Keynote Address: Victoria Stodden
Victoria is an assistant professor of Statistics at Columbia University. She completed her PhD in statistics and her law degree at Stanford University. Her research centers on the multifaceted problem of enabling reproducibility in computational science. This includes studying adequacy and robustness in replicated results, designing and implementing validation systems, developing standards of openness for data and code sharing, and resolving legal and policy barriers. She is the developer of the award winning "Reproducible Research Standard," a suite of open licensing recommendations for the dissemination of computational results.
She is a co-founder of http://www.RunMyCode.org, an open platform for disseminating the code and data associated with published results, and enabling independent and public cloud-based verification of methods and findings.
She is the creator and curator of SparseLab, a collaborative platform for reproducible computational research in underdetermined systems.
We are pleased to welcome the following panelists who will discuss specific tools and technologies for data-intensive research.
Michael Conlon, PhD
Principal Investigator, VIVO
VIVOis an open-source software system, a network of investigators and institutions, and an open information representation model for scholarship. Scholars using VIVO are able to find other scholars and their work.
Carly Strasser, PhD
Data Curation Specialist, CDL - California Digital Library
DMPTool(The Data Management Planning Tool) helps researchers create and manage data management plans, which facilitate good data stewardship and are now required by most funding agencies.
REDCap Administrator & Program Coordinator
Vanderbilt Institute for Clinical and Translational Research
REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing: 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources.
Melissa Haendel, PhD
Ontologist for eagle-i
Oregon Health & Science University Library
Department of Medical Informatics & Clinical Epidemiology
eagle-i is an innovative suite of applications that makes it easy to both discover and share biomedical resources at participating universities, helping investigators accelerate their research and collaborate. The platform is semantically engineered for maximal linking of research resources to other biomedical entities. eagle-i is working with VIVO to build a common ontology to further support research profiling leveraging data across the two systems.