Improve your Research Profile (3): Getting savvy about data sources & metrics

The third in an 8-part series on improving your research profile, reputation and impact. Gives you a "crash course" on data sources and metrics for citation impact.

This presentation is part of an 8-part series that I created in my role as Staff Development Lead at Middlesex University (see: Supportive, inclusive & collaborative research cultures). The series is comprised of three key parts:

All you ever wanted to know about...

This third presentation will take you on a crash course about data sources and metrics for citation analysis. After watching it you'll know more about citation analysis than 99% of the academics ;-). I will explain how different data sources and different research metrics paint a very different picture of research performance across disciplines and why is it so important to be aware of these differences.

I will also argue that metrics are not inherently evil. Academics often compare an idealist version of peer review (informed, dedicated, unbiased experts) with a reductionist version of metrics (Web of Science h-index or citations). A metrics-informed peer-review process might in fact be helpful to counteract the gender/ethnic/language/disciplinary biases in peer review. Watch the presentation to find out more.

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Other posts in this series