 We use structured sampling to overcome such scalability challenges and manage to compute accurately the importance of different data sources, even when their number ranges in the thousands, as in the case of all the taxi drivers in a large metropolis .
<meaning-changed>  We use structured sampling to overcome such scalability challenges and manage to compute accurately the importance of different data sources, even when their number ranges in the thousands, as in the case of all the taxi drivers in a large metropolis .
 We use structured sampling to overcome such scalability challenges and manage to compute accurately the importance of thousands of data sources. We show that the relative value of the data held by different taxi companies and drivers may differ substantially, and that its relative ranking may change from district to district within a metropolitan area .