Explanation Generation over Temporal Interval Algebra

Temporal interval algebra has generated strong interest for both theoretical and practical reasons. All its Maximal Tractable Subalgebras (MTS) have been identified. Now is the time to make the transition toward their practical applications. In this chapter, the authors have proposed a formalism on how to classify an input temporal network in one of these MTSs or decide its intractability. They have also proposed a linear algorithm for checking consistency when the input belongs to one of the seventeen MTSs, and for finding the constraints responsible for inconsistency in case the network is unsatisfiable.

PLCA

This chapter describes a framework called PLCA for Qualitative Spatial Reasoning (QSR) based on the connection patterns of regions. The goal of this chapter is to provide a simple but expressive and feasible representation for qualitative data with sufficient reasoning ability. PLCA provides a symbolic representation for spatial data using simple objects. The authors of this chapter define its expression and operations on it, and show the correspondance between the expression and a figure. PLCA also provides semantical reasoning incorporated with spatial reasoning. Moreover, it can be extended to handle shapes of regions. Throughout the study, the authors discovered many topics that relate QSR to other research areas such as topology, graph theory, and computational geometry, while achieving the research goals. This indicates that QSR is a very fruitful research area.

Topical and Spatio-Temporal Search over Distributed Online Databases

In this chapter, the authors propose a novel framework for the support of multi-faceted searches over distributed Web-accessible databases. Towards this goal, the authors introduce a method for analyzing and processing a sample of the database contents in order to deduce the topical, the geographic, and the temporal orientation of the entire database contents. To extract the database topics, the authors apply techniques leveraged from the NLP community. To identify the database geographic footprints, the authors first rely on geographic ontologies in order to extract toponyms from the database content samples and then employ geo-spatial similarity metrics to estimate the geographic coverage of the identified toponyms. Finally, to determine the time aspects associated with the database entities, the authors extract temporal expressions from the entities’ contextual elements and utilize a time ontology against which the temporal similarity between the identified entities is estimated.

Region-Based Theories of Space

This chapter focuses on the topological and mereological relations, contact, and parthood, between spatio-temporal regions as axiomatized in so-called mereotopologies. Despite, or because of, their simplicity, a variety of different first-order axiomatizations have been proposed. This chapter discusses their underlying ontological choices and different ways of systematically looking at them. The chapter further gives an overview of the algebraic, topological, and graph-theoretic representations of mereotopological models which help to better understand the model-theoretic consequences of the various ontological choices. While much work on mereotopologies has been primarily theoretical, the focus started shifting towards applications and domain-specific extensions of mereotopology. These aspects will most likely guide the future direction of the field: How can mereotopologies be extended or otherwise adjusted to better suit practical needs? Moreover, the integration of mereotopology into more comprehensive and maybe more pragmatic ontologies of space and time remains another challenge in the field of region-based space.

Methodologies for Qualitative Spatial and Temporal Reasoning Application Design

Although a wide range of sophisticated Qualitative Spatial and Temporal Reasoning (QSTR) formalisms have now been developed, there are relatively few applications that apply these commonsense methods. To address this problem, the authors of this chapter developed methodologies that support QSTR application design. They established a theoretical foundation for QSTR applications that includes the roles of application designers and users. The authors adapted formal software requirements that allow a designer to specify the customer’s operational requirements and the functional requirements of a QSTR application. The chapter presents design patterns for organising the components of QSTR applications, and a methodology for defining high-level neighbourhoods that are derived from the system structure. Finally, the authors develop a methodology for QSTR application validation by defining a complexity metric called H-complexity that is used in test coverage analysis for assessing the quality of unit and integration test sets.

Reasoning about Space, Actions, and Change

Qualitative spatial conceptualizations provide a relational abstraction and interface to the metrical realities of the physical world. Humans, robots, and systems that act and interact, are embedded in space. The space itself undergoes change all the time, typically as a result of volitional actions performed by an agent, and events, both deterministic and otherwise, which occur in the environment. Both categories of occurrences are a critical link to the external world, in a predictive as well as an explanatory sense: anticipations of spatial reality conform to commonsense knowledge of the effects of actions and events on material entities. Similarly, explanations of the perceived reality too are established on the basis of such apriori established commonsense notions. The author reasons about space, actions, and change in an integrated manner, either without being able to clearly demarcate the boundaries of each type of reasoning, or because such boundaries do not exist per se. This chapter is an attempt to position such integrated reasoning as a useful paradigm for the utilization of qualitative spatial representation and reasoning techniques in relevant application domains. From a logical perspective, the author notes that formalisms already exist and that effort need only be directed at specific integration tasks at a commonsense conceptual, formal representational, and computational level.

A Region-Based Ontology of the Brain Ventricular System and Its Relation to Schizophrenia

This chapter describes an initial region-based formalisation of some concepts about neuroanatomy into ontological and epistemic terms, as part of a major effort into the formalisation of the knowledge contained in neuroimages of patients with schizophrenia. The long-term goal is to build an ontology that is a formal basis for the expectations generated from statistical data analysis. To this end, the chapter presents an example of applying this ontology to interpret the results of image-based analysis of neuroimages from schizophrenic patients.

Integrated Ontologies for Spatial Scene Descriptions

Scene descriptions are typically expressed in natural language texts and are integrated within Web pages, books, newspapers, and other means of content dissemination. The capabilities of such means can be enhanced to support automated content processing and communication between people or machines by allowing the scene contents to be extracted and expressed in ontologies, a formal syntax rich in semantics interpretable by both people and machines. Ontologies enable more effective querying, reasoning, and general use of content and allow for standardizing the quality and delivery of information across communicating information sources. Ontologies are defined using the well-established standards of the Semantic Web for expressing scene descriptions in application fields such as Geographic Information Systems, medicine, and the World Wide Web (WWW). Ontologies are not only suitable for describing static scenes with static objects (e.g., in photographs) but also enable representation of dynamic events with objects and properties changing in time (e.g., moving objects in a video). Representation of both static and dynamic scenes by ontologies, as well as querying and reasoning over static and dynamic ontologies are important issues for further research. These are exactly the problems this chapter is dealing with.

On the Representation and Recognition of Temporal Patterns of Activities in Smart Environments

This chapter introduces a framework for enabling context-aware behaviors in smart environment applications, with a special emphasis on smart homes and similar scenarios. In particular, an ontology-based architecture is described that allows system designers to specify non-trivial situations the system must be able to detect on the basis of available sensory data. Relevant situations may include activities and events that could be prolonged over long periods of time. Therefore, the ontology encodes temporal operators that, once applied to sensory information, allow the recognition and efficient correlation of different human activities and other events whose temporal relationships are contextually important. Special emphasis is devoted to actual representation and recognition of temporally distributed situations. The proof of the concept is validated through a thoroughly described example of system usage.

A Qualitative Trajectory Calculus to Reason about Moving Point Objects

A number of qualitative calculi have been developed in order to reason about space and time. A recent trend has been the emergence of integrated spatiotemporal calculi in order to deal with dynamic phenomena such as motion. In 2004, Van de Weghe introduced the Qualitative Trajectory Calculus (QTC) as a qualitative calculus to represent and reason about moving objects. This chapter presents a general overview of the principal theoretical aspects of QTC, focusing on the two most fundamental types of QTC. It shows how QTC deals with important reasoning concepts and how calculus can be employed in order to represent raw moving object data.