Stanford University Libraries Data Sharing Prizes for 2024
We are pleased to announce the winners of the Stanford University Libraries Data Sharing Prizes for 2024. These awards recognize outstanding examples of impactful data sharing. Sharing research data:
- advances research rigor and reproducibility,
- enables reuse and new discoveries by others,
- recognizes data as a first-class research output, and
- requires expertise and dedicated effort.
The work involved in research data sharing is often unrecognized and undervalued. The Stanford Libraries Data Sharing Prizes highlight and celebrate researchers who:
- make their data available via an appropriate online repository,
- exemplify disciplinary best practices for making their data FAIR (findable, accessible, interoperable, reusable), and/or
- advance others’ research by sharing their own data.
The Stanford University Libraries are proud to offer these awards in support of CORES, the Stanford Center for Open and REproducible Science. Nominations are made each spring and awards are announced in conjunction with the CORES Annual Symposium.
The Stanford Libraries operate the Stanford Digital Repository, a repository for research data, articles, and other digital scholarly assets.
2024 Awards
Elana Chan
Ph.D. candidate, Civil & Environmental Engineering
Ms. Chan's ORCID iD (Open Researcher and Contributor iD)
Elana Chan is starting her research career with a conscious effort toward making her data and code easily accessible. Ms. Chan is a Civil and Environmental Engineering PhD candidate in the Boehm Research Group studying how wastewater monitoring data may be interpreted for public health action. To make it easy for monitoring programs to adopt the approaches presented in her first, first-author paper, Ms. Chan shared both the data and the software code through the Stanford Digital Repository. Her methods are currently being used to characterize trends for the WastewaterSCAN data dashboard. Ms. Chan recently published her second, first-author paper and shared the corresponding data and code by packaging them as an easily reusable R project with detailed documentation.
"There are still relatively few papers that make data and code publicly available and even among those that do, oftentimes findings are not reproducible," Ms. Chan writes. "I hope that by publishing my data and code alongside my research papers, I am helping transform the culture of data sharing!"
Highlighted Datasets
- Data and R code for trend and downsampling analysis of wastewater SARS-CoV-2 RNA paper
- Data and R code for policy impact evaluation using wastewater SARS-CoV-2 RNA concentrations paper
Blair Kaneshiro
Director of Research & Development with the Stanford Educational Neuroscience Initiative in the Graduate School of Education and Adjunct Professor of Music
Dr. Kaneshiro's ORCID iD (Open Researcher and Contributor iD)
Dr. Blair Kaneshiro, who uses brain and behavioral responses to better understand how we perceive and engage with music, sound, and images, has used the Stanford Digital Repository to share data and software from her research since 2015. She applies a suite of best practices to ensure easy data reuse, and researchers at Stanford and other institutions worldwide have utilized her datasets to investigate music reconstruction, tempo classification, onset detection, and song classification. Dr. Kaneshiro also incorporates data in her teaching, encouraging students to use shared data in course assignments and capstone projects.
Dr. Kaneshiro writes, "I view sharing of research resources such as data to be a valuable contribution to science, both to promote reproducible research and to give data 'new life' beyond what was envisioned when it was first collected. It has been fulfilling to see my own data be used to address new research questions, particularly by groups who may not otherwise have been able to collect the data themselves."
Highlighted Datasets
The Laboratory of Thomas C. Südhof
Avram Goldstein Professor Investigator, Howard Hughes Medical Institute; Professor, Dept. of Molecular & Cellular Physiology and of Neurosurgery; Professor (by courtesy), Dept. of Neurology & Neurological Sciences and of Psychiatry & Behavioral Science
Dr. Südhof's ORCID iD (Open Researcher and Contributor iD)
Dr. Südhof, who won the Nobel Prize for Physiology or Medicine in 2013, and his research team study how synapses form in the brain, how their properties are specified, and how neurological conditions may cause them to become dysfunctional. Researchers across the Südhof Lab consistently utilize both discipline-specific repositories and a collection in the Stanford Digital Repository to make the data they generate available to others, taking a deliberately transparent approach to their work.
Dr. Südhof was nominated by Professor Russ Poldrack and Zach Chandler of Stanford’s Center for Open and REproducible Science (CORES) who noted that Dr. Südhof and his colleagues “have blazed a trail for data sharing in a field where it remains uncommon.”
Dr. Südhof commented “Needless to say I am thrilled and grateful that my lab is selected for this award. It is not only personally rewarding for me, but also gives a big boost to my co-workers in the lab!”
Highlighted Dataset
For inquiries about the Stanford University Libraries Data Sharing Prizes, please contact the Stanford Libraries data sharing team.