Dubin, Stodden lead session at RDA Fifth Plenary Meeting

David Dubin
David Dubin, Teaching Associate Professor

Research Associate Professor David Dubin and Associate Professor Victoria Stodden participated in the Fifth Plenary Meeting of the Research Data Alliance (RDA), held March 8-11 in San Diego. They organized a session on the use of provenance encoding vocabularies for supporting research replication, with discussions focused on a use case in the field of epidemiology.

The session was jointly presented by the Research Data Provenance Interest Group (co-chaired by Dubin and Bridget Almas of Tufts University) and the Reproducibility Interest Group (co-chaired by Stodden and Bernard Schutz of the Max Planck Institute for Gravitational Physics).

Held twice annually, RDA plenary meetings provide opportunities for participants to develop connections and collaborations, and to discuss trends and innovations in research data sharing. The Fifth Plenary focused specifically on the outputs of RDA working groups and on encouraging external organizations to adopt data sharing practices set forth in those outputs.

Dubin has been a member of the GSLIS faculty since 1996. His current research interests include the foundations of information representation and description and issues of expression and encoding in documents and digital information resources. Currently, he teaches courses on information organization and access and ontology development. He has previously taught at GSLIS on topics including data analysis, information processing, data structures, library automation, and research methods. He holds a PhD in information science from the University of Pittsburgh as well a master’s degree in library and information science and a bachelor’s degree in humanities and communications from Drexel University.

Stodden joined the GSLIS faculty in Fall 2014. She is a leading figure in the area of reproducibility in computational science, exploring how can we better ensure the reliability and usefulness of scientific results in the face of increasingly sophisticated computational approaches to research. Her work addresses a wide range of topics, including standards of openness for data and code sharing, legal and policy barriers to disseminating reproducible research, robustness in replicated findings, cyberinfrastructure to enable reproducibility, and scientific publishing practices. Stodden earned a PhD in statistics and a law degree from Stanford University. She also holds a master’s degree in economics from the University of British Columbia and a bachelor’s degree in economics from the University of Ottawa.

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