Due to technical difficulties, the DataONE webinar is not available in recorded format. This recording reflects similar content presented in September 2017. We are working to make available the same content as was presented on Dec 12 2017. Unfortunately, the panel discussion will not be available.
Usage and citation metrics are essential to gauging reach and measuring the impact of data. Currently, groups are focused on determining best practices in data citation and linking data with publications. However, in order for data to be considered a first class research output, we must also build a common standard to measure how often data is being used. The Make Data Count (MDC) project is funded by the Alfred P. Sloan Foundation to develop and deploy the social and technical infrastructure necessary to elevate data to a first-class research output alongside more traditional products, such as publications. We plan to do so by finding alternative ways of gauging reach, measuring impact for data, and building data level metrics (DLMs). The MDC project plans to not just focus on citations and usage but also building out a technical hub so that information does not get left behind as it can with article. As the field gets more mature we expect metrics and usage stats to be fed into the DLM hub. To accomplish this we have drafted the first iteration of a COUNTER Code of Practice for Data Usage surrounding data usage statistics for community input. Once this first iteration of standards for data usage has been formalized we will be building out a DLM hub using Lagotto, and enlist the cooperation of the research, library, funder, and publishing stakeholder communities to implement DLMs across DataCite repositories and drive adoption of DLMs.