Elsevier Connect | Redefining impact: Get credit for ALL your scholarly work

"Let's say you're a researcher and you're looking for the latest developments in the area of intracellular membrane trafficking, a field which you believe may have some applications to your field of study. How do you find out what the latest discoveries are? You could try reading papers from well-known authors (if you know who they are), or you could find a recent review (if there is one), or you could see if anything as been published recently in a top journal like Cell, Nature or Science.  These are all good approaches, but they're far from systematic and leave you wondering what you've missed, so you try a search on PubMed. You get thousands of results and it's not immediately clear which ones you can even access, let alone which ones best reflect the scientific consensus.  Next, you try Scopus, sorting your results by the number of citations. This works a little better, but papers published this year often haven't yet accumulated many citations, and to make matters worse, you find that many of the highly cited papers just aren't very good when you take a closer look and you suspect some got through peer review on the strength of the author's name or institution rather than technical merit.  If this describes a situation you've often found yourself in, you're in good company. Not just researchers but funders and publishers often struggle to identify quality papers that suggest that an early-career researcher should be given a shot with some exploratory funding or that a paper is likely to appeal to their audience. This is the problem addressed by a new way of looking at research metrics, called altmetrics.  Altmetrics are essentially an application of what the rest of the Web uses to determine which pages are most likely to be relevant to a website's audience or to an individual in a scholarly context. If Amazon.com can tell you what phone you'd most likely want to buy, and Google Analytics can tell you what stories your audience is most interested in, why shouldn't there be a service that can tell you what papers you'd be most interested in reading or publishing?  The good news is that there can be, but we have some work to do to get it right and to expand our definition of impact beyond a paper that is highly cited by other research papers.  First, data on which papers have been cited by which needs to be available, under licensing terms (such as CC-BY or CC0) that enable use and reuse of this data by the many groups which alone could only solve part of the problem for their niche, but together as part of an innovation ecosystem could contribute to a much more powerful and more general solution.  Second, we need to study the various signals indicating attention and impact on the Web, including those from academic collaboration tools like Mendeley, repositories such as Dryad and Figshare, and other sources such as blog posts, Twitter and Github. We still don't understand why people write blog posts or Tweet about academic papers, but over time and with collaboration with the bibliometrics and webometrics communities, we'll learn how to understand what these signals mean and how they're best used to filter or assess the research mentioned in them. Finally, we need to capture all these metrics in a standardized format which makes them maximally useful to anyone who wishes to use them.  Here's what we know so far ..."