In this RCE Podcast, Brock Palen and Jeff Squyres discuss Reproducible Neuroscience with RCE Podcast Chris Gorgolewski from Stanford. "In recent years there has been increasing concern about the reproducibility of scientific results. Because scientific research represents a major public investment and is the basis for many decisions that we make in medicine and society, it is essential that we can trust the results. Our goal is to provide researchers with tools to do better science. Our starting point is in the field of neuroimaging, because that’s the domain where our expertise lies."
Join our panelists for a discussion on challenges and opportunities related to sharing and using open data in research, including meeting funder and journal guidelines.
A webinar on the challenges of reproducibility in data scarce fields.
Adolescence is a period of human brain growth and high incidence of mental health disorders. In 2016 the Neuroscience in Psychiatry Network published a study of adolescent brain development which showed that the hubs of the structural connectome are late developing and are found in association cortex (http://dx.doi.org/10.1073/pnas.1601745113). Furthermore these regions are enriched for genes related to schizophrenia. In this presentation Dr Kirstie Whitaker will demonstrate how this work is supported by open data and analysis code, and that the results replicate in two independent cohorts of teenagers. She will encourage Brainhack-Global participants to take steps towards ensuring that their work meets these standards for open and reproducible science in 2017 and beyond.
As a principal investigator, how do you run your lab for reproducibility? I submit the following action areas: commitment, transparency and open science, onboarding, collaboration, community and leadership. Make a public commitment to reproducible research—what this means for you could differ from others, but an essential core is common to all. Transparency is an essential value, and embracing open science is the best route to realize it. Onboarding every lab member with a deliberate group “syllabus” for reproducibility sets the expectations high. What is your list of must-read literature on reproducible research? I can share mine with you: my lab members helped to make it. For collaborating efficiently and building community, we take inspiration from the open-source world. We adopt its technology platforms to work on software and to communicate, openly and collaboratively. Key to the open-source culture is to give credit—give lots of credit for every contribution: code, documentation, tests, issue reports! The tools and methods require training, but running a lab for reproducibility is your decision. Start here–>commitment.
This blog is based on part of a talk I gave in January 2017, and the thinking behind it, in turn, is based on my view of a series of recent talks and blogs, and how they might be fit together. The short summary is that general software reproducibly is hard at best, and may not be practical except in special cases.
A poster by Rebecca Davies in the field of Veterinary Medicine.
There are many actions researchers can take to increase the openness and reproducibility of their work. This introductory webinar from the Center for Open Science is aimed at faculty, staff, and students involved in agricultural research. Participants will gain a foundation for incorporating reproducible, transparent practices into their current workflows.
There is growing interest in research transparency and reproducibility in economics and other scientific fields. We survey existing work on these topics within economics and discuss the evidence suggesting that publication bias, inability to replicate, and specification searching remain widespread problems in the discipline. We next discuss recent progress in this area, including improved research design, study registration and pre-analysis plans, disclosure standards, and open sharing of data and materials, and draw on experiences in both economics and other social sciences. We discuss areas where consensus is emerging on new practices as well as approaches that remain controversial and speculate about the most effective ways to make economics research more accurate, credible, and reproducible in the future.
A ReproZip demo has been accepted at SIGMOD 2016: "ReproZip: Computational Reproducibility With Ease." F. Chirigati, R. Rampin, D. Shasha, and J. Freire. Shape Modeling International (SMI 2016) Introduces Reproducibility Award http://www.geometrysummit.org/smi2016/index.html 2016-02-29 reproducibility conference This year, also SMI will introduce an Award for Reproducibility to be granted to authors of accepted papers who are willing to provide a complete open-source implementation of their algorithm. The reproducibility stamp does not affect the reviewing process or the requirements for your submission to be accepted. The awarded papers will receive an additional 5 to 10 minutes in their presentation to give a live demo and will be recognized during the SMI closing ceremony. More information on the web site soon.