resource in its basic form and shows how the resource is formed and created. This chapter emphasizes how metadata shapes the knowledge within Digital Humanities and further helps scholars to more deeply understand the research they are accessing.  Databases are collections of different information that allow data to be stored and analyzed. A simple example of a database would be a spreadsheet or table, which can function as a database, but some more complex digital humanities projects need a more complex database, like a relational database. These tie together multiple tables and different sources of data.  Metadata and databases form the foundation of digital humanities. T...

     Chapters 4 and 5 made me realize how much behind-the-scenes work goes into setting up a digital project. Before reading this, I knew metadata was "data about data" from my previous GIS class that I've taken. I did not realize how important it is for making archives searchable and easy to use. Metadata tells you who made the object, when it was created, where it came from, and what it connects to. At the same time, markup (like TEI-XML) tags parts of a text so a computer can process it. Together, they turn random digitized pages into something you can actually study.       On the Emily Dickinson Archive, metadata is doing a ton of heavy lifting. Since these physical letters and scraps existed long before the site was built, the metadata has to track their physical history (paper type, ink, recipient) alongside their digital details (file format, library source).      When you click on a poem, the sidebar gives you structured metadata...

  Metadata: The term ‘metadata’ has always been thrown around, and I had always assumed it was just the specific details of data, but it is actually so much more. Metadata, to my understanding, is a deeper dive into describing information in digital media. Metadata provides information about information and serves as a resource. It is most often used, from my understanding, in libraries and records to serve as a catalog of information. Metadata in libraries contains titles, authors, publishers, places of publication, dates, and even descriptions of physical features (pg 33). Metadata is a great resource for digital humanities as it gives the researcher a deeper understanding of what they are looking for while also allowing digital humanities project creators a way to display the records in a concise manner.  The first example of metadata that comes to mind is the UNH Libraries Website. The book mentions MARC being replaced by BIBFRAME when it was launched by the Library o...

From having read chapters 4 and 5, I can see that metadata organizes information which describes the content that makes up larger kinds of data. Data acts as the content we view, or ‘click’ to access files on a screen. This data may be images, music, text, etc. But metadata is the information that organizes said images, music, and text from one another. For example, the metadata of an image may be its specific source, date, place, digital format, and so on. A database is a larger ‘hub’ that can hold large quantities of information and organizes it to be easily accessed, researched, or stored. As a visualization, I thought of a database as a kitchen cabinet. Data would be the items found inside of the cabinet (the database). Metadata could be the nutrition label of an item (the data) in the cabinet (the database).  When considering a digital source that was converted from physical data, metadata can structure data in many kinds of ways. Metadata can describe the origin of the sub...

 I have always heard the term metadata but never really had any understanding of it until after I read these chapters. My understanding after reading chapter 4 is that metadata is information that describes other data like information, objects, content or documents. There are also different types of metadata such as descriptive, administrative, operational and paradata. Each of these provides different types of information about data. My understanding now of a database is that it is an organized electronic collection of information or data that is easily accessible and manageable. This is similar to my understanding before reading this chapter. When I hear database I think of library databases, which are an organized online collection of information. To me this term seems sort of broad but it helps to see how digital humanities actually works and is formatted. Both of these chapters furthered my idea of digital humanities. Every time I learn about a new aspect of digital humanities...

Chapters 4 and 5 of The Digital Humanities Coursebook helped me see how much planning goes into making information in a humanities project. Before reading these chapters I knew metadata was "data about data". I did not fully understand how crucial it is for making digital information searchable, clear, and easy to use. Metadata can tell us who made something, when it was made, what it is, where it came from, or even what topics it connects to. Markup helps organize information by marking parts of a text or digital object so that a computer can recognize them and work with them. In this way metadata and markup turn information into something that can be studied systematically or just being a page on the web. I now see databases as collections of data that let users store, link, search, and find information easily. Databases are powerful because they show connections between pieces of data. For example, listing historical objects, a database can link each object to its creato...

I think of metadata as the information attached to something that tells us what it is and helps us find or understand it. It can include basic things like the creator, date, place, subject, or format. One thing from Chapter 4 that stood out to me was that metadata is not just a technical detail. Someone has to decide what categories to use and what information is important enough to include. The chapter talks about classification and controlled vocabularies, which made me think about how much organization happens behind the scenes when we search a museum or library collection. I understood databases in a similar way. They are systems for storing information, but what seems important is how they organize relationships between different pieces of information. The example in Chapter 5 with artists, works, and owners helped make this clearer to me. Instead of putting everything into one huge list, a database can separate information into different tables and then connect them. That seems e...

  From my understanding, metadata is data which describes and explains other data. The textbook splits metadata into three groups, descriptive, administrative, and operational. In my previous studies of coding and web standards, I became most familiar with descriptive metadata which is used to simply describe and identify types of data. The textbook states administrative data helps organize large sets of data and operational metadata gives data specific roles. Previous to these chapters I was unaware of the other types of metadata but can see how important each role can be in giving data meaning.  My definition of a database would be an organized collection of large amounts of data stored to make locating and retrieving easier. This section taught me a lot of new terms and skills which definitely expanded my understanding of databases and how they work. Rational databases definitely seem a little daunting to me in terms of creating one. Having multiple spreadsheets all int...

 Blog post 2 Data and Digitization are fundamental tools in the digital humanities. Chapter 2 focuses on data. At the beginning of Chapter 2, the textbook discusses how finding and presenting data raises questions about what we leave out of studies, documents, or other materials because of the process by which we find and present it. In my project, I found the data for the website on Wikipedia. The timeline includes links to Wikipedia articles about each English monarch. I believe this could be an ethical issue in presenting data because Wikipedia is known as an unreliable source. Chapter 3 explains how the protocol and presentation for the web display are known as the “language” of the project. This language is also known as HTML, and it basically identifies and creates the basic structure of the design. As I understand it, it is the website's foundation. You can find it in tags on the website, like HTTP, which is encrypted information in the URL. This description helped me furthe...

In Chapters 2 and 3 of the digital humanities textbook, the authors explained different types of data that exist in the digital humanities world. In the second chapter, they went into detail about sub categories of the umbrella term “digital data” and the areas of data that existed before the digital world was developed. The authors transitioned chapters to inform us of the types of data that exist now as well as the processes by which data is preserved. This is where I truly made the connection between what it means when we refer to something as “digital” and how “humanities” as a study evolved by utilizing this as a resource. I find humanities to be similar to the offline data that the authors explain as the records or material which existed before a web presence or role imagined for them. Having the ability to translate this existing data into a digitized format allows us to archive almost anything. It provides creative ways to format data from past to the present and come up with n...

Chapters 2 and 3 helped me see DH as more than just using technology to study the humanities. Chapter 2 focuses on data modeling, which made me think more deeply about how information gets organized online. When something becomes data, someone has to decide what information is important, how it should be labeled, and how people will interact with it. Chapter 3 builds on this by talking about digitization and taking something that exists physically and turning it into something that can be viewed and used digitally. I can see both of these ideas in the MFA’s “Homer and the Epics” page, which is the project I chose to analyze. The page takes artwork and objects that you would normally have to visit the museum to see and makes them available online. At the same time, it gives the objects context by connecting them to Homer and stories from the Iliad and Odyssey. Data modeling shows up in the way the MFA organizes each piece and the information that goes along with it. Instead of only show...

     If someone were to think about Digital Humanities, they most likely would imagine scanning an old document, throwing it onto a website, and calling it a day. But Chapters 2 and 3 of the Digital Humanities Coursebook, Data Modeling and Digitization, show that it is way deeper than that.      Digital Humanities is not about moving humanities materials online. It is an active, hands-on process. Chapter 2 reminds us that data is not just lying around waiting to be found. It is made through abstraction. Every time we build a database, we make choices about what features to highlight, categorize, or leave out. Chapter 3 shows how converting real-world objects into digital files requires technical decisions around file types and image resolution. These two chapters show how technological choices and structures change the way we view humanities and history.      The concepts from both chapters show up all over the Emily Dickinson Archive. Dickin...

Data: “Data are some of the basic units of almost all digital work.” (pg 15) Data and data analysis/ extraction plays a large role in any digital humanities project. Data is quite literally all over the interweb, and there are different subcategories of data that can be used to describe data rather than keeping the term broad. Unstructured data is what most people see on the daily, things like images, text, and sound. But structured data is more sought after when someone is looking to be informed. Examples are graphs and tables that can be analyzed. Parametrization can be used to measure all the features within data. Examples include using metric systems to prevent biases and tokenization– determining which units are being represented and identified. Data is never neutral and will always come from a specific source that has its own biases.  Some examples of data in the project that I chose (New York Times Close Read) are poems, scans of artwork, scans of old newspapers, and the h...

Chapters 2 and 3 of The Digital Humanities Coursebook, “Data Modeling Use” and “Digitization,” extend my understanding of Digital Humanities by demonstrating that DH is not just representing humanities subjects in digital environments but also presenting information in a way that allows for recognizing patterns and ways of representation that would otherwise remain undiscovered. Data modeling practices demonstrated in chapter 2 allow for structuring information in a way that would enable its effective use by digital platforms, while digitization discussed in chapter 3 enables transforming physical or non-digital information into a digital format. My chosen project, American Panorama, created by the University of Richmond’s Digital Scholarship Lab, perfectly demonstrates the concepts discussed in both chapters 2 and 3. The project includes several historical timelines visualized on maps displaying migrations, elections, slavery, redlining, and land access in American history with intuit...

Chapters 2 and 3 definitely helped me expand my horizons on what I know about Digital Humanities just from a technical point of view. It helped push forward my understanding of exactly what goes into different types of stat manipulation and data usage in a DH project. As someone not super knowledgable or interested in coding or computers I'm not sure whether I will be applying what I learned to my project myself, which is a 9/11 Memorial Timeline, but it was cool nonetheless to get exposed to the process and to remind myself (especially in the age of AI) that all of these websites/projects/etc. didn't just pop up one day, but that they had to be meticulously coded to make sure that it was presented in the right way. All of this information definitely helped me look at my project in a different way. Knowing what it actually took to encode all of the pictures and words that I am seeing, and to make it as user-friendly and accessible as it is, helped me gain a sort of appreciation...

Data and Digitization:  After reading the next two chapters of the textbook, my knowledge of what Digital Humanities is and how it operates has definitely shifted and grown. Chapter 2 explains the difference between structured and unstructured data. Structured data is comprised of entities that are explicit and unambiguous, like numbers or true/false statements. Unstructured data is known to be more ambiguous and unclear, like natural language for instance. The distinction between these two concepts has ramifications for the ways that information can be used, shared, displayed, and analyzed. Unstructured data generally refers to texts, images and other digitally encoded information that hasn’t had a secondary structure imposed upon it. The concept of unstructured and structured data was very new for me to read and learn about. I am familiar with some of the ideas talked about in chapter 2, such as these two, but now I have a better idea of what unstructured and structured data refe...

 These chapters furthered my definition of Digital Humanities by explaining the methods of gaining data for digital humanities projects, as well as explaining the process of actually uploading and using the data. This made the definition of Digital Humanities more specific because it narrows down the types of projects that are considered Digital Humanities projects. I thought the steps for how to use preexisting data were interesting. I assumed this would be similar to a research project where you simply use ideas or images and credit the author. Using data for digital humanities projects seems to be much more of a process than this, where you need to research the author and the rights you have to the work. This makes sense to me because rather than just using ideas from the original author like you would in a research paper, you are actually directly using their work. I thought the digitization chapter was interesting as well because things like HTML I have seen many times using t...

  Chapter two helped me further understand the research and databases which are used or created in digital humanities projects. It also brought to my attention the pros and cons of using preexisting data. I never considered the impacts incomplete data and unethical uses could have on your projects. Especially in today's world. I find things online are much more monitored and protected under specific laws or regulations. Collecting data for a digital humanities project feels quite different from collecting research for a paper. Although some digging into the author, possible bias and overall trustworthiness are necessary for research projects, it seems to be much less expensive than that required of data. As I read through chapter two, I came to the realization that the majority of time put into creating a digital humanities project seems to be used for finding and integrating data. Because of this extensiveness, I appreciated the ...