Reading this article towards the end of the semester felt as though it was bringing the class full-circle. At the beginning of the semester I knew very little about the possibilities of data analysis, and was still relatively new to the idea of digital humanities. When Professor Shrout introduced herself as a historian who used coding in her field, I was pretty surprised/intrigued by the concept. This article, as well as the many others we have read this year,  introduced the innumerable and valuable ways in which the digital world and humanities can work together.

For years, we have heard the phrase “don’t trust everything you read on the internet”. However, as the Internet becomes a primary platform for sharing information, the issue now lies less-so in finding sources outside of the internet, and more-so in discriminating between credible and non-credible sources on the web.

In the same way, scholars are hesitant to acknowledge online texts as equal to their physical counterparts. As the authors state, “People who publish in online journals undoubtedly experience more substantial resistance, but the belief that online articles don’t really count seems more and more like the quaint prejudice of age than a substantive critique.” In a new age of sharing data, people are beginning to adapt their review processes in order to cater to the increasingly popular method of digital data distribution.

The professionals who fall under the field of “digital humanities” are also facing some hesitation from others who are not immediately familiar with the relatively new field. “For this group, making their work count is by no means an easy matter.” It would seem that all they contribute (e.g. “digital libraries”, “deep coding of literary texts,” “3-D models of Roman ruins”, “charts and graphs of linguistic phenomena”) are inherently of great value to their fields, but they seem to struggle for scholarly recognition nonetheless. (As my peer said in a previous blog post: “Their efforts to help facilitate the work of professionals… are crucial to their success and yet their work is constantly overlooked and even at times deemed non-scholarly.”)

In seeking to understand the study of digital humanities, I think the authors nail it on the head with their description of theory in the context of digital humanities: “ In the context of history or literary study, “theory” doesn’t predict, but it does explain. It promises deeper understanding of something already given, like historical events or a literary work.To say that software is a theory is to say that digital works convey knowledge the way a theory does, in this more general sense.”

This article felt a little too opinionated for my liking. I agree with DR that this article seemed to have a lot of filler, without making many concrete connections throughout the whole article. I find it ironic that this author seemed to be skeptical of online academia and scholarship (and the criticism of it) yet, they were writing academically and criticizing online work… A little too meta for my liking.

The only point I found interesting was at the very end when the author was debating whether creation of scholarly material still “counted” if it was built by a machine. I think that this just gets into ethics of ownership and intellectual property.

Ramsay and Rockwell embark on the process of trying to categorize the Digital Humanities in their article.  While I found it interesting and thought-provoking, I thought it was lacking in persuasiveness and somewhat in relevance.

First of all, we must define the term “scholarship” that they refer to constantly in the article. Cambridge dictionary defines scholarship as “the qualities, methods, or achievement of a scholar”.  In an article mainly focused on semantics and categorization, I find it extremely important to be precise about meanings and relevance.  I agree with tbarb in that the article is “awfully concerned with generalities”.  I couldn’t help but think, “Why does it matter?” in response to “Is building scholarship?”  I wish the author had been more clear about this (they might have, I just couldn’t tell).  However, I do agree that these conversations will be more and more important as DH continues to grow in our world.

Overall, I thought the article made some interesting hypotheticals, but I fail to see its relevance outside DH professors trying to secure grants/funding (in which case it might be very important!).

To be frank, the piece “Developing Things: Notes toward an Epistemology of Building in the Digital Humanities” by Rockwell and Ramsay did not do much for me.  I felt that the article was really vague and not blatantly insightful. While there were undoubtedly points that were beyond me, I feel that if somebody has a good point to make, it will generally be clear to the reader.

Was one point of this to decide if digital tools can be theories? They already stated that in the humanities sense “theory” is an adapted term from the classic scientific sense, so are the semantics really that important? I guess it just seems that whatever point they are arguing has little effect on what the results of any research would be.

I agree with DR that much of this “went right over my head”.

In the article “Urban Electoral Coalitions in an age of immigration”, Sonenshein and Drayse explore some interesting phenomena about the relationship between time, space, and political coalitions.  One of the things I found most surprising was how dynamic political coalitions in this country are. In other words, I was surprised to see how much political coalitions change depending on the political landscape as well as geography and immigration.  In modern politics, it’s easy to assume or predict which groups of people align themselves with others. This article proves, however, that political alliances are much more fickle than meets the eye. For example, sometimes, African-Americans and white conservatives align themselves based on mutual agreed threat that is brought in by Latino immigrants.  Due to ideological differences within white conservatives alongside the belief that immigrants pose a threat to the African-American position, sometimes these groups and their votes coincide. However, a fissure between white conservatives and African-Americans was exposed due to a policy regarding police support in LA. The point is that the coalitions that we come to assume can no longer be taken for granted.  Due to the heavy influx of immigrants from around the world, these political coalitions are more fickle than ever.

I also found the coalition data with regard to the maps to be very interesting.  In LA, historically white liberals and African-Americans have formed political coalitions.  The map suggests that white liberals have the furthest proximity from African-American and immigrant communities.  This draws my attention to a potentially interesting hypocrisy. It appears from this map that white liberals have adopted a progressive approach to immigration in parallel to a “not in my backyard” approach.  I find the effects of geography and spatial proximity on feelings toward immigration incredibly interesting and also ironic. To me it’s obvious that more exposure to undocumented citizens would demystify them and create support for them.  As the article shows, this is true in some cases, but not for others and is a truly fascinating phenomena.

I like how HR related this topic back to Lewiston, ME.  Lewiston faces many interesting immigration issues and is interesting to see the coalitions form between different communities, the racial implications they hold, and how they’ve changed.  Historically Lewiston is a city of immigrants. It’s interesting to see how the community and their relationship towards the latest wave of immigrants has changed and weather or not their are racial implications.   

In reading the blog post about Paul Revere there are a lot of really cool things to be discovered. First is the utility of networks in visualizing all sorts of information. from connections to people to connections from people to places and all sorts of other things. As a math major it’s always nice when I see a concept that I learned in a math class be used in a different context with extreme seamlessness and usefulness. Then looking at measures like centrality and betweenness of a node and seeing that number have a real world interpretation is also very satisfying to me. I really like this post, it’s fun, there some cool stuff in it and it definitely helps reinforce the stuff we’re learning about metadata and networks. As csamuelson points out: the article is entertaining and educational and an all around great read.

This article raises a few interesting points about text. Specifically I’m interested in the availability of texts. They mentioned that sometimes texts are abundant in one discipline. So abundant that it an be difficult to get through all of the texts and find what is relevant to the topic someone is looking into. Other times there is so little text available on a topic that it can limit research like user Jnichols99 astutely points out. However when text is available there is the problem of visualizing such large amounts of text in a way hat people can extrapolate meaning from it. Then there is also the problem of presenting a visualization that people can interact with and explore to fit their own individual interests. Ultimately, visualization is very subjective and comes down to what is the purpose of the visualization. What may serve as a good visualization for one person for one purpose may be a bad visualization for another person or another purpose.

This article about the guiding principles for findable, accessible, interoperable and re-usable data was very interesting and I enjoyed it quite a lot. Towards the beginning of the article I really like the idea that was presented and upheld. This idea was that this document is a “guide to FAIRness of data, not a specification”. I think it is very important to specify these as guidelines as all sets of data are different and some might not be able to meet the criteria. Again they say later “the purpose of this document is not to define nor suggest and technological implementation for any of these facets, but rather to define the characteristics, norms, and practices that data resources, tools, and infrastructures should exhibit in order to be considered ‘Fair’, and FAIR-ness can be achieved with a wide range of technologies and implementations.” This document also does a good job defining concepts, data object, and meta data to make this information really accessible to everyone. Also, the figures make kind of explain the overall idea of what’s going on with FAIR within each aspect of data. This was an interesting article that presented information in fair way haha.

Honestly, I did not like this reading very much at all. I feel like the information given throughout this text isn’t very useful and a lot if filler. A lot of the information that is given within the first half of the article is hard for me to find correlations to the main idea. It starts out with all this talk about people posting in online journals which would be stressful but then it goes into scholarship and whether those doing such things are still engaged in humanistic inquiry. A part that I did enjoy from the reading is the part about theories and how they should be more accessible to those that that don’t have a higher education. I particularly like this description “A well-tuned instrument might be used to understand something, but that doesn’t mean that you, as the user, understand how the tool works. Computers, with chains of abstraction extending upward from the bare electrical principles of primitive XOR gates, are always in some sense opaque” I don’t know if it was just me, but I feel that this reading was hard to understand and for the most part went right over my head.

This article is one that is very interesting and brings up many interesting issues concerning the work done my digital humanitarians. Their efforts to help facilitate the work of professional writers are crucial to their succus and yet their work is constantly overlooked and even at times deemed non-scholarly. I found this article very though provoking because of how challenging this question is. Why aren’t certain tools deemed scholarly if they are used to create a scholarly piece? If writer uses a program that helps create their bibliography or uses a topic model to create important connections from a vague text, how can it not be counted as a scholarly tool?