"Research is all about testing and re-testing ideas, tools, methods and concepts. In the past it wasn’t easy to make available the details of how research was done but today we have the ability to share software, analysis, data, and computational tools” says Open Research Computation Editor-in-Chief and open data proponent Cameron Neylon.
With the growth of open movements during the last decade, the biomedical world has seen increasing awareness of the benefits of open data and data-sharing. This is in part due to a shift towards data-intensive science, but also due to the realization that much can be achieved by the pooling of resources and through scientific collaboration.
To promote and support open data in science, BMC Research Notes has been publishing an ongoing thematic series to endorse the practice of publishing underlying data files associated with journal articles in standard, reusable formats. This endorsement is further supported by Biosharing, who encourage authors to submit educational Data Notes which can then be linked to the BioSharing catalogue.
A recently published article which examines the BrainMap project demonstrates how neuroimaging data standards are now being utilized. This project provides the human brain mapping community with datasets and computational tools to establish a basis for neuroimaging-based models of healthy brain function. Another recent study provides data standardization for cancer therapy development for the first time; the Guidelines for Information About Therapy Experiments (GIATE) is a minimum information checklist which provides a consistent framework to transparently report the purpose, methods and results of the therapeutic experiments.
Other well-annotated and reusable datasets highlight the advantages of data-sharing and standardization, such as the immense benefits of cost savings which can then be re-invested into further research; the comparisons that can be drawn between different models; and the flexibility of form and function of such web-based Data Notes.
Despite continuing obstacles to the development of data-sharing, such as patient confidentiality and an eagerness on the investigator’s part to protect their financial investment and rights to their data, it seems that a lot can be accomplished through data standardization and scientific collaboration. In light of this, we are seeking to collate even more of these high-quality examples of novel datasets, in order to build on the promising achievements of this thematic series so far.
To discuss submission of your standardized dataset or to propose a contribution on other aspects of data-sharing and open data, please contact email@example.com.