Point-versus interval-based temporal data models

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. The 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 time fragment preservation as the essential defining property of an interval based data model.