The Suggested Upper Merged Ontology (SUMO) is an upper level ontology that has been proposed as a starter document for The Standard Upper Ontology Working Group, an IEEE-sanctioned working group of collaborators from the fields of engineering, philosophy, and information science. The SUMO provides definitions for general-purpose terms and acts as a foundation for more specific domain ontologies. In this paper we outline the strategy used to create the current version of the SUMO, discuss some of the challenges that we faced in constructing the ontology, and describe in detail its most general concepts and the relations between them. Categories & Descriptors --- I.2.4 [Knowledge Representation Formalisms and Methods]: Artificial Intelligence -- representations (procedural and rule-based), semantic networks. General Terms --- Documentation, Languages, Standard-ization, Theory. Keywords --- Ontologies, Knowledge Interchange Format.

. The field of Qualitative Spatial Reasoning is now an active research area in its own right within AI (and also in Geographical Information Systems) having grown out of earlier work in philosophical logic and more general Qualitative Reasoning in AI. In this paper (which is an updated version of [25]) I will survey the state of the art in Qualitative Spatial Reasoning, covering representation and reasoning issues as well as pointing to some application areas. 1 What is Qualitative Reasoning? The principal goal of Qualitative Reasoning (QR) [129] is to represent not only our everyday commonsense knowledge about the physical world, but also the underlying abstractions used by engineers and scientists when they create quantitative models. Endowed with such knowledge, and appropriate reasoning methods, a computer could make predictions, diagnoses and explain the behaviour of physical systems in a qualitative manner, even when a precise quantitative description is not available 1 ...

This paper surveys the work of the qualitative spatial reasoning group at the University of Leeds. The group has developed a number of logical calculi for representing and reasoning with qualitative spatial relations over regions. We motivate the use of regions as the primary spatial entity and show how a rich language can be built up from surprisingly few primitives. This language can distinguish between convex and a variety of concave shapes and there is also an extension which handles regions with uncertain boundaries. We also present a variety of reasoning techniques, both for static and dynamic situations. A number of possible application areas are briefly mentioned.

. Although Qualitative Reasoning has been a lively subfield of AI for many years now, it is only comparatively recently that substantial work has been done on qualitative spatial reasoning; this paper lays out a guide to the issues involved and surveys what has been achieved. The papers is generally informal and discursive, providing pointers to the literature where full technical details may be found. 1 What is Qualitative Reasoning? The principal goal of Qualitative Reasoning (QR) [86] is to represent not only our everyday commonsense knowledge about the physical world, but also the underlying abstractions used by engineers and scientists when they create quantitative models. Endowed with such knowledge, and appropriate reasoning methods, a computer could make predictions, diagnoses and explain the behaviour of physical systems in a qualitative manner, even when a precise quantitative description is not available 1 or is computationally intractable. The key to a qualitative ...

In this paper we discuss the development and application of a large formal ontology to the semantic web. The Suggested Upper Merged Ontology (SUMO) (Niles & Pease, 2001) (SUMO, 2002) is a "starter document" in the IEEE Standard Upper Ontology effort. This upper ontology is extremely broad in scope and can serve as a semantic foundation for search, interoperation, and communication on the semantic web.

. This paper develops a taxonomy of qualitative spatial relations for pairs of regions, which are all logically defined from two primitive (but axiomatised) notions. The first primitive is the notion of two regions being connected, which allows eight jointly exhaustive and pairwise disjoint relations to be defined. The second primitive is the convex hull of a region which allows many more relations to be defined. We also consider the development of the useful notions of composition tables for the defined relations and networks specifying continuous transitions between pairs of regions. We conclude by discussing what kind of criteria to apply when deciding how fine a taxonomy to create. 3 The support of the SERC under grant no. GR/G36852 and GR/H 78955 is gratefully acknowledged. Thanks are also due to Brandon Bennett, John Gooday and Nick Gotts for useful comments. y Randell is now at the Dental School, Birmingham and Cui is now at ICRF, London. 0 1 Introduction Although the us...

. This chapter surveys the work of the qualitative spatial reasoning group at the University of Leeds. The group has developed a number of logical calculi for representing and reasoning with qualitative spatial relations over regions. We motivate the use of regions as the primary spatial entity and show how a rich language can be built up from surprisingly few primitives. This language can distinguish between convex and a variety of concave shapes and there is also an extension which handles regions with uncertain boundaries. We also present a variety of reasoning techniques, both for static and dynamic situations. A number of possible application areas are briefly mentioned. 1. Introduction Qualitative Reasoning (QR) has now become a mature subfield of AI as its tenth annual international workshop, several books (e.g. (Weld and De Kleer 1990, Faltings and Struss 1992)) and a wealth of conference and journal publications testify. QR tries to make explicit our everyday commonsense kno...

The paper continues the work of Randell, Cohn and Cui on region-based qualitative representations of spatial properties and relations, built on the `logic of connection' developed by Clarke. The paper shows how taxonomies of topological properties and relations can be developed, using the single primitive `C', where C(x; y) indicates that regions x and y are `connected', meaning that their closures share at least one point. This is done by considering a specific task: deciding whether a region has the topology of a solid torus, or `doughnut', by asking questions using only terms logically derived from C. It is shown how this task could be performed under a restrictive set of assumptions about the topological properties of regions in general, and the target region in particular. These assumptions are then progressively relaxed. As this is done, the task requires the definition of successive layers of terminology, all derived ultimately from C, providing the basis ...

We propose a modular ontology of the dynamic features of reality. This amounts, on the one hand, to a purely spatial ontology supporting snapshot views of the world at successive instants of time and, on the other hand, to a purely spatiotemporal ontology of change and process. We argue that dynamic spatial ontology must combine these two distinct types of inventory of the entities and relationships in reality, and we provide characterizations of spatiotemporal reasoning in the light of the interconnections between them.

. In this paper we consider the problem of representing the shape of a region, qualitatively, within a logical theory of space. Using just two primitive notions, that of two regions connecting, and the convex hull of a region, a wide variety of concave shapes can be distinguished. Moreover, by applying the technique recursively to the inside of a region (i.e. that part of the convex hull not occupied by the region itself), a hierarchical representation at varying levels of granularity can be obtained. 1 Introduction In this paper we consider the problem of representing the shape of a region, qualitatively, within a logical theory of space, known as RCC theory (Randell and Cohn 1989, Randell, Cui and Cohn 1992, Cohn, Randell and Cui 1994). This logic originally had just one primitive notion, C(x; y), that of two regions x and y connecting. However, to make an initial attack on this problem, the notion of the convex hull of a region, conv(x) was introduced (see figure 1); this a...