Establishing a low-threshold data checkout system using REDCap, to facilitate preregistration and Registered Reports for pre-existing data

Preregistration, Registered Reports, and data sharing are all open science initiatives to increase transparency, reproducibility, and replicability in scientific research. Yet, there is a tension between making data completely open and preserving “naivety” about data to prevent data dependent decision-making. Preregistration and Registered Reports both require researchers to have minimal knowledge of the data prior to analysis and to be able to provide detailed descriptions and, in some cases, proof of prior data knowledge and access. Especially in situations where large datasets are used to answer different research questions by many researchers over time, minimising researchers’ knowledge of pre-existing data – and documenting it – is challenging. A data checkout system, which operates similar to a library, has been proposed as a solution to this. Here we present a low-threshold data checkout system designed and operated via REDCap, which allows data access to be controlled and provides proof of researchers’ data access history. A series of linked, online questionnaires prompt researchers to submit an abstract and a detailed variable access request, before variables are checked-out to researchers by a data manager. A custom dataset is then released to the researcher with a time and date-stamped receipt. A researchers’ data access record can also be produced to submit with a Stage 1 Registered Report, as evidence that data have not yet been accessed. In this presentation, the design and implementation of the data checkout system will be discussed, as well as the opportunities and challenges created by using such a system. unknown