In the article called Big?Smart?Clean?Messy?Data in the Humanities gives us a basic introduction to data in the humanities in a well-structured way. Data in the humanities currently include both smart and big data, which have different features and uses. However, what the author proposes at the end of the article is the idea of big smart data, which combines big and smart data with the techniques of automation and crowdsourcing. The reason why we currently only have separate big data and smart data is due to the limitation in technology. However, finding the focus area and taking a closer look at this area requires big and smart data, which is crucial in digital humanities.

Towards the end of this article, the author mentions the idea of machine learning, which from my perspective, is a key to generating big smart data. Nowadays, we have been using machine learning in all aspects of fields. For instance, in architecture design, machine learning has been proposed to generate residential floor plans automatically by manually inputting key parameters. As a result, designers can choose from those generated layouts, which I suppose can be called big smart data, and decide which options are better. Though not widely used in this field, designers somehow have seen great potential in what machine learning and data can support us in design. However, I would suggest this process of using data by machine learning still relies much on manual input and intervention. It should be a back-and-forth process between humans and machines. Otherwise, machines will replace humans someday, which is entirely contrary to the essence of design.