Don’t be afraid to fail or to get bad results, because those will help you find the settings which give you good results.
Topic modeling gives room for failing or getting bad results. This allows for users to build up on their errors and to find a solution. This is important because users are able to work through using these errors to find the necessary settings for good results.
Topic modeling is not necessarily useful as evidence but it makes an excellent tool for discovery.
Although topic modeling may not be the most accurate tools for evidence it is useful to digital humanists. It helps digital humanists to put data together
It is important to be aware that you need to train these tools. Topic modeling tools only return as many topics as you tell them to; i
This is an important point because without training these tools they could cause issues during the topic modeling. It is important that specifications are given to these tools so that they are able to process exactly what is needed. This would allow for any issues to arise while topic modeling and to allow for a smooth process to occur.
I think that’s why digital humanities is so challenging and fun, because you’re always holding in your head this tension between the power of computation and the inadequacy of data to truly represent reality.
In my opinion this statement is very true. Even though it is challenging at times , digital humanities can be fun. When collecting and improving the quality of data to represent reality it creates a thrill for digital humanists. The challenge allows humanists to think creatively and find different solutions to the problems presented to them
In many ways, digital humanists will have similar data-management needs to scientists and social scientists — they’ll have spreadsheets, images, and video, and will probably at least know what metadata is.
Although digital humanities is a career in a class on its own there are some similarities with other careers. Different careers will have close data management needs. Like digital humanists use applications such as spreadsheets these other careers use them to store and sort out data
different schemes serve distinctneeds and audiences.
There are different schemes created for different types of people. The schemes are catered to meet their needs and wants. Standards need to be upheld so that the different schemes contain the correct information for the particular groups they were created for.
The creation of metadataautomatically or by informationoriginators who are not familiar withcataloging, indexing, or vocabularycontrol can create quality problems.
It is important that metadata quality is held at a certain standard. Metadata needs to have a set quality so that it can be consistent. Consistency is important so that metadata can be professional looking.
Preservation metadata
This type of metadata is important because it allows for preservation of important data and information.
Our digital age presents a different medium in which to convey multiple sources of information and to render interpretive arguments
This is an important point because our digital age allows for more information about our history . It allows for different versions and different perspectives of major events that occurred in our history.
increasing the scale of research and data involved
This quality is extremely important in my opinion. I think this because if the scale of research and data are increased then more information will be able to be processed.
We have only a “glancing bird’s eye view.”
This statement is true especially in the case of digital humanities. Digital humanists have not uncovered the complete capacity and potential of Digital Humanities. This statement shows that digital humanists have not unlocked the full potential of digital humanities
speaking of “data” in the humanities is problematic
This is a good point. Humanists opinion on the definition of what data is varies, based on who you speak to. This is shown for example Information scientist Luciano Floridi defines data at its most basic level as the absence of uniformity. But on the other hand Digital Archivist Trevor Owens argues that data is not a given rather, it is “a multifaceted object which can be mobilized as evidence in support of an argument.” These are just two of many examples of how data can be defined as a among humanists.
I actually find these problems to be quite interesting and challenging: taking the datasets we’ve been given — which were not at all created for our purposes — and working against their grain or reinventing them to try and tease out the things we think are really interesting.
I agree that the problems are interesting and fun. The fact that digital humanists have to basically take apart datasets to use the most "interesting" parts of them to be able to use them to deal with data is very fascinating to me. It shows how the work that digital humanists do is so different from other people who deal with data
you’ll see that we’re cobbling together dozens of tools, none of which really do what we want them to do.
This statement is true. To digital humanists data management can be difficult. Especially with the collection of information that they receive and collect. For the common man it may be easier to use one data management tool but with digital humanists, to collect and store data they would need to make use of many tools.