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Open Data can be Big Data, and Big Data can be Open Data -- but they are not synonymous. What is the major difference between the two?

  • Nick, These terms are unrelated. Please refer to the definition of these concepts (Open Data, Big Data). If you don't understand something specific about the definition in relation to Open Data SE, please feel free try again by describing what you are having trouble understanding specifically. Thanks. – Robert Cartaino Jun 3 '13 at 15:25
  • Robert, thanks! The terms mean different things, but are both terms to describe data (and even movements). I asked this question because I've seen these terms used occasionally interchangeably in non-expert settings, and I thought it would be helpful to have an answer here that explains the venn diagram of the two terms. If that's not helpful or is inappropriate for the Open Data SE, then please close. – Nick Jun 3 '13 at 23:15
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They are not the same at all. Datasets are Open if they are available under a free license to everyone. Datasets are Big if... well, they are. Typically big beyond where common software can handle them in real time.

For example Facebook and Google work with Big Data that is not Open.

Most Open Data sets are actually an example of Small Data: The datasets themselves are not huge, but there is a large number of them that can be correlated to increase their value.

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They aren't synonymous, but big data can be inherited by open data. "Big" is just a quantifiable attribute given to data; meaning there is a large amount of it. "Big" data can also be misrepresented in terms of scale. Your big data could be small to someone else and vice versa. "Open" data is an idea that data should be readily available to the public.

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Big Data.

I think the point has been missed about "Big Data". It doesn't need to be large in volume.

There are historically (from 2001) three tenets of big data

  • high volume (e.g. Facebook, Google index)
  • high velocity (e.g. mouse click data being analysed every second for user behaviour triggers)
  • high variety (e.g. data that has a diversity of data types stored within it, e.g. documents, images, structured information, relationship information, etc.)

If data has one or more of these, then it is considered "big".

Open Data.

This very good article on open data that shows what it is.

For Example.

An open data set could be small, slowly changing or non-changing, and contain a well structured simple format - this would not be a "big data" set. If we consider data.gov.uk's 'Trees in Camden' data set, it is a 2.8 Mb csv file of council owned trees which is updated periodically (maybe monthly).

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Open Data vs Big Data.

Open Data: Open data is data that anyone can share and publicly accessible. Open data is a description or type of data, usually with little to no restrictions.

Big Data: Big data exists on a large scale that usually cannot be processed by regular software. It's massive in size and includes a set of datasets.

Open Data does not need to be related to Big Data in order to exist. These are basically separate terms used to describe data. Hope this helps!

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