Reproducible Analyses

 

Understanding the provenance and qualityof methods is essential for responsible reuseof FAIR data

Data availability and reusability are critical to open research. The FAIR principles provide a minimal set of guiding principles for making data findable, accessible, interoperable and reusable. Open data are not necessarily FAIR, and FAIR data are …

Using the 'Transparency Checklist Guidelines' as an Educational tool

As an educational tool, the Checklist can be used to teach and improve the standards of transparency and credibility in research reports made by students. The aim is that students are embedded in transparent and open practices from the beginning of …

What does research reproducibility mean?

The language and conceptual framework of “research reproducibility” are nonstandard and unsettled across the sciences. In this Perspective, we review an array of explicit and implicit definitions of reproducibility and related terminology, and …

When is science (un)reliable?

In this course, we will explore the so‐called “reproducibility crisis” that has struck fields from psychology and economics to ecology and cancer biology. You will learn statistical principles at the heart of the reproducibility crisis, how disregard …

You are not so smart

Psychology is working on the hardest problems in all of science. Physics, astronomy, geology — those are easy, by comparison. Understanding consciousness, willpower, ideology, social change – there’s a larger-than-Large-Hadron-Collider level of …

ZooTraits: An R shiny app for exploring animal trait data for ecological and evolutionary research

Animal trait data are scattered across several datasets, making it challenging to compile and compare trait information across different groups. For plants, the TRY database has been an unwavering success for those ecologists interested in addressing …
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