DNA repair and genetic stability: Elucidating the effects of cell physiology in Escherichia coli (360G-Wellcome-205008_Z_16_A)

One of the biggest problems for data re-use in Open Research is the quality of data description (metadata), which often lacks sufficient detail. The problem is acute in quantitative microscopy, which is the central method for my project to measure DNA repair proteins in living bacteria. A carefully-tuned sequence of image and data analysis steps is critical for us to count or track individual protein molecules. However, the intermediate results tend to become dispersed during the process. Each stage of analysis must be recorded and described to make the research reproducible, in addition to sharing the voluminous image data. Preparing our recent publication showed that our current manual process is error-prone and cripplingly slow. Here, we will develop a software platform that solves this problem, by linking the research tools that we use daily with existing, public and institutional repositories. First, the platform will collect automatically the necessary metadata at each step. Second, the platform will assemble comprehensively-described datasets. Third, it will make them automatically available for open access, on the University’s DataShare service. By developing a fully automated platform we will make open data sharing far easier and more accurate. The comprehensive data packages will be more valuable for re-use. The platform builds on established data-sharing resources, which are sustainable and will also make our methods and results easier to find. Finally, we will use the platform to share data with our collaborators thus improving working practices in other groups.