Adjacent research areas and starting papers, curated in Semble and synced into the site.
Home | Bellingcat's Online Investigation Toolkit
A toolkit for open source researchers
[109] Data Falsificada (Part 1): "Clusterfake" - Data Colada
This is the introduction to a four-part series of posts detailing evidence of fraud in four academic papers co-authored by Harvard Business School Professor
Semble — A social knowledge network for research
Follow your peers' research trails. Surface and discover new connections. Built on ATProto so you own your data.
About CRDTs • Conflict-free Replicated Data Types
Resources and community around CRDT technology — papers, blog posts, code and more.
A Short Guide to Data Strikes and Conscious Data Contribution in the Context of 2026 Frontier AI
Back to the basics of data leverage.
Media Bias/Fact Check News
We are the most comprehensive media bias resource on the internet. There are currently 3900+ media sources listed in our database and growing every day.
Verification Handbook | DataJournalism.com
This book equips journalists with the knowledge to investigate on disinformation and media manipulation.
DASL — Data-Addressed Structures & Links
A small set of simple, standard primitives to work on content-addressed data.
DASL — Data-Addressed Structures & Links
A small set of simple, standard primitives to work on content-addressed data.
Wikipedia:Reliable sources/Perennial sources
This is a non-exhaustive list of sources whose reliability and use on Wikipedia are frequently discussed. This list summarizes prior consensus and consolidates links to the most in-depth and recent discussions from the reliable sources noticeboard and elsewhere on Wikipedia.
Sensors, not just bookmarks [Patterns of Sensemaking #1] - Cosmik Labs
First of a new series on sensemaking patterns we're observing on Semble
Datacurve | The data engine for frontier AI
Custom data for long-horizon reasoning, software engineering, and data science.
Connecting with your readers on Semble [Patterns of Sensemaking #2] - Cosmik Labs
On how the references you make help your writing find its natural audience
Why Most Published Research Findings Are False
Summary There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.
GRN · German Reproducibility Network
Working together for trustworthy and useful research