Artificial Intelligence is one of the ‘hot topics’ in science; recently, Tesla’s Elon Musk announced he was beginning a new venture, Neuralink, to “merge the human brain with AI”. But apart from visions of cyborgs dancing the heads of science fiction writers, what are the implications of Artificial Intelligence? For the general public? For researchers? And for the future of employment?
The aim is to bring together people from different backgrounds to explore the possibilities around data mining tools, and how they can be used to save researcher’s time by finding and processing huge amounts of information quickly and easily.
We’re asking for submissions before the 13th July 2014 from those interested in analysing and mining databases of scientific publications, developing systems to enable such analysis, or designing new technologies to improve research and the free availability of research data. Researchers should submit their papers online, for inclusion in the programme. Both long papers (up to eight pages in the ACM style) and short papers (not exceeding four pages) are welcome, as are practical demonstrations and presentation of systems and methods (demonstration submissions should consist of a two-page description of the system, method or tool).
“We’re looking to attract researchers from across academia and industry to work through the amazing possibilities and challenges around mining scientific content. The collaborations that come from these initiatives always yield really interesting results, so I’m looking forward to see what submissions we get through this year” says Kris
The workshop will be structured around three main themes:
The whole ecosystem of infrastructures, including repositories, aggregators, text-and data-mining facilities, impact monitoring tools, datasets, services and APIs that enable analysis of large volumes of scientific publications.
Semantic enrichment of scientific publications by means of text-mining, crowdsourcing or other methods.
Analysis of large databases of scientific publications to identify research trends, high impact, cross-fertilisation between disciplines, research excellence etc.
This year, we also put together a CORE publications dataset containing a large array of publications from various research areas. This includes full-text as well as enriched versions of metadata, with the aim of providing workshop participants with a framework for developing and testing methods and tools around the workshop topics. You can access this data through the CORE portal.
If you have any questions or comments, leave them below or tweet @WOSP2014
Since we recently announced our $10001 Binary Battle to promote applications built on the Mendeley API (now including PLoS as well), I decided to take a look at the data to see what people have to work with. My analysis focused on our second largest discipline, Computer Science. Biological Sciences (my discipline) is the largest, but I started with this one so that I could look at the data with fresh eyes, and also because it’s got some really cool papers to talk about. Here’s what I found:Read More »