YARD is an open-source web application for reviewing and enhancing research outputs.
YARD for Researchers
Why use YARD?
YARD facilitates the production and sharing of quality research outputs to advance research reproducibility and transparency.
Many researchers seek to share data and other research outputs (e.g., analysis code) with the scientific community, and some may be required to do so. These days, sharing data is becoming easier and good repositories or archive options are available. But, shared materials may not be usable and scientific claims may not be reproduced using the available data.
YARD offers a way to easily upload files for pre-publication review, seamlessly deposit them into a data archive or repository, and ensures that the research products they share are well documented and their results are computationally reproducible.
YARD connects researchers, data curators, and publishers through a single pipeline for the purpose of improving research transparency, reproducibility, and long-term use.
How does YARD work?
The short version:
YARD structures and records all curation and review actions, integrates and captures DDI metadata production with curation and review, and directs processed data packages to pre-specified destinations for publication.
The longer version:
Upon deposit, a safe copy of the research materials are created and deposited in a dark archive. A public copy of the files is created and used for processing. Processing includes generating study-level and file-level metadata, confirming all variables and values are labeled, standardizing missing values, creating and augmenting documentation, assessing and minimizing disclosure risk by applying techniques such as recoding, masking, or removal of variables, and assigning persistent links. The review of code files—statistical and other programming scripts—includes verifying that the code executes and that the published scientific results can be reproduced with the given code and data. The data and code review processes include an assessment of the quality of documentation and contextual information necessary for long-term usability (for example, a codebook, a README file, a commented code). In cases where these are found lacking or insufficient, the archive or repository works with researchers on remedial actions. All file formats are normalized (including migrating software-specific data files to flat file formats such as ASCII, text, or comma delimited and rewriting code written using licensed statistical software such as SPSS to open-source statistical languages such as R). All files are assigned a unique identifier (handle), and files sets have citation information. After completion of the process, materials are stored and made publicly available via a pre-specified destination.
Click on the link below for background on the YARD project.
Interested in using YARD?
YARD can support multiple organizations with separate instances administered independently. A YARD “instance” is an organization-specific configuration of the software.
Are you at Yale University?
At Yale, the tool as currently configured is feeding into the Institution for Social and Policy Studies’ ISPS Data Archive and intended for the use of ISPS affiliates.
Click on the link below to learn about how YARD is used at ISPS.
Researchers, organizations, and departments at Yale interested in using YARD can contact digitalscholarship.services@yale.edu.
If you are not a member of the Yale community
You can still try YARD using our Sandbox environment. Experience YARD from a researchers’ point of view: describe and deposit research data via YARD.