In 2001, the industry analyst Douglas Laney at Gartner described data management challenges along the three dimensions volumes, velocity and variety in the E-commerce branch. Volumes stands for the quite huge increase of volumes of data, Velocity for increased point-of-interaction speed and the pace of data generated by interactions and used to support interactions. Data Variety means variety of incompatible data formats, non-aligned data structures and inconsistent data semantics. This 3-V-model has been widely used attempting to define big data since this publication in 2001. [1]
The Oxford dictionary has defined the term Big Data as “extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions”. [2]
Viktor Mayer-Schönberger and Kenneth Cukier point to what can be done with the data and why its size matters in the way that it is “the ability of society to harness information in novel ways to produce useful insights or goods and services of significant value”. Nevertheless, they focus on potential risks e.g. in terms of privacy, predictions to punish people even before they acted or the abuse of data by people with bad intentions. [3]

[1]    Laney, D. (2001), 3D Data Management: Controlling Data Volume, Velocity, and Variety,, retrieved February 20, 2018.
[2]    Oxford Dictionary (2018), Big Data,, retrieved February 20, 2018.
[3]    Mayer-Schönberger, V., Cukier, K. (2013), Big Data: A Revolution That Will Transform How We Live, Work, and Think, Houghton Mifflin Harcourt, New York.
Trend tendency (relative frequency of related scientific publications)
Relative frequecies of Big Data related publications
Public Sector Relevance (relative frequency of related scientific publications)
Trend Public Sector Relevance of Big Data related publications
Big data potential
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Since big data solutions have the potential to generate previously unavailable insights and create valuable services, how could companies be motivated to share proprietary data with the public sector, while preserving security and privacy?

With regard to your question, we have identiefied the trend Data Philanthropy which partly correspondes with the aspect you have mentioned in your comment. But data privacy and security are for sure issues which need to be solved for such an public private cooperation model.

Projects, like the H2020 Espresso project tackeling the topic by developing a smart city architecture with consideration of digital marketplaces as well as the possibility to develope and provide data related services and applications.