Modern biological research relies on big data analytics. Vast reservoirs of memory and powerful computing ability mean machines find patterns and make meta-analyses and even predictions for scientists.
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Articles on Big data
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The first digits of numbers in a data set aren’t distributed equally. And now you know more than a lot of fraudsters do – and should – when they’re making up their phony numbers.
The end-of-year shopping whirlwind is underway. How does your credit card issuer watch out for fraudulent purchases on your account amid all those transactions?
Big data is about processing large amounts of data. It is often associated with multiplicities of data. But the ability to generate data outpaces the ability to store it.
Preventing crime before it happens, while saving resources, sounds like a great use of big data. But these calculated probabilities raise big questions about civil liberties.
The availability of data is just the starting point – we then need to make sense of the data.
The Investigatory Powers Bill would require ISPs to store 12 months of our web browsing history – a year-long snapshot of our thoughts, fears, interests and behaviour.
By simulating cities from the “bottom-up”, scientists can help us plan for the future.
Could the key to countering a culture of bribery and greed be in the hands of the people?
Using more accurate data, researchers find that waste disposal at methane-emitting landfills is two times greater than previous EPA estimates.
Sophisticated models and supercomputers allow researchers to create a high-fidelity map of the Earth’s trees – and show that we’re losing billions of trees a year.
Math isn’t prejudiced, goes the argument. But these arithmetic programs can learn bias from the data fed into them by human beings, leading to unfair treatment and discrimination.
The health sector is good at using technology to help treat patients, but it’s not so good with technology in the business of health care.
Analyzing big data sets holds the promise of big insights. But the axiom “garbage in, garbage out” is particularly apt, since conclusions can be only as good as the raw data itself.
Today’s world is drenched in data, and we need the best tools to help us understand and use it.
We think that more information means better decisions, but really it means we struggle to make decisions at all.
Online infrastructure and business are becoming increasingly important, as is our need to focus research efforts on securing them from cyber-attack.
Sometimes the best way to deal with mountains of data is to turn to the public for help. That’s what Snapshot Serengeti did to classify millions of photos from savanna camera traps in Tanzania.
Collect all the data you want, but if you can’t figure out what you’re looking at, it’s useless. Topologists look for spatial relationships to figure out what the data can tell us.
The Apple Watch represents a significant shift from handheld technology to devices that become an invisible part of our lives.
Top contributors
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Professor, Director of Big data and smart analytics lab - IIIS, Griffith University
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Engaged Research Fellow, Institute for Culture and Society, Western Sydney University
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Senior Lecturer in Applied Ethics & CyberSecurity, Griffith University
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Adjunct Professor and Industry Fellow, UNSW Sydney
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Professor of Information Sciences and Technology at Altoona campus, Penn State
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Senior Lecturer, The University of Queensland
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Professor of Cybersecurity, School of Computer Science and Informatics, De Montfort University
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Assistant researcher, University of Sydney
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Assistant Professor of Philosophy, UMass Lowell
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Research Fellow, University of Exeter, University of Exeter
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Associate Professor, School of Law, University of Canberra
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Director of UWA Centre for Software Practice, The University of Western Australia
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Senior lecturer, University of Twente
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Professor, School of Science, Western Sydney University
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Fellow of the Faculty of Engineering and Information Technology, University of Technology Sydney
