Schoch’s paper about the paradox of smart vs big data in humanities makes some important points about current limitations in data collection and analysis. While smart data provides more specific points of research, the methods of generating such data are specialized to the purposes that it serves, making it difficult to generalize these methods. On the other hand, big data can be used for a wider variety of purposes, but requires more advanced analysis to draw meaningful conclusions from it. As Schoch argues, there is a need for data to become both smart and big.

I found it interesting that although this challenge in data exists beyond the field of humanities, it is particularly a challenge to humanities research because of how difficult data collection is in this field. For example, data used in humanities research often involves texts that come from inconsistent sources (eg. books, newspapers, online blogs), and so it is challenging to create a structured method of data collection. Other fields also struggle with the challenge of smart vs big data, such as in HCI research. However, the challenge in these fields lies in creating technology that can better structure and analyze data. In the humanities, however there exists the additional challenge of creating more efficient data collection methods in the first place.