Welcome to Things we read this week, a weekly post featuring articles from around the internet recommended by BMJ’s Digital Group members.
OpenCitations announced the release of the Crossref Open Citation Index (#COCI) which contains open DOI-to-DOI citations extracted from Crossref. Crossref’s really useful participation reports show what percentage of a publisher’s content has 10 key metadata elements registered. Going through BMJ’s report we found out that some of our reference deposits are failing and we need to resubmit 🙁
Lucy Montgomery and Xiang Ren’s case study on Chinese Journals and Open Access looks at the development of Chinese open access (OA) journals, and national-level OA repositories and concludes with:
“…relationships between open knowledge, democracy, accountability, and national power are as complex and potentially diverse as the communities that make and use knowledge. As the concept of open knowledge shifts from periphery to mainstream moving beyond simplistic contrasts between open (good) and closed (bad) is necessary to understanding digitally enabled knowledge systems, and to identifying the infrastructures, policies, and forms of regulation most likely to produce positive change for the communities that use them. ”
Innovation and product development
Freia Nahser writes up a GEN summit on how The New York Times, Vayner Media, BBC, Evening Standard are experimenting with voice interfaces.
NPR have created an excellent 38 page Guide To Hypothesis-Driven Design For Editorial Projects to help editorial teams take a user-centered and evidence-based approach to storytelling projects.
We like Tristan Ferne’s photo of 12 concepts for new story types based on re-using content that we’ve already created… …at some point we hope that reusing content in this way will be easy on academic publishing platforms.
Quick shout out to Ian Mulvaney’s ScholCommsProd blog which does what it says on the tin and has articles focusing on product development in scholarly communications.
Artificial Intelligence & Machine Learning
Lots of interesting experiments with bot technology happening at The BBC. The BBC’s News BotBuilder tool gives journalists the “ability to easily convert long explainer articles into an interactive conversation or create new content from scratch. It automatically generates a database of questions and answers from an inputted article URL, saving journalists the headache of repurposing their content from scratch.”
Not the most rigorous of studies but Alan VanderMolen’s Creepy V Cool barometer gives some interesting results:
“Google has created technology that lets artificial intelligence on your phone make appointments for you (eg if you wanted a haircut, a chatbot on your phone would call the salon and speak to a human on your behalf).” On this one, we had a statistical dead heat: 41% “creepy”, 42% “cool” and 16% “neither.”
In ten years time will it seem quaint that people were uncomfortable with this kind of technology?
A number of global AI research centers have run machine learning models to predict outcomes for the FIFA World Cup 2018 in Russia with limited success. Worth noting that Paul the Octopus who picked football match winners at the Euro 2008 and 2010 FIFA World Cup had a success rate of 85.7 percent!
Is someone says something is “Likely,” How Likely Do People Think It Is? A survey published in HBR asked members of the general public to attach probabilities to 23 common words or phrases appearing in random order with the following results:
The authors Andrew Mauboussin and Michael J. Mauboussin suggest that for clearer communication ask yourself: What percentage chance, in what time period, would I put on this outcome? Rather than using terms such as “unlikely” or “virtually certain”.