The public sharing of primary research datasets potentially benefits the research community but is not yet common practice. In this pilot study, we analyzed whether data sharing frequency was associated with funder and publisher requirements, journal impact factor, or investigator experience and impact. Across 397 recent biomedical microarray studies, we found investigators were more likely to publicly share their raw dataset when their study was published in a high-impact journal and when the first or last authors had high levels of career experience and impact. We estimate the USA's National Institutes of Health (NIH) data sharing policy applied to 19% of the studies in our cohort; being subject to the NIH data sharing plan requirement was not found to correlate with increased data sharing behavior in multivariate logistic regression analysis. Studies published in journals that required a database submission accession number as a condition of publication were more likely to share their data, but this trend was not statistically significant. These early results will inform our ongoing larger analysis, and hopefully contribute to the development of more effective data sharing initiatives. **Earlier version presented at ASIS&T and ISSI Pre-Conference: Symposium on Informetrics and Scientometrics 2009**

Microarray study attributes and data sharing status397 rows, one row for each study that created gene expression microarray data as identified by Ochsner et al. (doi:10.1038/nmeth1208-991). Attributes of each study are included in 23 columns. Dependent variable is called is_data_shared.Piwowar_Metrics2009_rawdata.csvStatistical analysis R scriptStatistical R script for analysis and graphics as presented in the paper.Piwowar_Metrics2009_statistics.R