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Whether you are a student trying to get your head around a complex field for the first time or a professor trying to stay on top of the ever increasing flood of new publications, being able to tame the vast tangle of scientific literature is critical.
Traditional discovery tools for scientific literature are based on keyword searches, which are a difficult art to master and can often miss crucial papers due to changes in terminology. Meanwhile, the recent wave of 'Netflix' style recommendation engines for science simply inundate the researcher with yet more papers to read.
We aim to create a discovery platform for scientific literature that is both targeted, accurate and comprehensive.
Rather than starting with keywords, Gecko allows researchers to conduct a specific search using a handful of “seed papers” that indicate the area they wish to explore. By following the forwards and backwards citations of these 'seed papers' it builds a localised citation network that provides an interactive map of the field by putting the relevant papers in context.
By defining different metrics on this localised network we can help direct researchers to the type of papers they are looking for: whether it be the most recently published developments or the more historical foundational papers of the field.
I’m a PhD student at Imperial College London passionate about using technology to make life easier for researchers. The idea for Gecko was born out of my own frustrations when doing a literature review in the first year of my PhD.
We want to turn Gecko into a scalable web service that anyone can use. To do that we need money for web servers. We are also building our own database of citations in the cloud which will cost money to host.
Gecko is completely Open Source so if you want to follow our progress in real time or contribute, check out our Github repo at https://github.com/bjw49/citation-network-explorer . You can also check out a beta version for yourselves at http://citationgecko.com .