Montana Kaimin, March 5, 1981

Student newspaper of the University of Montana, Missoula.https://scholarworks.umt.edu/studentnewspaper/8304/thumbnail.jp

Data recovery status definitions.

<p>Data recovery status definitions.</p

Final status of all data projects.

<p>Black bars are projects for which data were successfully acquired, grey bars represent projects for which no data were acquired.</p

Data recovery grouped by research field.

<p>Total successful (black) and unsuccessful (grey) data requests by research field. Asterisks indicate significant research fields.</p

Hurdles to recovery category definitions.

<p>Hurdles to recovery category definitions.</p

Reasons given for not providing data.

<p>Communication loss and lack of contact information were the main reasons data were not obtained.</p

A funder-imposed data publication requirement seldom inspired data sharing

<div><p>Growth of the open science movement has drawn significant attention to data sharing and availability across the scientific community. In this study, we tested the ability to recover data collected under a particular funder-imposed requirement of public availability. We assessed overall data recovery success, tested whether characteristics of the data or data creator were indicators of recovery success, and identified hurdles to data recovery. Overall the majority of data were not recovered (26% recovery of 315 data projects), a similar result to journal-driven efforts to recover data. Field of research was the most important indicator of recovery success, but neither home agency sector nor age of data were determinants of recovery. While we did not find a relationship between recovery of data and age of data, age did predict whether we could find contact information for the grantee. The main hurdles to data recovery included those associated with communication with the researcher; loss of contact with the data creator accounted for half (50%) of unrecoverable datasets, and unavailability of contact information accounted for 35% of unrecoverable datasets. Overall, our results suggest that funding agencies and journals face similar challenges to enforcement of data requirements. We advocate that funding agencies could improve the availability of the data they fund by dedicating more resources to enforcing compliance with data requirements, providing data-sharing tools and technical support to awardees, and administering stricter consequences for those who ignore data sharing preconditions.</p></div