The development of new experimental technologies has opened the way to new, data-generative approaches to plant research, particularly within the genomics field but also high-throughput transcriptomics, proteomics and metabolomics. Furthermore, publication models are moving away from the traditional "data late" approach, and are shifting towards the "data early", with particular pressure being made by funding agencies to see data publicised quickly. Alongside the wealth of these large plant science datasets held in public and private laboratories around the globe, there are a large number of tools to help researchers disseminate, analyse and publish those datasets. However, the disparate nature of the tools, data formats and scientific problems in light of this expansive experimental development has resulted in a lack of interoperable, production-quality software available for data analysis and dissemination.
We present a newly funded project, Collaborative Open Plant Omics (COPO), to address this disparity in interoperability and easy access to important services in the 'omics data realm. We will develop a framework to utilise existing services to facilitate the description, deposition and publication of datasets, but also to enable the identification and citation of datasets, thereby increasing transparency and reproducibilty. Promoting reward for making data available is a central aim of the project.
All source code for the project is available via GitHub.