Research Data Management (RDM) is an important competency that is beneficial for graduate and undergraduate students across the disciplines. Not only are many funding agencies requiring a Data Management Plan (DMP) for new grant proposals, there is also a shift toward data driven research, data driven analyses, data visualization and new distributed computational systems that use "big data". One piece of data management is metadata and the problems that insufficient or bad metadata can cause. Take, for example, a recent article in Science "Engaging over data on fracking and water quality". The authors discuss both the political and scientific side to the complexities of gathering disparate data sets and merging them into one online public database for high-volume hydraulic fracturing in Pennsylvania. A major problem with merging data sets is often related to a metadata issue, "Water data is particularly complex in comparison to ...". In this case, they are describing the problem of disparity in metadata; they found 13 different reporting conventions used for reporting nitrate. This is one example supporting the need for good data literacy and management, especially with the move to make data freely available to facilitate data verification, data reuse and duplication of experimental results.
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