Recognizing Determinism in Prioritized Repairing of Inconsistent Databases

Abstract. A repair of an inconsistent database is traditionally defined as a consistent database that differs from the inconsistent one in a "minimal way." As there are often reasons to prefer one repair over another, researchers have introduced and investigated the framework of preferred repairs, where a priority relation between facts is lifted towards a priority relation between consistent databases, and repairs are restricted to ones that are optimal in the lifted sense. In this paper we describe our recent results on the complexity of deciding whether the priority relation suffices to clean the database unambiguously, or in other words, whether there is exactly one optimal repair. In particular, we show that different conventional semantics of priority lifting entail highly different complexities

Consistent Query Answers in the Presence of Universal Constraints

The framework of consistent query answers and repairs has been introduced to alleviate the impact of inconsistent data on the answers to a query. A repair is a minimally different consistent instance and an answer is consistent if it is present in every repair. In this article we study the complexity of consistent query answers and repair checking in the presence of universal constraints. We propose an extended version of the conflict hypergraph which allows to capture all repairs w.r.t. a set of universal constraints. We show that repair checking is in PTIME for the class of full tuple-generating dependencies and denial constraints, and we present a polynomial repair algorithm. This algorithm is sound, i.e. always produces a repair, but also complete, i.e. every repair can be constructed. Next, we present a polynomial-time algorithm computing consistent answers to ground quantifier-free queries in the presence of denial constraints, join dependencies, and acyclic full-tuple generating dependencies. Finally, we show that extending the class of constraints leads to intractability. For arbitrary full tuple-generating dependencies consistent query answering becomes coNP-complete. For arbitrary universal constraints consistent query answering is \Pi_2^p-complete and repair checking coNP-complete.Comment: Submitted to Information System

Processing Uncertain RFID Data in Traceability Supply Chains

Radio Frequency Identification (RFID) is widely used to track and trace objects in traceability supply chains. However, massive uncertain data produced by RFID readers are not effective and efficient to be used in RFID application systems. Following the analysis of key features of RFID objects, this paper proposes a new framework for effectively and efficiently processing uncertain RFID data, and supporting a variety of queries for tracking and tracing RFID objects. We adjust different smoothing windows according to different rates of uncertain data, employ different strategies to process uncertain readings, and distinguish ghost, missing, and incomplete data according to their apparent positions. We propose a comprehensive data model which is suitable for different application scenarios. In addition, a path coding scheme is proposed to significantly compress massive data by aggregating the path sequence, the position, and the time intervals. The scheme is suitable for cyclic or long paths. Moreover, we further propose a processing algorithm for group and independent objects. Experimental evaluations show that our approach is effective and efficient in terms of the compression and traceability queries

Preference-driven querying of inconsistent relational databases

Abstract. One of the goals of cleaning an inconsistent database is to remove conflicts between tuples. Typically, the user specifies how the conflicts should be resolved. Sometimes this specification is incomplete, and the cleaned database may still be inconsistent. At the same time, data cleaning is a rather drastic approach to conflict resolution: It removes tuples from the database, which may lead to information loss and inaccurate query answers. We investigate an approach which constitutes an alternative to data cleaning. The approach incorporates preference-driven conflict resolution into query answering. The database is not changed. These goals are achieved by augmenting the framework of consistent query answers through various notions of preferred repair. We axiomatize desirable properties of preferred repair families and propose different notions of repair optimality. Finally, we investigate the computational complexity implications of introducing preferences into the computation of consistent query answers.