The Brown University Library is thrilled to announce a new partnership with the Carney Institute for Brain Science on two prizes for student work that exemplifies research rigor, transparency, replication, and reproducibility.
Library Innovation Prize
Drawing on the rising importance of rigor and reproducibility of research, the Brown University Library will award up to $750 for the creation of a publication, capstone paper, digital project, and/or thesis/dissertation that incorporates innovation in rigor and transparency in any field of research.
Carney Institute for Brain Science Undergraduate Student Prize
The Carney Institute for Brain Science is offering a parallel but independent undergraduate prize for a capstone paper or thesis within the general area of brain science that incorporates innovation in reproducibility.
Timeline & Registration
- Friday, March 13 at 2 p.m.: Informational meeting the Digital Studio Seminar Room (160) at the Rockefeller Library. (Attendance is not required but is strongly encouraged.)
- Wednesday, April 1, 2020: Deadline for registration for both prizes
- Saturday, May 2, 2020: Submissions from registered participants are due by 5 p.m.
- Week of May 18, 2020: Winners will be notified by email
- Dr. Jason Ritt, Scientific Director of the Carney Institute
- Lydia Curliss, Physical Sciences and Native American and Indigenous Studies Librarian
- Dr. Oludurotimi Adetunji, Associate Dean of the College for Undergraduate Research and Inclusive Science
Innovation in Reproducibility
An example of innovation in reproducibility is linking data, analysis code, and figures/visualizations within a single document file that can be opened, read, and executed by the panel of judges using commonly available, preferably open source applications (e.g., Jupyter notebooks in a generic web browser).
Rigor & Transparency
Projects with enhanced rigor and transparency could include:
- Curating and publicly sharing a data set
- Pre-registration and sharing of a protocol
- Sharing and containerization (e.g., Docker or Singularity) of analysis code and other computing environment related technologies
- Incorporating an “Annotation for Transparent Inquiry (ATI) Data Supplement” for transparency in qualitative data analysis
- Lewis, L. M., Edwards, M. C., Meyers, Z. R., Talbot, C. C., Jr., Hao, H., Blum, D., & Reproducibility Project: Cancer Biology. (2018). Replication Study: Transcriptional amplification in tumor cells with elevated c-Myc. ELife, 7, https://repro.elifesciences.org/example.html. GitHub: Source: https://github.com/elifesciences/rds-example
- Hinsen, Konrad (2011). A data and code model for reproducible research and executable papers. Procedia Computer Science, 4, https://doi.org/10.1016/j.procs.2011.04.061
- Whitaker, Kirstie (2017): Publishing a reproducible paper. figshare. Presentation: https://doi.org/10.6084/m9.figshare.4720996.v1
- Qualitative Data Repository (2019). Instructions for preparing and depositing an “Annotation for Transparent Inquiry (ATI) Data Supplement” accompanying a digital manuscript. Qualitative Data Repository. https://qdr.syr.edu/ati/ati-instructions
- Library prize contestants must be currently enrolled Brown undergraduate or graduate students. The Carney prize is restricted to Brown undergraduates.
- Projects may be created by individuals or teams. The projects should be new or created in the past calendar year (2019).
- There are no limits on coding languages or tools to create the reproducible paper.
- The research must be the contestants’ original work. You may submit original work that you complete for a capstone paper for a course or an honors thesis or thesis at Brown.
- Winning projects remain the intellectual property of the contestant(s), but the winning contestant(s) will grant a nonexclusive perpetual license to Brown University for its internal, non-commercial use.
- A panel of judges selected from faculty and Library staff will determine the winners.
- For additional information, please contact Andrew Creamer at firstname.lastname@example.org
- For questions on reproducible documents and their implementation, registered participants may contact Dr. Jason Ritt, Scientific Director of Quantitative Neuroscience in Brown’s Carney Institute for Brain Science at email@example.com. Dr. Ritt will provide general advising up to schedule availability. Advice will be provided as is, with no implication for contest judging or award outcomes.