“At ScienceOpen, we’ve just upgraded our search and discovery platform to be faster, smarter, and more efficient. A new user interface and filtering capabilities provide a better discovery experience for users. ScienceOpen searches more than 27 million full text open access or article metadata records and puts them in context. We include peer-reviewed academic articles from all fields, including pre-prints that we draw from the arXiv and which are explicitly tagged as such The current scale of academic publishing around the world is enormous. According to a recent STM report, we currently publish around 2.5 million new peer reviewed articles every single year, and that’s just in English language journals. The problem with this for researchers and more broadly is how to stay up to date with newly published research. And not just in our own fields, but in related fields too. Researchers are permanently inundated, and we need to find a way to sift the wheat from the chaff. The solution is smart and enhanced search and discovery. Platforms like ResearchGate and Google Scholar (GS) have just a single layer of discovery, with additional functions such as sorting by date to help narrow things down a bit. GS is the de facto mode of discovery of primary research for most academics, but it also contains a whole slew of ‘grey literature’ (i.e., non-peer reviewed outputs), which often interferes with finding the best research. As well as this, if you do a simple search with GS, say just for dinosaurs, you get 161,000 returned results. How on Earth are you supposed to find the most useful and most relevant research based on this if you want to move beyond Google’s page rank, especially if you’re entering this from outside the area of specialisation? Simply narrowing down by dates does very little to prevent being overwhelmed with an absolute deluge of maybe maybe-not relevant literature. We need to do better at research discovery…”