The concept of ORCID (Open Researcher Contributor ID)  appears to be simple. The promise is to have a unique identifier for each researcher "the same way books have ISBN" . As a librarian who has helped researchers pull out citation counts from Scopus, Google Scholar in the past, the idea of ORCID seems elegant and logical.

We can all agree that Google Scholar has many strengths , but no matter how complete or deep it's indexing, how much better it is at finding free articles or it's presumed better relevancy ranking , we librarians have always had one weakness of Google Scholar to point at. We often say "Despite it's strengths, still we have to be careful, after all we don't know what Google Scholar actually includes, as they refuse to provide lists of

So I celebrate my 10th anniversary in  Academic librarianship at the end of this month - Aug 2017. Yes, I have been a academic librarian for 10 years, where did all the time go? When I first began as a librarian, the very first version of the iPhone had just launched in the US and Facebook had just opened access to the public a year ago, kicking off the mobile and social media revolution.

At my prior institution, I was the administrator of the discovery service - Summon and one of the features that I loved the most was the "best bets" and database recommender feature. If you are unfamiliar with what that does, it essentially allows you as a librarian to setup special notes/links/images to appear when they are triggered by specific search terms - called tags in Primo.

When you attend librarian conferences, it is common to hear speakers say that librarians are too modest about our value to our stakeholders and they advocate that we librarians should well.. advocate for ourselves more. Yet I think things are not that simple. There is always a tension between advocacy (which is by it's nature not fully objective) and analysis/assessment which is mostly objective.

In 2014, I wrote about “How academic libraries may change when Open Access becomes the norm” which attempts to forecast how academic libraries will change when “50%-80% or more of the annual output of new papers will be open access in some form”. I’ve come to realize a more interesting and critical question for libraries would be on what to do during the transition period, when open access becomes a significant but not yet majority pool of

There seems to be something in the water. Out of the blue, interest in helping users find free/open access articles seems to have blossomed since earlier this year when Unpaywall was unveiled.

With the current interest in browser extensions like Unpaywall to help access open access material, it may be easy to forget that the majority of scholarly content is still locked behind paywalls and there is a need to provide seamless access to them for our users. One interesting solution to this is Lean Library's browser extension.

I haven't done a "tools" post in a while, so this blog post will just be a whirlwind introductory tour of tools and applications I have explored recently and my thoughts on them. The interesting trend that links many (but not all) of these apps and services below together is that a lot of them are starting to embed machine learning into their feature sets.

As every librarian knows, there are three main sources of citation data. The three citation indexes (in increasing order of size) are Web of Science, Scopus and Google Scholar. However, they are not the only sources, and recently, I noticed studies showing that two other sources, ResearchGate and Microsoft Academic search are getting large enough to be worth considering.

Last month I wrote 4 different ways of measuring library eresource usage  and argued one can obtain usage statistics by obtaining them from publishers or rely on one's own analysis of ezproxy logs.  You can also analyse them by studying downloads or sessions, leading to a 2 by 2 matrix of measures. However, there are in fact other ways that can provide alternative dimensions to measure usage or even help predict use.