The Challenge of Communicating Computational Research

Research Without Borders
April 4, 2013

Computational approaches to scholarship have revolutionized how research is done but have at the same time complicated the process of disseminating the results of that research. Conclusions may be produced using mathematical models or custom software that are not easily accessible to, or reproducible by, those outside the research team. And in some fields, a lack of understanding of computational approaches may lead to skepticism about their use.  

The panel considers urgent questions faced by researchers across the range of academic disciplines. How can scientists and social scientists address the lack of access to the software and code used to produce many research results, which has led to a crisis of verifiability and concern about the accuracy of the scientific record? How can digital humanists approach discussions of computational methods, which may not fit into traditional forms of scholarship and can be viewed with suspicion in disciplines that prize the art of scholarly analysis? Computational researchers are examining communication practices, policies, and tools that promise to more effectively convey their research process and the results it produces.

The panelists:

Neil Chue Hong is Director of the Software Sustainability Institute. He is responsible for representing the Institute and the interests of UK researchers at the national and international level. Within the organization, he oversees operations, leads policy development, develops and manages collaborations, and acts as the principal liaison with stakeholders. Neil has worked with researchers from across the UK and internationally to address barriers to the use of e-Infrastructure in research domains such as  biosciences, chemistry, digital humanities, Earth systems modelling, medicine, and the social sciences.

Matthew Jockers is an Assistant Professor of English at the University of Nebraska, Lincoln. Prior to his position at Nebraska, he was a Lecturer and “embedded” Academic Technology Specialist in the Department of English at Stanford University. During that time he co-founded and directed the Stanford Literary Lab. His research and teaching are focused on computational text analysis, specifically an approach that he calls “macroanalysis.” His forthcoming book is titled Macroanalysis: Digital Methods and Literary History.

Daniel P. W. Ellis is an Associate Professor of Electrical Engineering at Columbia University. His Laboratory for Recognition and Organization of Speech and Audio (LabROSA) is concerned with all aspects of extracting high-level information from audio, including speech recognition, music description, and environmental sound processing. He also runs the AUDITORY email list of 1700 worldwide researchers in perception and cognition of sound.

You can also review the discussion on Twitter by searching for the hashtag #rwob.