  The Internet of Things (IoT) is a cyber physical social system that
encompasses science, enterprise and societal domains. Data is the most
important commodity in IoT, enabling the "smarts" through analytics and
decision making. IoT environments can generate and consume vast amounts of
data. But managing this data effectively and gaining meaningful insights from
it requires us to understand its characteristics. Traditional scientific,
enterprise and big data management approaches may not be adequate, and have to
evolve. Further, these characteristics and the physical deployment environments
also impact the quality of the data for use. In this paper, we offer a taxonomy
of IoT data characteristics, along with data quality considerations, that are
constructed from the ground-up based on the diverse IoT domains and
applications we review. We emphasize on the essential features, rather than a
vast array of attributes. We also indicate factors that influence the data
quality. Such a review is of value to IoT managers, data handlers and
application composers in managing and making meaningful use of data, and for
big data platform developers to offer meaningful solutions to address these
considerations.
