Literature Review on Temporal, Spatial, and Spatiotermpoal Data Models

This paper reviews papers on temporal databases, spatial databases, and spatio-temporal databases

Ontology-mediated query answering over temporal data: a survey

We discuss the use of various temporal knowledge representation formalisms for ontology-mediated query answering over temporal data. In particular, we analyse ontology and query languages based on the linear temporal logic LTL, the multi-dimensional Halpern-Shoham interval temporal logic HSn, as well as the metric temporal logic MTL. Our main focus is on the data complexity of answering temporal ontology-mediated queries and their rewritability into standard first-order and datalog queries

Interval-based temporal functional dependencies: specification and verification

In the temporal database literature, every fact stored in a database may beequipped with two temporal dimensions: the valid time, which describes the time whenthe fact is true in the modeled reality, and the transaction time, which describes the timewhen the fact is current in the database and can be retrieved. Temporal functional dependencies(TFDs) add valid time to classical functional dependencies (FDs) in order to expressdatabase integrity constraints over the flow of time. Currently, proposals dealing with TFDsadopt a point-based approach, where tuples hold at specific time points, to express integrityconstraints such as \u201cfor each month, the salary of an employee depends only on his role\u201d. Tothe best of our knowledge, there are no proposals dealing with interval-based temporal functionaldependencies (ITFDs), where the associated valid time is represented by an intervaland there is the need of representing both point-based and interval-based data dependencies.In this paper, we propose ITFDs based on Allen\u2019s interval relations and discuss theirexpressive power with respect to other TFDs proposed in the literature: ITFDs allow us toexpress interval-based data dependencies, which cannot be expressed through the existingpoint-based TFDs. ITFDs allow one to express constraints such as \u201cemployees starting towork the same day with the same role get the same salary\u201d or \u201cemployees with a given roleworking on a project cannot start to work with the same role on another project that willend before the first one\u201d. Furthermore, we propose new algorithms based on B-trees to efficientlyverify the satisfaction of ITFDs in a temporal database. These algorithms guaranteethat, starting from a relation satisfying a set of ITFDs, the updated relation still satisfies thegiven ITFDs

A parametric prototype for spatiotemporal databases

The main goal of this project is to design and implement the parametric database (ParaDB). Conceptually, ParaDB consists of the parametric data model (ParaDM) and the parametric structured query language (ParaSQL). Parametric data model is a data model for multi-dimensional databases such as temporal, spatial, spatiotemporal, or multi-level secure databases. Main difference compared to the classical relational data model is that ParaDM models an object as a single tuple, and an attribute is defined as a function from parametric elements. The set of parametric elements is closed under union, intersection, and complementation. These operations are counterparts of or, and, and not in a natural language like English. Therefore, the closure properties provide very flexible ways to query on objects without introducing additional self-join operations which are frequently required in other multi-dimensional database models