Research Data Management: The Benefits of Sharing Data

Benefits to data creators

• Wider dissemination of research findings: there is evidence that journal articles for which the underlying data has been made available receive a boost to their citation count.
• Increased credit and recognition: data is a research output itself which can be cited like a published paper, crediting the researcher who produced it. This in turn can be used to help demonstrate research impact, and allows researchers to get proper acknowledgement for this portion of the work.
• Demonstration of research integrity: sharing the data which underpins research findings helps to clarify how that research has been conducted, and how conclusions were arrived at.

Benefits to the wider academic community

• Reduced duplication of effort: if data is made available to others, considerable time, money and resources can be saved by not re-collecting data that already exists.
• Speeding up research: pooling shared data may help researchers answer their research questions more rapidly. If this permits a larger body of data to be analysed, conclusions may also be more robust.
• Stimulation of additional research: shared datasets can provide inspiration for new work, or may make possible a project that would not otherwise have been achievable.
• Aiding research reproducibility: having access to the underlying data makes it easier for other researchers to see how conclusions were arrived at.

Benefits to funding bodies

• More efficient use of funding: if data from earlier projects is available, funders do not have to pay for additional data collection when this is unnecessary.
• Better return on investment: it is rare for the full value of a dataset to be exploited by a single project. If the same dataset can be used in multiple endeavours, more research can be achieved for the same outlay.

These benefits may also make research projects which plan to share their data more attractive to funding bodies, resulting in another potential benefit to researchers who opt to do this.

Researchers are sometimes concerned that their data will be misused, or that it will be used only to question the original analysis. However, in practice, this is rare. Researchers can reduce the risk of misinterpretation of their work by ensuring that data is well documented, and including clear methods information helps make it straightforward for other researchers to validate their conclusions. But shared data is also frequently used in ways not envisaged by the data creator: the focus may be on variables or aspects of the dataset deemed unimportant for the original project, for example, or the data may turn out to be valuable to researchers in another discipline, or may provide inspiration in terms of content or methodology.

Source: Research Data Oxford