Multilingual, Multidisciplinary, Multicultural: Welcome to the New World of Scholarship

When we held our first group meeting, the video-conferencing system didn’t work. Big Data indeed.

Working in large, international research groups poses many challenges and many opportunities. Skype breaking is probably the most predictable. But there are others, like the fact that in our group English definitely isn’t everyone’s first language (don’t get me started about time zones!). In fact, by my count I think we have five different native tongues involved (& 9 time zones for the record). But it’s even more complicated than that because language and culture don’t overlap seamlessly: team member Robert Wisnovsky’s specialization is Islamic philosophy but is from the U.S. and teaches in French-speaking Canada. Mohamed Cheriet works in French in Quebec but was trained in Algiers and Paris. Elaine Treharne is a Brit working on medieval manuscripts in California. Each member of our group looks similarly multi-patterned.

Understanding each other linguistically is probably the easy part however. Even harder is how to get people from the humanities talking productively with people from engineering and computer science. Our disciplinary languages don’t yet have an esperanto like global English. We’re still working on how to explain our interests and our abilities to each other in ways that not only make sense but get people from the other respective disciplines excited. It’s a lot easier for me to understand what my colleagues in Islamic Studies or East Asian Studies are after even though I don’t speak Arabic or Mandarin than it is to immediately figure out what my colleagues in the Synchromedia Lab or ALICE are doing.

And yet that’s the exciting part. We each have expertises that benefit the other. Knowing how to analyze visual features of pages, whether it is capturing high-value words or questions of lay-out and spatial arrangements of words, is incredibly valuable to the humanist team members and something we could never do alone. Knowing which words and which spatial features to concentrate on is similarly a gold-mine for our colleagues in computer science who wouldn’t know where to begin to look for meaningful semantic and cultural features of documents.

There’s always a lot of hype around big data, but at the simple, everyday level of being able to get people to come to the table from different cultures (broadly understood to include language, culture, nation, and discipline), it is an unbelievable opportunity.

This is the world of learning I want to inhabit: smart people speaking different languages with different expertises trying to find common ground to learn new things about human culture.

Whatever we do or do not find out, the process itself is a major intellectual outcome in its own right.