Pricing Schemes for Metropolitan Traffic Data Markets
نویسندگان
چکیده
Data marketplaces provide platforms for management of large data sets. The data markets are rapidly growing, yet the pricing strategies for data and data analytics are not yet well-understood. In this paper, we explore some of the pricing schemes applicable to data marketplaces in the context of transportation traffic data. This includes historical and real-time freeway and arterial congestion data. We investigate pricing raw sensor data vs. processed information (e.g, prediction of traffic patterns or route planning services) and show that, under natural assumptions, the raw data should be priced higher than processed information.
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