Reproducible Analyses

 

Toward a 21st Century National Data Infrastructure: Managing Privacy and Confidentiality Risks with Blended Data

Protecting privacy and ensuring confidentiality in data is a critical component of modernizing our national data infrastructure. The use of blended data - combining previously collected data sources - presents new considerations for responsible data …

Towards building a trustworthy pipeline integrating Neuroscience Gateway and Open Science Chain

When the scientific dataset evolves or is reused in workflows creating derived datasets, the integrity of the dataset with its metadata information, including provenance, needs to be securely preserved while providing assurances that they are not …

Towards reproducible radiomics research: introduction of a database for radiomics studies

Objectives To investigate the model-, code-, and data-sharing practices in the current radiomics research landscape and to introduce a radiomics research database. Methods A total of 1254 articles published between January 1, 2021, and December 31, …

Transparency, replicability, and discovery in cognitive aging research: A computational modeling approach

Healthy aging is associated with deficits in performance on episodic memory tasks. Popular verbal theories of the mechanisms underlying this decrement have primarily focused on inferred changes in associative memory. However, performance on any task …

Transparent and Open Social Science Research course

Demand is growing for evidence-based policy making, but there is also growing recognition in the social science community that limited transparency and openness in research have contributed to widespread problems. With this course, you can explore …

Understanding Bayes: Visualization of the Bayes Factor

An abstract about Understanding Bayes and visualising Bayes Factor

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 …