There’s been an explosion of news around big data over the last month but nothing much actually seems to have happened, perhaps its newsworthiness is the result of a growing realisation that it’s here to stay?
The fact that data is being collected, en masse and used to influence almost every aspect of your daily life, is nothing new. The stark realisation just how some of this data has been collected in the past has created some stirs and caused the odd person to flee the country but still, for many, it’s old news, or just a validation point for a lot people who said “I told you so”.
For many, their credit score is something to be nurtured and tended in order for it to provide a lifestyle that we otherwise could not afford and we tend to welcome data collection that reflects well on our salary, ability to borrow and payback and generally shows us to be individuals worthy of inhabiting this planet of ours, so what’s good data and what’s bad data or is there no such thing as either?
In many ways we are on the verge of a new information era as can been seen by the changes of Internet2, currently we have the means to capture unheard of amounts of data relating to almost anything we wish, using it effectively however, is still proving tricky. Google’s flu-tracking database has not had a good time of it lately, completely mis-calculating the ’11-’12 and ’12-’13 flu outbreaks, not great for what had become big data’s poster child. Never has the old adage, rubbish in – rubbish out, been so true, much of the feeds for this area of development, known as “computational social science”, are from social networks such as twitter and facebook, which in themselves are proving to be unreliable platforms when it comes to reporting numbers.
However, in more closed systems is big data doing any better? IBM lists hundreds of examples where big data analysis has yielded positive results, ranging from preventing athletes injuries to managing transport infrastructure, but these generally seem to be big data being applied to solve small problems.
There has been a certain amount of bandwagoning in the agricultural sector after some big money was spent on big data companies by even bigger agricultural companies but big data is far from new in this sector. The NSF funded iplant platform, was developed nearly a decade ago to help manage animal and plant life sciences data and is deeply engaged in Internet2 via universities and research hubs.
Modern farming techniques already harness huge amounts of data, helping to make decisions on how much fertiliser to use, levels of irrigation, when to harvest and methods of crop rotation. Expensive machinery can now be monitored and pre-emptively serviced before costly breakdowns occur and with machine to machine communication, product usage and optimisation can be done in real time, saving money and potentially increasing profits. Many people argue that big data is just a logical progression from the latest in a continuing stream of innovations that began with the mechanisation of agriculture in the early 1900s, followed by hybrid corn in the late 1920s.
With a predicted 47% growth in population by 2050, many people think that agriculture cannot serve the coming needs of the planet without the use of big data but does this throw up a potentially new conundrum for the sector? Big data can help optimise the production levels of crops and also tell the a farmer the best time to harvest and go to market, based on the current market price for
their products, but who actually owns this potentially sensitive data and how private is it? Could this mean the age of free market competition in agriculture is about to end? With more and more information available on almost every acre of land in the US can a farmer keep this information private or indeed, should they, given the remit for big data to do more, with less?
You can read more at http://www.farmers-exchange.net/detailPage.aspx?articleID=13580
IBM’s success list can be found here (http://www-01.ibm.com/software/success/cssdb.nsf/solutionareaL2VW?OpenView&Count=30&RestrictToCategory=default_BigData).
Matt Willis, Director, International Markets.