Size doesn’t matter in Big Data, it’s what you ask of it that counts

Size doesn’t matter in Big Data, it’s what you ask of it that counts


Data have traditionally been collected manually by measurement scientists, using microscopes or surveys. Big Data provides scientists with the ability to conduct powerful analyses and make new discoveries. The problem is that the way many researchers ask scientific questions has not yet changed with Big Data. 

Biologists are expecting big things from Big Data, but they are finding out that it initially delivers only so much. Many biologists have responded by gathering more and more data. Put simply, scientists have been lured by size, writes Andrew Stott. The way we ask questions says a lot about the type of information we use, he says. For example, systematists like myself study the diversity and relationship between the many species of creatures throughout evolutionary history. We have tended to use physical characteristics, like teeth and bones, to classify mammals.

Size matters
Quantity is often seen as a benchmark of success. The more you have, the better your study will be. If all the data was available, then scientists wouldn’t have the problem of missing or corrupted data. A real-world example would be a complete genome sequence. Therefore, size doesn’t matter, it is what we ask of our data that counts. 

Big Data is not a replacement for traditional methods and questions, rather it is a supplement. Big and traditional data can be used together to enable biologists to better navigate their way down the path of discovery. Unlike traditional data, Big Data cannot give a precise answer to a traditionally framed question.


Anna
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