When preparing a grant or publication, where can you turn for new ideas? You can bounce ideas off colleagues, search PubMed and Web of Science for related literature, and maybe take a trip down Google lane. But it’s difficult to get outside one’s particular area of expertise — to mine the opportunities at cross-disciplinary boundaries unless you know what you’re looking for. The developers of a new document search engine hope to make such cognitive leaps easier, finds Jeff Perkel.
Want to embrace open data but don’t know where to start? The tools are out there, says Matthew Edmonds.
The Publishing Better Science through Better Data conference, or #scidata16 for short, took place at the Wellcome Collection in London at the end of October. This one-day event organised by the journal Scientific Data, Springer Nature and the Wellcome Trust explored the challenges facing early-career researchers as we enter the era of open data.
As a data novice, I arrived without really knowing what to expect. The types of experiments I perform generate only small datasets needing a simple statistical test, easily summarised in a graph in the manuscript. The original data can be safely left to gather dust in a shared drive. Continue reading →
Our reporter Monya Baker runs through some of the statistical tools she found when writing her latest story.
As I reported in a Nature feature published this week, I found more online courses that were being developed than were actually in place. Resources to help scientists do more robust research are set to expand quickly. For example, the National Institute of General Medical Sciences has a competitive program that awards funds to institutions to enhance graduate student training; of 15 such supplements awarded in 2015, a dozen involved data analysis, statistics, or experimental rigor. You can find more here, and that is only a fraction of what is available. Some courses are still being developed and piloted to select students; others are being offered only to those in a particular department or training grant. If you find one that interests you, it can’t hurt to ask.
“Big data” is a catchall term for any data set of exceedingly large volume. It could be transaction information at a credit card company, invoice data at an online retailer, meteorological measurements from a weather station. All these data sets have unique characteristics that make it extremely difficult to use conventional computing technologies and techniques to store and process them for analysis. Their variety is daunting, and high velocity is required to handle them in a timely manner.
So who is going to store, manage and process all this information? Well, why not you? Companies are starved for people with this kind of expertise. Big data is a growth industry and people from a variety of academic backgrounds can find successful careers in this area.
