Welcome to Things we read this week, a weekly post featuring articles from around the internet recommended by BMJ’s Digital Group members.
Molecular and Cellular Biology (MCB) have published a preprint describing their program to screen images of accepted papers prior to publication which identified 12 manuscripts out of 83 with image concerns in two months. The screening and correction of papers before publication required an average of 30 min of staff time per problematic paper but 6 hours of journal staff time to resolve after publication. (H/T Phil Davis’s Tweet )
Towards the end of The authority file podcast there are some interesting insights about TDM requests coming into academic libraries, issues librarians face and how vendors can best fulfill these requests.
eLife is conducting a trial in which authors will decide how to respond to the issues raised during peer review. The Blockchain in Healthcare Webinar Series about Scientific Publishing and Replicability (see video below) is worth watching for some thoughts on using blockchain to support peer review and build more trust within the academic community.
Turn your data into stories without writing code using DIVE, an open source research project from the MIT Media Lab. More in the video below:
Marie Segger shares her experience of creating data GIFs for The Economist’s social media account (lots of good tips).
Future thinking and innovation
Anna Cupani and Richard Watson from Imperial’s Tech Foresight team have put together a table of 100 emerging technologies ranked by both time and disruptive potential. Its a fantastic list, which includes things like implantable phones, diagnostic toilets, cognitive prosthetics and human organ printing.
Sahil Chinoy in the New York Times looks at how Facebook are thinking about the future by reviewing their creepiest patents:
“Facebook has filed thousands of patent applications since it went public in 2012. One of them describes using forward-facing cameras to analyze your expressions and detect whether you’re bored or surprised by what you see on your feed. Another contemplates using your phone’s microphone to determine which TV show you’re watching. Others imagine systems to guess whether you’re getting married soon, predict your socioeconomic status and track how much you’re sleeping.”
JISC has a nice article about the positive power of extreme personalisation providing personalised learning experiences in specialist colleges . Finally, a nice reminder that small innovations can have a huge impact. A chatbot known as Becky, which was developed in two months for just £30, has won the Jisc-sponsored digital innovation of the year.
“Using AI and chatbot technology, Becky provides an instantaneous response and information to prospective students through clearing… During the development process, the team behind Becky realised that they could develop a bot that could take the user through the whole application process, including making offers. A total of 89 students who were made an offer via the chatbot enrolled in September 2017, which represents a 46.6% conversion of offers to enrolment. This compared to a general conversion rate of 26%. Leeds Beckett’s enrolment of students recruited during clearing increased by 11% in 2017 and the university estimates a return of investment on Becky of £2.4m in tuition fees.”
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