TEMPOS: A Platform for Developing Temporal Applications on Top of Object DBMS

This paper presents TEMPOS: a set of models and languages supporting the manipulation of temporal data on top of object DBMS. The proposed models exploit object-oriented technology to meet some important, yet traditionally neglected design criteria related to legacy code migration and representation independence. Two complementary ways for accessing temporal data are offered: a query language and a visual browser. The query language, namely TempOQL, is an extension of OQL supporting the manipulation of histories regardless of their representations, through fully composable functional operators. The visual browser offers operators that facilitate several time-related interactive navigation tasks, such as studying a snapshot of a collection of objects at a given instant, or detecting and examining changes within temporal attributes and relationships. TEMPOS models and languages have been formalized both at the syntactical and the semantical level and have been implemented on top of an object DBMS. The suitability of the proposals with regard to applications' requirements has been validated through concrete case studies

Combining Geospatial and Temporal Ontologies

Publicly available ontologies are growing in number at present. These ontologies describe entities in a domain and the relations among these entities. This thesis describes a method to automatically combine a pair of orthogonal ontologies using cross products. A geospatial ontology and a temporal ontology are combined in this work. Computing the cross product of the geospatial and the temporal ontologies gives a complete set of pairwise combination of terms from the two ontologies. This method offers researchers the benefit of using ontologies that are already existing and available rather than building new ontologies for areas outside their scope of expertise. The resulting framework describes a geospatial domain over all possible temporal granularities or levels, allowing one domain to be understood from the perspective of another domain. Further queries on the framework help a user to make higher order inferences about a domain. In this work, Protege, an open source ontology editor and a knowledge base tool, is used to model ontologies. Protege supports the creation, visualization and manipulation of ontologies in various formats including XML (Extensible Markup Language). Use of standard and extensible languages like XML allows sharing of data across different information systems, and thus supports reuse of these ontologies. Both the geospatial ontology and the temporal ontology are represented in Protege. This thesis demonstrates the usefulness of this integrated spatio-temporal framework for reasoning about geospatial domains. SQL queries can be applied to the cross product to return to the user different kinds of information about their domain. For example, a geospatial term Library can be combined with all terms from the temporal ontology to consider Library over all possible kinds of times, including those that might have been overlooked during previous analyses. Visualizations of cross product spaces using Graphviz provides a means for displaying the geospatial-temporal terms as well as the different relations that link these terms. This visualization step also highlights the structure of the cross product for users. In order to generate a more tractable cross product for analysis purposes, methods for filtering terms from the cross product are also introduced. Filtering results in a more focused understanding of the spatio-temporal framework

Enhancing Natural Interaction with Circumstantial Knowledge

This work focuses the circumstantial knowledge management for a specific need: the achievement of Natural Interaction (NI). In first place, a cognitive approach to NI is glanced as the framework for such knowledge management. This approach reflects some certain requirements for the whole interaction system, which are met by a multi-agent system implementation. Finally, a Situation Modeling is proposed for a first approach to the interaction circumstances management.The presented work has been developed within the MAVIR project (S-505/TIC/0267) endorsed by the Regional Government of Madrid, and is being extended through the SOPAT project (CIT-410000-2007-12), supported by the Spanish Ministry of Science and Education.Publicad

A Spatio-Temporal Framework for Managing Archeological Data

Space and time are two important characteristics of data in many domains. This is particularly true in the archaeological context where informa- tion concerning the discovery location of objects allows one to derive important relations between findings of a specific survey or even of different surveys, and time aspects extend from the excavation time, to the dating of archaeological objects. In recent years, several attempts have been performed to develop a spatio-temporal information system tailored for archaeological data. The first aim of this paper is to propose a model, called Star, for repre- senting spatio-temporal data in archaeology. In particular, since in this domain dates are often subjective, estimated and imprecise, Star has to incorporate such vague representation by using fuzzy dates and fuzzy relationships among them. Moreover, besides to the topological relations, another kind of spatial relations is particularly useful in archeology: the stratigraphic ones. There- fore, this paper defines a set of rules for deriving temporal knowledge from the topological and stratigraphic relations existing between two findings. Finally, considering the process through which objects are usually manually dated by archeologists, some existing automatic reasoning techniques may be success- fully applied to guide such process. For this purpose, the last contribution regards the translation of archaeological temporal data into a Fuzzy Temporal Constraint Network for checking the overall data consistency and reducing the vagueness of some dates based on their relationships with other ones

Linking Moving Object Databases with Ontologies

This work investigates the supporting role of ontologies for supplementing the information contained in moving object databases. Details of the spatial representation as well as the sensed location of moving objects are frequently stored within a database schema. However, this knowledge lacks the semantic detail necessary for reasoning about characteristics that are specific to each object. Ontologies contribute semantic descriptions for moving objects and provide the foundation for discovering similarities between object types. These similarities can be drawn upon to extract additional details about the objects around us. The primary focus of the research is a framework for linking ontologies with databases. A major benefit gained from this kind of linking is the augmentation of database knowledge and multi-granular perspectives that are provided by ontologies through the process of generalization. Methods are presented for linking based on a military transportation scenario where data on vehicle position is collected from a sensor network and stored in a geosensor database. An ontology linking tool, implemented as a stand alone application, is introduced. This application associates individual values from the geosensor database with classes from a military transportation device ontology and returns linked value-class pairs to the user as a set of equivalence relations (i.e., matches). This research also formalizes a set of motion relations between two moving objects on a road network. It is demonstrated that the positional data collected from a geosensor network and stored in a spatio-temporal database, can provide a foundation for computing relations between moving objects. Configurations of moving objects, based on their spatial position, are described by motion relations that include isBehind and inFrontOf. These relations supply a user context about binary vehicle positions relative to a reference object. For example, the driver of a military supply truck may be interested in knowing what types of vehicles are in front of the truck. The types of objects that participate in these motion relations correspond to particular classes within the military transportation device ontology. This research reveals that linking a geosensor database to the military transportation device ontology will facilitate more abstract or higher-level perspectives of these moving objects, supporting inferences about moving objects over multiple levels of granularity. The details supplied by the generalization of geosensor data via linking, helps to interpret semantics and respond to user questions by extending the preliminary knowledge about the moving objects within these relations