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Radio Frequency Identification (RFID) technology is widely
used to trace objects. However, RFID application systems can not effectively
and efficiently use massive uncertain data. This study considers some properties
of objects captured by sensor and GPS and proposes a comprehensive extensible
model for uncertain data according to key features of RFID data which is suitable
to different application scenarios. The model can effectively and efficiently
store different RFID data according to key features of RFID data and supports
a variety of queries for tracking and tracing RFID objects.
Inconsistency may arise when data are integrated together
with respect to a given set of integrity constraints. Many techniques can identify
inconsistent data by ad-hoc ways but inconsistent data can not be managed effectively.
To judge a query is rewritable, the work analyses whether the join graph for
the query is directed. Also, the work presents an approach for computing tuple
probabilities and a basic technique for query rewriting. The experiments use
the data and queries of the TPC-H specification to compare performance for degrees
of inconsistencies and the results show that the approach is effective and feasible.
