An image of a city with skyscrapers at night is in the background. The image on top is a series of blue colored lights, switching back and forth across the image. This image symbolizes connections and data, two elements that are descriped in further detail in this post.
LibParlor Contributor Reflection

No research topic is too esoteric for a librarian

Kimmy Szeto recounts how working across disciplines ended up opening up a wonderful new research area.

Kimmy Szeto is a librarian at Baruch College in New York City. His research focuses on the design and philosophy of linked data. Outside of the library, he enjoys playing music and dancing the Argentine tango.

When Learning Turns into Research

While I have always conceptually understood that libraries and librarianship are not free from systemic bias, I recently stumbled upon an interdisciplinary, cross-cultural research project that really clarifies to me what this is about. 

At the start of my career, I could never have imagined reaching a point where I, of all people, seemed to be the only person on the planet systematically building an open access knowledge base for a set of fundamental concepts in traditional Chinese medicine. After all, Chinese medicine has existed for over 5,000 years! Three years ago, curious about my own cultural heritage, I took some coursework on shiatsu. (Shiatsu is like acupuncture but uses finger pressure rather than needles; they both share the theories of traditional Chinese medicine.) When learning the locations and functions of acupoints, I noticed that students in my class relied on rote memorization, and had a hard time integrating and retaining the knowledge. This reminded me of the well-established visualization tools that exist for western anatomy and physiology, and how simple it is to look up any bone, muscle, and major neuron on Wikipedia, where each page clearly lays out systematic and complete information drawn from its underlying structured data repository Wikidata. The librarian in me started to create a LibGuide for my classmates. I was able to find a handful of websites but none was geared toward students. So I thought, “There ought to be better reference sources. If there isn’t already one on Wikipedia, we should make one.” After all, librarians are knowledge creators, too! What can be more befitting than entering linked data directly into the semantic web?

I casually suggested to the professor, Wouldn’t it be fun to host an edit-a-thon to populate information about acupoints? Students would come together over pizza, solidify their own knowledge, while helping build a knowledge base so that visualizations can be built in the future. 

Little did I know…as I started to make preparations for the event, I discovered there was nowhere for the information to go in the Wikipedia/Wikidata universe. As I started to set up data fields, I could not find any suitable properties for the core understanding of meridians and acupoints—properties that describe the relative increase/decrease and equilibrate/balance of qi, or properties that map non-physical aspects to the physical anatomy. 

The more I looked, the more I realized that Wikidata’s emphasis on part-whole, class-subclass, and opposite relationships represents a reductionist and dialectical worldview, where the body is made of smaller physical parts down to the molecular level, and the physical and non-physical are necessarily opposing. In contrast, traditional Chinese medicine is based on a harmonious duality (yin-yang), and is a holistic system that focuses on bodily functions while considering both physical and non-physical contributors. The concepts of qi and meridians are examples of the non-physical substances and structures, while acupoints interface between the non-physical and the physical. 

Doing Research on Wikidata 

Needless to say, I soon scrapped the idea of the Wikidata edit-a-thon. Instead, this episode opened up an entirely new area of research into developing linked data ontologies compatible with aspects of eastern philosophy. So far, I have been able to conduct some preliminary work thanks to a research grant from my university. 

As a Wikidata novice, my work was primarily exploratory, without making drastic changes to existing items, creating new items, or proposing new properties, just as my cataloging mentor once said, “If you’re not sure yet, don’t.” In a way, looking for Wikidata items and properties to describe a body of knowledge is, in my mind, analogous to searching for the most appropriate cataloging rule and selecting the best suited MARC subfield and indicators. I looked for analogies in systems of science past and present—mathematics, biology, astronomy, medicine. I created an annotated catalog of items and properties, where my reasoning and analysis are noted for each. In addition, due to the open nature of Wikidata, I had to invent a system to document work in a globally shared space where my work will inevitably be overprinted on. Essentially, I kept a journal with dated snapshots of each item and property and detailed notes on my thought process toward all that I read, considered, analyzed, and touched. Finally, when I felt comfortable enough to do this responsibly, I removed the inconsistencies in the Wikidata items for acupoints and meridians, and placed these entities in proper hierarchies, even though some descriptors are not yet optimal.

Research with a Mission

In the future, I look forward to the opportunity to take a deeper dive into the philosophical underpinnings of traditional Chinese medical knowledge and to propose new properties toward a systematic overhaul of Wikidata properties for these concepts. 

As a mid-career librarian and recently tenured academic faculty, I found myself caught up in perpetuating the system: the more I build on the existing Web 3.0, the more I am allowing the system to become entrenched in its western paradigm. Hopefully, this new area of research will re-imagine the web a little and help make the internet a more culturally inclusive place. 

Acknowledgement: I would like to thank Rezan Akpinar of Queensborough Community College for her expert guidance on the intricacies of the science, Ann Matsuuchi of LaGuardia Community College for getting me started on OpenRefine, and Megan Wacha of City University of New York for taking me through QuickStatements.

Featured image by Pixabay from Pexels

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License

The expressions of the writer do not reflect anyone’s views but their own

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