In my last post, I talked about the state of retractions in the literature and how so much of the literature includes authors who probably unknowingly cites retracted works As journals (possibly even peer reviewers) are increasingly screening citations for retractions, it might be also a good idea to do your own screening before you submit your manuscript to avoid embarrassment.

Chinese translated version available here In terms of cross disciplinary citation indexes that are used for discovery, everyone knows of the two incumbants — Web of Science and Scopus(2004) . Joined by the large web scale Google Scholar (2004) , these three reigned as the “Big 3” of citation indexes for roughly a decade more or less unchallenged.

As always I am on the lookout for new interesting discovery applications and search engines, and in this blog post I will briefly mention and describe (not a full blown review) the following new ones that caught my eye.  Internet Archive's Fatcat & Internet Scholar Archive OpenAIRE Research Graph Open Research Knowledge graph Orion Search - Open source funding by Mozilla.

So it is Open Access Week 2020, while I write quite a bit on Open Access and Open Data, I don't often post specifically for Open Acess Week.

Do note what follows is my own personal reflections while working on I4OA and may not represent the views or opinions of I4OA as a whole. Last month I4OA - the Initiative for Open Abstracts was launched.  The mission of I4OA is simple as stated on the home page Founding members and individuals of I4OA included representatives from Scholarly publishers e.g. Sage Publishing, Royal Society

As a academic librarian, iinterested in discovery, I have always been a bit skeptical about the value and usefulness of graph based techniques for enhancing discovery. Sure, they look cool, but are they actually useful? Part of this belief stems from over-hyped but poorly implemented commericial search interfaces of the past that incorporate graphs as well as the failure of early library linked data efforts to capture the

Two years ago in 2018 I started to realise  the importance and value of Data discovery and slowly began studying various challenges to making Datasets discoverable. Google eventually launched Google dataset search, while Crossref, DataCite began to work together to enable linking of DOIs between Journal articles with Crossref dois and datasets with DataCite dois.

Update Nov 2021 - A relook at GetFTR , Libkey, Exlibris Quicklinks, and other linking and authentication technologies While allowing users to gain access to paywalled academic content aka delivery services is often seen to be less sexy than discovery it is still an important part of the researcher workflow that is worth looking at. In particular, I will argue that in the past few years we have seen a renewed

https://www.leidenranking.com/ranking/2020/list Recently the CWTS Leiden Rankings for 2020 was released and like many institution rankings , it used common research indicators such as More importantly it included less commonly seen indicators like Open Access Indicators and Gender Indicators.

My apologies for the little deception in the last blost post.

Why GPT-3 might be the greatest disruption to libraries since Google tags : tech, machine-learning, academic libraries Summary : I share my early experiments with OpenAI's new language prediction model (GPT-3) beta. I explain why I think GPT-3 has potential to disrupt academic librarians