Democratizing Data

Democratizing Data builds a community-driven data ecosystem by identifying how datasets are used and reducing barriers to accessing high-quality public data. The initiative enhances the discoverability, usability, and relevance of data for researchers, policymakers, and stakeholder communities. A suite of tools and strategic partnerships supports this work by connecting users to the data, insights, and networks needed to inform decisions and generate impact.

Collective Social | Track what you love. Share what matters.

Curate lists, track your progress, and share recommendations across books, movies, TV shows, and more — all on the open social web.

Reviewing post-publication peer review

Post-publication peer review (PPPR) is transforming how the life sciences community evaluates published manuscripts and data. Unsurprisingly, however, PPPR is experiencing growing pains, and some elements of the process distinct from standard pre-publication review remain controversial. I discuss the rapid evolution of PPPR, its impact, and the challenges associated with it.

Coding Club: a positive peer-learning community

Free and accessible tutorials on data analysis, manipulation, visualisation and more.

Data Is Plural

A weekly newsletter of useful/curious datasets.

Deepnote: Collaborative analytics & data science notebook

Explore data with Python & SQL, work together with your team, and share insights that lead to action — all in one place with Deepnote.

RegCheck: A tool for structured comparisons between study registrations and papers

Across the social and medical sciences, researchers recognize that specifying planned research activities (i.e., 'registration') prior to the commencement of research has benefits for both the transparency and rigour of science. Despite this, evidence suggests that study registrations frequently go unexamined, minimizing their effectiveness. In a way this is no surprise: manually checking registrations against papers is labour- and time-intensive, requiring careful reading across formats and expertise across domains. The advent of AI unlocks new possibilities in facilitating this activity. We present RegCheck, a modular LLM-assisted tool designed to help researchers, reviewers, and editors from across scientific disciplines compare study registrations with their corresponding papers. Importantly, RegCheck keeps human expertise and judgement in the loop by (i) ensuring that users are the ones who determine which features should be compared, and (ii) presenting the most relevant text associated with each feature to the user, facilitating (rather than replacing) human discrepancy judgements. RegCheck also generates shareable reports with unique RegCheck IDs, enabling them to be easily shared and verified by other users. RegCheck is designed to be adaptable across scientific domains, as well as registration and publication formats. In this paper we provide an overview of the motivation, workflow, and design principles of RegCheck, and we discuss its potential as an extensible infrastructure for reproducible science with an example use case.

Introduction to Open Science

This course introduces the principles and practices of open science, with an emphasis on reproducible research workflows, transparent reporting, and collaborative scholarship. Students will critically examine reproducibility, explore tools that support openness (such as Git, GitHub, and Quarto), and apply these tools in hands-on assignments and a final open project. Students will also explore how open science practices vary across disciplines, including education, humanities, social sciences, industry and government, and STEM contexts. This course emphasizes applying open science principles to real-world data problems in alignment with the principles of producing reproducible research.

Two billion citation links in Crossref help research travel further - Crossref

We’ve recently reached an important milestone for the research nexus: the works in our metadata corpus are now connected with over 2 billion citation links! This is a great opportunity to share a dedicated dataset and discuss why these are important for science.

DataColada: No Comments - Replicability-Index

Science is like an iceberg. The published record is only a fraction of the things that university -paid academics do. Some time ago, Brian Nosek dreamed about a scientific utopia of open science that would make the workings of academia more transparent, but all we got was preprints and some badges - that are apparently DataColada: Open Science, but Closed Comments?

The Consensus Trap: Dissecting Subjectivity and the “Ground Truth” Illusion in Data Annotation

As part of the Digital Library's transition to Open Access, new features for researchers are available in the Premium Edition. Click here to learn more.

communitycheck/design at main · rosestt/communitycheck

A design specification for attaching representative public opinion data to viral social media posts — correcting the gap between what people think and what they think others think. - rosestt/commun...

modular research preprint server demo with meaningful social context

a concept preprint server demonstrating what kinds of features would be possible in the future with more modular research publishing and an open social protocol to layer in the public discourse in meaningful ways.