A Relational Model for the Possibilistic Valid-time Approach

Abstract

In real world, it is very common that some objects or concepts have properties with a time-variant or timerelated nature. Modelling this kind of objects or concepts in a (relational) database schema is possible, but time-variant and time-related attributes have an impact on the consistency of the entire database and must be appropriately managed. Therefore, temporal database models have been proposed to deal with this problem in the literature. Time can be affected by imprecision, vagueness and / or uncertainty, since existing time measuring devices are inherently imperfect. Additionally, human beings manage time using temporal indications and temporal notions, which may also be imprecise. However, the imperfection in human-used temporal indications is supported by human interpretation, whereas information systems need appropriate support in order to accomplish this task. Several proposals for dealing with such imperfections when modelling temporal data exist. Some of these proposals transform the temporal data into a compact representation but there is not a formal model for managing and handling uncertainty regarding temporal information. In this work we present a novel model to deal with imprecision in valid-time databases together with the definition and implementation of the data manipulation language, DML.

Combining quantifications for flexible query result ranking

“…In this paper, a quantification is exactly this: a numerical value expressing a valuation. Thus, a similar data collection is again considered a query answer, but, compliance to the user's preferences is now a matter of degrees (quantifications) [2]- [7], [10]- [13], [15]- [17], [19]. For example, the result set of the last example query applied to the example relation visualized in table I might take the form of the set of tuples visualized in table II.…”

Bipolar Querying of Valid-Time Intervals Subject to Uncertainty

“…These temporal values are usually either time intervals [1] or instants [1], which may informally be seen as infinitesimally short 'periods' or 'points' in time. Based on their interpretation and purpose, temporal values can be classified into several categories, but the presented work will only consider valid-time indications, which indicate when corresponding data is a valid or true representation of the reality modelled by its database [1][2][3][4].…”

“…Of course, data representing temporal values may contain such imperfections too [2][3][4], [7]. The work presented in this paper will consider databases containing data representing validtime intervals subject to uncertainty and will assume all non-temporal data in these databases to contain no imperfections.…”

“…Hence, several proposals have considered specific sets of temporal operators, often based on the possible temporal relationships between two time indications [2], [14], [15]. Such temporal relationships define semantically meaningful relationships with a temporal nature, between two time indications.…”

“…Techniques for the regular or fuzzy querying of valid-time databases containing valid-time data subject to uncertainty are considered by several existing proposals [2], [4], [17]. However, to the knowledge of the authors, only one proposal has considered the bipolar querying of valid-time databases (in [18], a technique is proposed to query a valid-time database containing temporal data subject to imprecision in a bipolar way) and none have considered the bipolar querying of valid-time databases containing temporal data subject to uncertainty.…”