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YARD: A Curation Workflow Tool

Yale’s platform for curating, reviewing, and archiving reproducible social science research data.

The Yale Application for Research Data (YARD) is an open-source web application developed by the Institution for Social and Policy Studies (ISPS) at Yale University to enhance the transparency, reproducibility, and long-term usability of social science research. Designed primarily for randomized trials, YARD structures the data curation and code review workflow, enabling researchers to upload files for pre-publication review and deposit them into the ISPS Data Archive.

The platform supports curators in replicating analyses, validating results, and ensuring that research outputs are well-documented and free of personally identifiable information. YARD facilitates the creation of high-quality, repository-agnostic data packages that can be ingested into any archive. Developed in partnership with Innovations for Poverty Action and Colectica, and supported by Yale’s IT and library services, YARD connects researchers, curators, and publishers through a unified pipeline. It is currently deployed on Yale infrastructure and tailored for use by ISPS affiliates.

In this video, YARD Software Development PI Limor Peer PhD, describes the tool and its uses.

Limor Peer PhD
Associate Director for Research and Strategic Initiatives at the Institution for Social and Policy Studies (ISPS), and Open and Reproducible Research Program Lead at the Data-Intensive Social Science Center (DISSC), Yale University

Research projects

A Future of Unmanned Aerial Vehicles
Yale Budget Lab
Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute - Unlocking Intelligence
The Institute for Experiential AI
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
SEQer - Sequence Evaluation in Realtime
Revolutionizing Materials Design with Computational Modeling
Remote Sensing of Earth Systems
Quantum Computing in Renewable Energy Development
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
New Insights on Binary Black Holes
NeuraChip
Network Attached FPGAs in the OCT
Monte Carlo eXtreme (MCX) - a Physically-Accurate Photon Simulator
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Genome Forecasting
Global Consequences of Warming-Induced Arctic River Changes
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Energy Transport and Ultrafast Spectroscopy Lab
Electron Heating in Kinetic-Alfvén-Wave Turbulence
Discovering Evolution’s Master Switches
Dexterous Robotic Hands
Developing Advanced Materials for a Sustainable Energy Future
Detecting Protein Concentrations in Assays
Denser Environments Cultivate Larger Galaxies
Deciphering Alzheimer's Disease
Dancing Frog Genomes
Cyber-Physical Communication Network Security
Asteroid Data Mining
Analyzing the Gut Microbiome
Adaptive Deep Learning Systems Towards Edge Intelligence
Accelerating Rendering Power
ACAS X: A Family of Next-Generation Collision Avoidance Systems
Computation + Machine Intelligence | Wu Tsai Institute
Computational Modeling of Biological Systems
Computational Molecular Ecology
Social Capital and Economic Mobility
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Collaborative projects

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OUTREACH & EDUCATION PROJECTS

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