2026-06-09 –, AUDITORIUM
Registered Reports were created to improve openness and replicability in research. While they have gained in popularity over the past decade, they remain difficult to systematically identify and discover, hindering meta-science efforts to evaluate them at scale. To address this gap, we are developing a comprehensive living database of published Registered Reports. Since our 2025 hackathon, initial work focused on building a Zotero database, developing machine learning mechanisms for identifying and collecting Registered Reports, and defining processing terms/information to include in the database. Our hackathon will build directly on this foundation. Participants will collaborate to improve data collection pipelines, improve tagging and metadata standards, expand database coverage across journals and disciplines, and address sustainability, versioning, and long-term maintenance. The goal is to develop a robust, scalable, community-driven resource that enables reliable discovery and reuse of Registered Reports for researchers, meta-researchers, and the broader scientific community.
The main deliverable from this hackathon will be a functioning database of all published Registered Reports. However, that is the long term deliverable. The more immediate/short term deliverable will be the creation of a usable (though likely incomplete) public zotero database, identification of maintenance strategies, and a working group that will continue the project after SIPS 2026 is over.
How will the session's content foster diversity & inclusion (e.g., who will present, who will it serve), and how will it improve psychological science?:Presenters will include William Krenzer, Erin Buchanan, Amanda Montoya, and Lillian King. The hackathon will help to introduce Registered Reports and collaborative tool development to the participants. The product will help researchers seeking examples of Registered Reports, meta-scientists conducting research on Registered Reports, and journals publishing Registered Reports by increasing discoverability.
Please note any pre-requisite knowledge/expertise you will expect from attendees (i.e., is the session most appropriate for someone who already has experience with a topic?).:No prerequisites for this hackathon. Experience with programming (e.g., R, Python, C++), databases (SQL, DataStudio), reference management software (e.g., Zotero, EndNote), and/or registered reports (i.e., knowing what they are) would be of great benefit to the team! Any and all are welcomed to attend and contribute, as we will have tasks that rely on different skill sets.
I am currently a Professor of Cognitive Analytics at Harrisburg University of Science and Technology - a STEM school in Pennsylvania. I teach computational linguistics courses in our Analytics and Data Science programs, such as Natural Language Processing, Sentiment Analysis, and Human Language. I also teach a bunch of statistics courses and you can learn more about my stats work on my website aggieerin.com
