Point-versus interval-based temporal data models

Abstract

The association of timestamps with various data items such as tuples or attribute values is fundamental to the management of time-varying information. Using intervals in timestamps, as do most data models, leaves a data model with a variety of choices for giving a meaning to timestamps. Specifically, some such data models claim to be point-based while other data models claim to be interval-based. The meaning chosen for timestamps is important-it has a pervasive effect on most aspects of a data model, including database design, a variety of query language properties, and query processing techniques, e.g., the availability of query optimization opportunities. This paper precisely defines the notions of point-based and interval-based temporal data models, thus providing a new, formal basis for characterizing temporal data models and obtaining new insights into the properties of their query languages. Queries in point-based models treat snapshot equivalent argument relations identically. This renders point-based models insensitive to coalescing. In contrast, queries in interval-based models give significance to the actual intervals used in the timestamps, thus generally treating non-identical, but possibly snapshot equivalent, relations differently. The paper identifies the notion of timefragment preservation as the essential defining property of an interval-based data model.

Reconciling point-based and interval-based semantics in temporal relational databases: a treatment of the telic/atelic distinction

“…For instance, in our phone-call example, one could add an additional attribute containing the sequence number of calls for each phone number to ensure that relations contain no valueequivalent tuples (see the table PHONE AT T R in Table 7). However, in the example above and in many practical cases, forcing that no value-equivalent tuples occur in base relations imposes a strong requirement on database designers, who need to introduce new attributes which are often scarcely useful and informative [7]. Moreover, the problems discussed in this paper would arise again for derived relations.…”

“…However, the distinction between point-based and interval-based approaches in TDBs (see, e.g., [41], [43], [12], [7], [8]) is an entirely different one than the distinction in the above areas. In this paper, we show how the latter distinction can be profitably incorporated into temporal models and query languages and, in fact, we argue that this distinction is in some ways more central than the similarly named but orthogonal distinction in temporal databases.…”

CHOROCHRONOS - Research on Spatio-temporal Database Systems

“…The team at Aalborg has continued previous research on temporal query languages. First, a framework consisting of temporal relations and algebraic operations on these has been provided, within which query language properties, e.g., the notion of snapshot equivalence, the reducibility of algebraic operators, and the notions of point-based and interval-based semantics have been studied formally [1]. This framework may be generalized to cover also spatial aspects.…”

Towards Ontology-Based Event Processing

“…Regarding time, we assume a point-based time semantics [3] for events; an event e as a pair (G,t), where G is an RDF graph containing the event statements and t is the associated timestamps. A partial ordering is established among events, i.e.…”