Handling Uncertainty in Database: An Introduction and Brief Survey

Abstract

In the last years, uncertainty management became an important aspect as the presence of uncertain data increased rapidly. Due to the several advanced technologies that have been developed to record large quantity of data continuously, resulting is a data that contain errors or may be partially complete. Instead of dealing with data uncertainty by removing it, we must deal with it as a source of information. To deal with this data, database management system should have special features to handle uncertain data. The aim of this paper is twofold: on one hand, to introduce some main concepts of uncertainty in database by focusing on different data management issues in uncertain databases such as join and query processing, database integration, indexing uncertain data, security and information leakage and representation formalisms. On the other hand, to provide a survey of the current database management systems dealing with uncertain data, presenting their features and comparing them.

Uncertainty representation in software models: a survey

“…Other uncertainty classifications have also been proposed for specific domains within software development and engineering, mainly in the areas of adaptive systems [73,135,144,180,199,201,223], complex event processing [125], databases [131,156,175,178,195,200,224], requirements engineering [207], and cyber-physical systems [120,121]. All of them try to harmonize the terminology of uncertainty and propose conceptual frameworks that classify different types of uncertainty according to several criteria.…”

“…Occurrence uncertainty is also called Existential uncertainty [131,225], Record uncertainty [175] or Tuple uncertainty [195] in the database domain, although the meaning in all the cases is the same.…”

“…Similarly, we did not consider the numerous works dealing with model-based performance or reliability engineering of software systems, which enrich software models with the information required for evaluation using different notations (e.g., UML Profiles such as SPT [190], MARTE [72] or DAM [129]), transform the enriched model to a formal and mathematical model supporting the evaluation (e.g., Queueing Networks [161,217], Probabilistic Process Algebras [157], Stochastic Petri Nets [182,183], Fault Trees [143] or Markov chains [214]) and evaluate the performance or reliability of the system using the tools available for the formal model [139,127]. The interested reader can consult already existing corresponding surveys about these topics, such as [131,156,175,195,200,224] in the context of databases, [125] in the context of complex event processing, or [127,128,168,160] on model-based performance or reliability engineering of software systems. Second, we excluded papers that only describe transformations between notations representing uncertainty that are semantically equivalent.…”

Uncertainty Support in the Spectral Information System SPECCHIO

“…All three topics are generally of interest to the application in spectral databases. However, the number of available and operational uncertain DBMSs is small and their implementations are either proprietary or based on a specific relational DBMS implementation [28]. Their use in the context of an already existing information system like SPECCHIO is thus very limited or prohibitive unless a complete redesign were to be planned.…”

Framework for Managing Uncertain Distributed Categorical Data

“…With the advent of the Internet and network technology [14], there is an important emergence and unprecedented flourishing of real world applications and devices that participated to produce large amounts of uncertain data daily. e.g.…”