Practical open science: tools and techniques for improving the reproducibility and transparency of your research

Science progresses through critical evaluation of underlying evidence and independent replication of results. However, most research findings are disseminated without access to supporting raw data, and findings are not routinely replicated. Furthermore, undisclosed flexibility in data analysis, such as incomplete reporting, unclear exclusion criteria, and optional stopping rules allow for presenting exploratory research findings using the tools of confirmatory hypothesis testing. These questionable research practices make results more publishable, though it comes at the expense of their credibility and future replicability. The Center for Open Science builds tools and encourages practices that incentivizes work that is not only good for the scientist, but also good for science. These include open source platforms to organize research, archive results, preregister analyses, and disseminate findings. This poster presents an overview of those practices and gives practical advice for researchers who want to increase the rigor of their practices.