A webinar on the challenges of reproducibility in data scarce fields.
The University of Minnesota Libraries addressed this issue head-on this year by launching the reproducibility portal in an effort to help faculty and others on campus improve their research practices. The portal is a collaboration that includes Liberal Arts Technology and Information Services (LATIS) and the Minnesota Supercomputing Institute (MSI).
A preview of ReproZip by Vicky Steeves at the PresQT Workshop May 1, 2017 at the University of Notre Dame.
Introduce the python environment wrapper and packing tools; virtualenv & pip. Show you how you can stay up to date by using in requires.io egg security and update checking. Cover Fabric a python deployment tool and wider systems and workflow replication with Vagrant and Reprozip.If time allowing touch upon test driven development and adding Travis to your project.
Accumulating evidence suggests that many findings in psychological science and cognitive neuroscience may prove difficult to reproduce; statistical power in brain imaging studies is low, and has not improved recently; software errors in common analysis tools are common, and can go undetected for many years; and, a few large scale studies notwithstanding, open sharing of data, code, and materials remains the rare exception. At the same time, there is a renewed focus on reproducibility, transparency, and openness as essential core values in cognitive neuroscience. The emergence and rapid growth of data archives, meta-analytic tools, software pipelines, and research groups devoted to improved methodology reflects this new sensibility. We review evidence that the field has begun to embrace new open research practices, and illustrate how these can begin to address problems of reproducibility, statistical power, and transparency in ways that will ultimately accelerate discovery.
Background: The reproducibility of research is essential to rigorous science, yet significant concerns of the reliability and verifiability of biomedical research have been recently highlighted. Ongoing efforts across several domains of science and policy are working to clarify the fundamental characteristics of reproducibility and to enhance the transparency and accessibility of research. Methods: The aim of the proceeding work is to develop an assessment tool operationalizing key concepts of research transparency in the biomedical domain, specifically for secondary biomedical data research using electronic health record data. The tool (RepeAT) was developed through a multi-phase process that involved coding and extracting recommendations and practices for improving reproducibility from publications and reports across the biomedical and statistical sciences, field testing the instrument, and refining variables. Results: RepeAT includes 103 unique variables grouped into five categories (research design and aim, database and data collection methods, data mining and data cleaning, data analysis, data sharing and documentation). Preliminary results in manually processing 40 scientific manuscripts indicate components of the proposed framework with strong inter-rater reliability, as well as directions for further research and refinement of RepeAT. Conclusions: The use of RepeAT may allow the biomedical community to have a better understanding of the current practices of research transparency and accessibility among principal investigators. Common adoption of RepeAT may improve reporting of research practices and the availability of research outputs. Additionally, use of RepeAT will facilitate comparisons of research transparency and accessibility across domains and institutions.