Mendeley, Times Square and Number 10 Downing Street
Victor Henning is a co-founder and Chief Executive of Mendeley. Mendeley is a free reference manager and academic social network that can help you organize your research, collaborate with others online, and discover the latest research.
In your interview with The Kernel, you mentioned that at that time, Mendeley had 1.9 million users. That’s quite a figure. Did you anticipate such a high number?
Thanks! Yes, we always hoped we’d get to this point and much further. When we started Mendeley, we did some market research that suggested there were about 150 million knowledge workers - academics, students, industry researchers, doctors, nurses, engineers, consultants, researchers in government and NGOs etc. - worldwide who might benefit from a tool like Mendeley. So, we honestly believe we’ve only just seen the tip of the iceberg.
You also mentioned that Mendeley has 285 million documents uploaded to your database and on average, you are currently getting about five to eight hundred thousand documents a day added. These figures are quite mind boggling. Can you expand a bit about the social layer to your database?
Sure. The social layer to our database is what makes it unique, and not just a copy of other big databases like Thomson Reuters’ Web of Knowledge or Elsevier’s Scopus. Because our data is crowdsourced, each document comes with information about the researchers who uploaded the document. This means that, for every document, we know how many researchers have read it, what their academic background is, which keywords they have added to the document, which bits of the document they have highlighted, or what else they are reading at the same time. Of course, we would never share an individual researcher’s information to preserve their privacy, but it enables us to generate really interesting anonymized summary statistics and research trends. In essence, we can peer over the shoulders of millions of scientists worldwide to see what they’re reading - and thus, what impacts their research - long before citation data and journal impact factors capture these trends.
More generally, the social layer helps us add context to research papers - based on our real-time readership information, we can show you related documents or public groups on Mendeley in which the document is being discussed. All of this helps you discover research papers or research groups faster.
In terms of academics self archiving their Manuscripts, since we know that uptake via Institutional Repositories is low (in terms of Open Access), it’s encouraging to know that, as you say, “A ton of papers have been made available by Mendeley in this way, by academics uploading their own papers”. Is this something that you are actively promoting?
It hasn’t been a focus of Mendeley, but yes, we are encouraging our users to make their publications available on their Mendeley profile. That can be the pre-print, post-print, or final published version, depending on the permissions they have received from the journal.
We have also been working on a JISC-funded research grant together with the University of Cambridge and Symplectic (one of figshare’s sister companies at Digital Science) to increase Open Access deposits to university repositories (more info here). The idea is that any publications which Mendeley users have posted to their Mendeley profiles can be synchronized to their Institutional Repositories. Say, for example, you’re a researcher at Imperial College as well as a Mendeley user: The publications from your Mendeley profile could then be automatically imported to the Imperial College repository, which saves both you and the repository administrator work as well as increasing Open Access to research.
Leslie Carr, who runs the University of Southampton’s repository, looked into the numbers a while ago and concluded that Mendeley could boost Open Access by “mainly attracting users who are not already "OA active". Users of Mendeley have clearly transitioned from "scholarly knowledge collectors" to "scholarly knowledge sharers"".
Generally, we feel Open Access and Open Science are the way forward - and we have to find sustainable business models to support them.
In terms of Open Science, it’s not unreasonable to say that data/text mining are significant tools. Can you talk a bit about your own thoughts on this and how you think the Semantic Web might develop over the next few years generally?
Yes, I firmly believe that data and text mining will enable us to speed up scientific discovery across all fields of inquiry in the next few years - both in the sciences and the humanities. One of the best talks on the potential of mining Linked Open Data is still the one Tim Berners-Lee gave at TED in 2009. I’ve been quoting him in a lot of my presentations:
“All the time we are very conscious of the huge challenges that human society has now – curing cancer, understanding the brain for Alzheimer‘s. But a lot of the state of knowledge of the human race is sitting in the scientists’ computers, and is currently not shared. We need to get it unlocked so we can tackle those huge problems.“
Mendeley has been trying to tackle exactly this problem by building an Open API which enables third-party developers to tap into our complete crowdsourced database - including the social layer - under a Creative Commons license. To date, there are more than 260 active third-party apps using our data to build tools for research analytics, collaboration, visualization, or for mashups between raw data (like genetic information) and the latest research papers. Recently, we announced that these apps were now querying our API more than 100 million times per month. Here’s a cool pic from when the news was shown on Times Square in New York:
I believe that we will see many more text and data mining apps being built on the Mendeley platform in the near future. One of the most recent entries is Virtu - an expert finder service that mines Mendeley user profiles and publications. Go check it out, it’s really cool!
We would certainly like to expand our API’s capabilities to make text and data mining even easier, but there are a number of legal and regulatory issues to be solved. I’ve been to a number of consultations in parliament and No 10 Downing St. to support the text mining exception in the Hargreaves report, as well as meeting with a lot of publishers to explain why I believe that this is also a great commercial opportunity for them. Hence, I was glad to see the Nature editorial supporting text mining without requiring additional licenses.
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