Data is absolutely essential in the digital humanities. It's the backbone of every DH project. The gathering of and analyses of data allows humanities scholars and other interested parties to interpret said data into a new understanding of historical, cultural, and social occurrences. Data is a rather broad term that essentially means "information." This type of information could come in the form of archivable items/documents like digitized medieval coinage, letters from the Civil War, oral history files and transcripts of Indigenous cultures, Japanese artwork, classical piano music sheets... The list is endless.
Open data repositories are very valuable in DH. They provide access to diverse datasets, reproducibility and transparency for creators and users, they are free so researchers don't need to spend any money (thus helping promote equality and equal access), they facilitate and expedite research, and help safeguard the preservation of cultural heritage. They are also great practice for researchers who are new to the field.
Data mining in the context of DH is the process of discovering meaningful patterns or trends from large and complicated datasets. The type of data that can be mined include digital sources like texts, images, and videos. The following links lead to detailed explanations on the various methods of data mining and collection.
