Time modeling is an important issue in information management. Both traditional and soft computing approaches have been thoroughly studied in the existing literature. Traditional approaches are specifically designed to efficiently deal with perfect temporal data. Soft computing techniques additionally support the efficient handling of imperfect temporal data. In this paper, a novel soft computing technique is presented, based on fuzzy set theory and using possibility theory, to represent, handle, and reason with time intervals that have uncertain starting and/or ending boundaries. Hereby, a 2-D visualization approach, which is called the triangular model, is generalized to efficiently and effectively cope with such time intervals subject to uncertainty. The proposed approach provides a straightforward and compact visualization for possibilistic interval data, which supports temporal analytical processing and in which temporal distributions are easy to observe, explore, and analyze. Moreover, it is shown how temporal analysis can be carried out using the proposed novel approach. In this context, both the presence and absence of uncertainty in one or more time intervals are supported. The value of the proposed novel approach is demonstrated through the development of two illustrative use cases.

Currently, many existing information systems contain large amounts of data. Prior research shows that many of these data represent time (domain) intervals and many of those may be subject to uncertainty. Moreover, great attention has been attracted by defining, finding or using qualitative temporal relationships between time (domain) intervals. In this context, the framework of Allen relationships is one of the most notable proposals. As a consequence, many existing proposals consider qualitative temporal relationships between time (domain) intervals subject to uncertainty on one hand and regular time (domain) intervals on the other. One of the most novel approaches in this context is given by the ill-known constraints framework. However, this framework does not yet support comparisons between time (domain) intervals subject to uncertainty. In this paper, a proposal is presented to expand this ill-known constraints framework in order to allow it to support the aforementioned temporal comparison, based on the Allen relationships.

Querying large databases containing imperfect data requires efficient indexing techniques. Without such techniques query processing would simply take too much time. Considering a possibility based database modelling approach, imperfect data are modelled using a possibility distribution. The possibility distributions used for data modelling in different database records have to be indexed in order to support a faster processing of query conditions that act on the imperfect data. In this paper we study the indexing of imperfect temporal data in the Diplomata Belgica database, which has been co-developed by our research group. Diplomata Belgica is a relational database describing medieval charters written and issued in the southern Low Countries. More specifically, we study how imperfect data on the issuing date of a charter can be modelled and indexed in order to support searches for charters with an issuing date that is compatible with `fuzzy' query preferences provided by the user. A novel, so-called Interval B+-Tree (IBPT) indexing technique is proposed and some illustrative examples of (the handling of) complex, realistic queries are given.

Databases contain data and database systems governing such databases are often intended to allow a user to query these data. On one hand, these data may be subject to imperfections, on the other hand, users may employ imperfect query preference specifications to query such databases. All of these imperfections lead to each query answer being accompanied by a collection of quantifications indicating how well (part of) a group of data complies with (part of) the user's query. A fundamental question is how to present the user with the query answers complying best to his or her query preferences. The work presented in this paper first determines the difficulties to overcome in reaching such presentation. Mainly, a useful presentation needs the ranking of the query answers based on the aforementioned quantifications, but it seems advisable to not combine quantifications with different interpretations. Thus, the work presented in this paper continues to introduce and examine a novel technique to determine a query answer ranking. Finally, a few aspects of this technique, among which its computational efficiency, are discussed.