There are generally four matters of data acquisition and management that need to be addressed at the outset of a study: (1) collection, (2) storage; (3) ownership, and 4) sharing.¹³

The first two matters—data collection and storage—directly pertain to data integrity. Chapter Two discussed the intentional publication of false data; however, false data may also be published unintentionally due to poor data acquisition methods or sloppy data management. Whether intentional or unintentional, many of the consequences of publishing false data are the same, such as polluting the scientific literature, compromising research and practices that build upon false data, and risking a lab investigation and paper retraction.

The matters of data ownership and sharing directly relate to the content of Chapter Three—Collaboration. Clarifying data ownership and sharing data with others are essential elements to successful research collaboration. Researchers need to be aware of who owns the data, tissue samples or other materials that they are studying. Government, private companies, foundations, and philanthropic organizations may have different scientific goals, obligations, and ownership stipulations. Distinguishing between grants and contracts is also important since they may have differing rules on ownership and restrictions on publishing.
Sharing data enables other researchers to replicate findings, thereby reinforcing the integrity of science. Further, it allows others to use data to advance science in a cost-effective manner. Regardless whether results are positive or negative, researchers are expected to disseminate research findings so that others can learn from and build upon information. Researchers who receive federal funding to explore a research question are expected to include a plan for sharing final research data for research purposes or to explain why this may not be possible.²²

The Cases and Role Play

The cases and role play in this chapter present common scenarios that occur at various stages of data acquisition and management. Issues discussed include acquiring sensitive data, sharing data with colleagues, and managing data collection processes.

• Case One: A researcher wants to sequence the genomes of children with cancer, eventually making them publicly available online, but encounters issues with adequate data protection and parental consent.
• Case Two: After working with her advisor to develop a sophisticated database, the postdoc wants access to the database in order to submit a grant proposal but runs into trouble when seeking the advisor’s permission.
• Case Three: A post-doc has a novel idea after observing a procedure during residency, but he needs access to a large amount of clinical data, including medical record numbers, so that he can eventually recruit individuals to participate in his research.
• Role Play: An assistant professor places her data on the NIH’s database of genotypes and phenotypes (dbGaP) only to find that a leading researcher has published a paper using the data shared in the NIH database before the one-year embargo period was up.