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Just an idea I have about Research Analytics. So the Dutch government would like to see performance indicators by the Higher Education institutions. This information can be drawn from many silo's and just give the indicator. However, when the information from these silo's can be combined, more advanced analytic's can be drawn from this information by data and text mining techniques.
But the first step is to integrate the information in a scalable data infrastructure. Research information is not big data, but it is wise to think about scalability to overcome performance issues in the future.
Multiple sources provide the data with a daily update, such as repositories'metadata, web log files, altmetrics data, citation references, funding and grand information, etc. The information is calculated and implicit relations are made explicit. In he end it is provided as open data invarious formats, including RESTful API's. Services can draw information from these API's to base their services on. Examples are metrics and analytics services, but also resolution and information portals.
Clipping is a handy way to collect important slides you want to go back to later.