杏吧原创

DIGITAL tools have changed the way we live. Five years on from the release of the first iPhone, people can now explore foreign cities, track their portfolio performance and graph their sleep cycle 鈥� all within their coffee break. Smartphone apps, coupled with new trends in social media, have become enmeshed in the daily lives of the stylish, the affluent and the slightly geeky.

But what about scientists? Somewhat bafflingly, much of what goes on in the lab still relies on the same pen-and-paper methods that have served science well this past millennium. So how is digital technology affecting life in the lab? And will the tools that have already made inroads phase out science鈥檚 analogue darlings, or will they be dropped once the novelty wears off?

In the early days of the smartphone, apps were mainly minimalist platform games or an easy way to find a good Thai restaurant. But their fun-loving childhood was short-lived and they are now more synonymous with utility than shakable light-sabres. This has made them an essential part of daily life for many. One particularly useful group for scientists is archiving apps like . Effectively allowing you to archive all the notes you have ever taken on a subject, be it a voice memo or a scribble on a napkin, Evernote and its ilk appeal to the budding lifeloggers among us 鈥� and those who need to organise vast amounts of information.

Another popular app is . Created by Sarah Butcher and her team at Imperial College London, this data-collection cousin to note-taking apps takes information recorded by a smartphone, logs each data point鈥檚 location, and then sends it to a central server. The app can be applied to virtually any type of project 鈥� from logging disease transmission in western Africa to mapping your summer road trip.

鈥淧eople have a very clear idea of how they generate data, but they don鈥檛 necessarily have the means to analyse it or to share it in a way that makes it usable,鈥� says Butcher. This becomes more of a problem as people want to integrate larger data sets, she says. 鈥淵ou might have 10 postdocs all working on the same project, generating and modelling data of different types. They need to be able to visualise the same stuff at the same time.鈥� Epicollect can solve this problem.

Despite the popularity of apps such as these, and the relatively straightforward development process to make and distribute them, science apps are not available in anything like the same number as finance or business apps. Why is this?

鈥淣o one ever really thinks software can do the tasks of pen-and-paper processes in lab science,鈥� says Chris Seaton. He co-created the app while doing a PhD in computer science at the University of Manchester, UK. Having been a captain in the Royal Army Medical Corps, Seaton knew that when people receive serious burns, medics need to get the right amount of fluid into them very quickly. Mersey Burns calculates the precise quantity of fluids needed, saving time and avoiding mistakes.

But long-standing medical practices are hard to phase out, even when they are flawed. Not to mention that whipping out a smartphone in the ER may rub some doctors, and patients, up the wrong way. But Seaton thinks digital tools need to become an extension of our professional minds, even in high-stress situations. 鈥淭hey just need to crack on and get the fluids in. The idea is that the app can be in their back pocket and it鈥檚 free so they have it when they need it.鈥�

Not all scientists are against the march of smartphones. For Enea Milioris, a second year PhD student at the Institute for Child Health at University College London, note-taking apps have revolutionised the way he organises his work. Of these, he prefers Evernote, he says. 鈥淚 drop in protocols, data, sample lists, scanned gels, meeting notes, presentations, admin paperwork. Everything.鈥� The other apps in his digital tool-belt reflect the variety of his work. 鈥淥n the bench, I use DailyCalcs, Protocols and Cloning Bench as well as the Promega app. They are all handy quick references and I find the visualisation of protocols helps me shift focus.鈥�

聯I drop protocols, data, sample lists, scanned gels, meeting notes and presentations into the Evernote app. Everything聰

Currently, Milioris is an outlier in his embrace of all things digital, being one of just a few in his department that has caught the app bug. That鈥檚 understandable, he says, as things can get pretty messy in the lab. 鈥淣ot everyone wants their phone or tablet in the way of salmonella, and in departments like mine you can鈥檛 put your work in the cloud as it鈥檚 private data, often from patients.鈥� Nevertheless, Milioris relishes not having to look through yellowing notebooks every time he needs to look something up.

Social media鈥檚 presence in traditional science can also be a touchy subject. In most fields, Twitter, Facebook and blogging platforms like WordPress and Tumblr have become accepted as effective ways of broadening your profile, bringing with them a vast range of potential faux pas and new etiquette (retweeting compliments is a no-no; the casual publishing of panda videos less so).

To tweet or not to tweet

Hugh Goold is a PhD student studying lipid biochemistry at the Aix-Marseille University in France. A social media user himself, he is well aware of its complex identity among scientists. Goold uses tools like Dropbox and the Google suite, but his feelings are mixed when it comes to social media networks that specifically target professionals. 鈥淚 use LinkedIn for my work life and Facebook for my social life. But honestly, I think it鈥檚 very superficial to look at someone鈥檚 online profile. I think being proactive and making a phone call beats checking someone in that clandestine way,鈥� he says. But he does admit to using social media to ask friends for advice. 鈥淩ecently I used Facebook to troubleshoot a problem I had with a DNA prep. Because I鈥檓 friends with so many scientists, I got a bunch of great ideas.鈥�

Blogging is another increasingly popular way for plugged-in scientists to share information. Scientopia is one of several platforms for science bloggers to publish their thoughts on everything from tornadoes to time travel. One of its founders and most prolific bloggers is , a postdoctoral lab researcher in the US who prefers to use her online pseudonym to distinguish her online presence from her offline career. To her, blogging has the potential to humanise a field which is too often misunderstood by the public. 鈥淭he science culture as a whole is such a black box to most people,鈥� she says. 鈥淚 love the bloggers who write about their experiences, who open that black box up and show that scientists are people too.鈥�

But to Scicurious, the perception that scientists may only be in the blogging game to promote their research is far from accurate. 鈥淚 never write about my own research to avoid conflicts of interest. Writing about work that is outside of my field, though, has allowed me to put connections together for my work that I never would have seen.鈥�

There鈥檚 no doubt, however, that the increased exposure that social media brings can increase a researcher鈥檚 currency. Writing on a blog for New 杏吧原创, Inger Mewburn, a research fellow at the Royal Melbourne Institute of Technology in Australia, described how, as a result of her , her work has been featured in the mainstream media, which led to requests to give keynote talks and write books. 鈥淚n short, I have had access to opportunities usually reserved for more experienced players. It would take me at least 10 years to achieve this kind of status and recognition through the normal academic 鈥榝ame鈥� channels of citations and conference attendances,鈥� she wrote.

Beyond the blogging format, social networking tools 鈥� particularly Twitter 鈥� can bring an additional value to researchers. They are linked to large groups of people, who aren鈥檛 just an audience for any findings, but also a potential vehicle for gathering data in the first place. Alexandre Bayen, an associate professor of electrical engineering and computer science at the University of California, Berkeley, has long been interested in the flow of information accessible with networking tools. His team has developed , a traffic monitoring system for the California Bay Area which harvests GPS data from people鈥檚 phones. It uses data taken from , a social network that allows commuters to comment on traffic, and the team is currently looking at ways to harness commuter-commuter interaction through the network to produce traffic updates. Bayen describes social media as 鈥減robably the most forward-thinking way鈥� of engaging people, particularly as a way to share information.

聯Social media is probably the most forward-thinking way of engaging with people and sharing information聰

Scicurious agrees that the use of social media is quickly evolving. But she cautions that many still need to be convinced that it is 鈥渘ot a waste of time that should be spent in the lab or writing papers, but a useful tool that can help you in your career鈥�.

So what鈥檚 next to be digitised in the world of science? Recommendations for what you read, perhaps? It鈥檚 not hard to imagine the day when an algorithm is telling scientists which research papers to read, just like Amazon鈥檚 algorithm tells you what books to buy.

But things are already going further than that. Take Eureqa 鈥� a program of predictive algorithms developed by Hod Lipson and colleagues at Cornell University in Ithaca, New York. When let loose on a set of data, it can find the laws of nature that govern it. The algorithm behind the software is relatively straightforward, but the implications are astounding, potentially lending insight into the natural world 鈥� even to areas which are presently a mystery. 鈥淒ata collection from new experiments has far outpaced our ability to analyse it,鈥� says Michael Schmidt, one of its developers. 鈥淭his data is a powder keg waiting to go off, just as soon as our algorithms can catch up. Tools like Eureqa are a new way to navigate this abundance of observation.鈥�

If such tools live up to their promise, anyone with data will soon be able to winnow out laws of nature. But there are major challenges. 鈥淲hat do we do when we have the answer but not the explanation? Will we be able to comprehend scientific results indefinitely? How do we choose what to study? These will be the core issues occupying scientists in the next few decades,鈥� says Schmidt.

And it鈥檚 not just experimental data analysis that is being targeted. Another program that will surely occupy scientists鈥� minds if it catches on is one which claims to determine who should get that sought-after position or research grant. In September 2012, Nature published a . It is based on the 鈥渉-index鈥�, which calculates a scientist鈥檚 impact based on their publications and citations. Daniel Acuna from Northwestern University in Evanston, Illinois, and colleagues set out to predict future h-indices based on crowd-sourced listings of scientists and their mentors via academic database .

Ethical or practical disclaimers in the paper are few and far between; the team are eager to emphasise their model鈥檚 real-world applications. 鈥淥ur formula is particularly useful for funding agencies, peer reviewers and hiring committees who have to deal with vast numbers of applications and can give each only a cursory examination,鈥� they write, adding that 鈥渢he results offer some comfort by showing that the future is not so random鈥�.

Whether any company or university would actually submit their applicants to the new equation is really a matter of speculation. But applications like this 鈥� which turn scientists into a data point in someone else鈥檚 black box 鈥� remind us that proponents of the digitisation of science, hungry for the time-saving, paper-saving and crowd-sourcing benefits it promises, will also have to be prepared for the mirror to be turned on them.