I recently came across "Automated citation recommendation tools encourage questionable citations" (which was first brought to my attention by this blog post) an exceedingly thought-provoking article about bias in discovery tools, particularly new ones that can

With open scholarly data (metadata and full-text) becoming increasingly available, it is natural to see attempts to apply the latest deep learning techniques to try to see if one can ease the burden of doing literature review.

My blog usually takes the view that most of our users do not start at the library homepage as a truism and since the beginning of the blog in 2009, I have covered tools that help users "get back" to library resources or at least easily check for availability via their library catalogs or library discovery service.

I've been writing about the rise in availability of open Scholarly metadata (in particular Open Citations) as far back as 2018 and how they might impact academia.

I've always had an interest in bibliometrics, and while I have served in teams supporting bibliometrics in the past (2010-2015) and enjoy reading and skimming bibliometrics papers, I have never been officially given the title of a librarian supporting bibliometrics.

In late 2018, I gave a talk at OCLC Asia Pacific Regional Conference Meeting 2018 and I gave my thoughts on how I see the game changing for libraries in the years to come based on 3 fundamental trends.

Note: This is based off my contribution to the Upstream blog (plus some major additions)- Aaron Tay is Keeping Tabs on Open Research

Note: This is adapted from an internal talk I gave at my place of work.

If there is one academic discovery search that dominates it is Google Scholar.

Web of Science - Pilot- enhanced cited references In the recent years I have been blogging quite a bit about the idea of citation contexts (or citation intent or citation sentiment or...) in journal articles. While definitions and concepts might vary a little, the idea is not to simply just count citations but also try to figure out what they mean.

Since I started blogging about GPT-3 and language models, interest in this area has continued to increase.