While you were working 28 March 2017

New open access portal from the Gates Foundation; Altmetric annual grant applications open; Kudos and PubFactory partner; Karger and UNSILO enrich content

Gates Foundation to launch open-access publishing platform

The Bill & Melinda Gates Foundation has announced that it is to launch an open-access publishing portal, which aims to speed up the publication of biomedical research and data funded by the global health charity. Gates Open Research is scheduled to launch in the third quarter of 2017 and will follow the model recently adopted by the Wellcome Trust, based on the F1000Research platform.


Research metrics: applications open for Altmetric annual grant

Data science company Altmetric have announced that applications are now open for its annual research grant. The grant provides up to £1,500 ($1,900 USD) to fund research that facilitates the development and understanding of alternative research metrics as part of the wider scholarly agenda. The aim is to support projects that would not otherwise receive funding, and submissions are sought from academics, researchers and librarians globally. Last year’s winner was Lauren Cadwallader, Open Access Research Advisor at the University of Cambridge.


PubFactory and Kudos team up to increase reach of research content

Publishing technology platform PubFactory is partnering with Kudos to deliver tools and services to publishers that aim to increase the dissemination and visibility of their research content. Publication data will be transmitted automatically from PubFactory, enabling Kudos to undertake promotions with, and on behalf of, authors. Authors will be able to share content through social media channels and track clicks, views, and downloads along with other metrics captured by Kudos.


Karger and UNSILO enrich content

Medical and scientific publishers Karger will partner with Danish artificial intelligence company UNSILO to create AI based content enrichment solutions for its biomedical content. The solutions will be based on UNSILO’s concept extraction engine and will use machine learning to identify core concepts in scientific book chapters or journal articles. The first application to be launched will be the creation of article packages, supporting content selection for thematic collections.