Formalization and automatic interpretation of map requirements

The map requirements (constraints) can be interpreted by computer programs using their basic embedded functionalities. There are a huge number of constraints available to define the objective of various generalization outputs. Some of the constraints contain high-level knowledge which is not easy to interpret. This needs a huge amount of efforts to implement those constraints. The fact that many constraints have something in common makes the implementation per constraint a waste of resource. The paper proposes to decompose the constraints into more basic units, so as to interpret those constraints more flexible and reuse the already developed functionality as much as possible

Spatial Reasoning for the Semantic Web -Use Cases and Technological Challenges

The goal of semantic web research is to turn the World-Wide Web into a Web of Data that can be processed automatically to a much larger extend than possible with traditional web technology. Important features of the solution currently being developed is the ability to link data from from different sources and to provide formal definitions of the intended meaning of the terminology used in different sources as a basis for deriving implicit information and for conflict detection. Both requires the ability to reason about the definition of terms. With the development of OWL as the standard language for representing terminological knowledge, reasoning in description logics has been determined as the major technique for performing this reasoning So far little attention has been paid to the problem of representing and reasoning about space and time on the semantic web. In particular, existing semantic web languages are not well suited for representing these aspects as they require to operate over metric spaces that behave fundamentally different from the abstract interpretation domains description logics are based on. Nevertheless, there is a strong need to integrate reasoning about space and time into existing semantic web technologies especially because more and more data available on the web has a references to space and time. Images taken by digital cameras are a good example of such data as they come with a time stamp and geographic coordinates. In this paper, we concentrate on spatial aspects and discuss different use case for reasoning about spatial aspects on the (semantic) web and possible technological solutions for these use cases. Based on these discussions we conclude that the actual open problem is not existing technologies for terminological or spatial reasoning, but the lack of an established mechanism for combining the two. The Case for Spatial Queries One of the most central functionality that should be supported by semantic web technology is query answering over web data. The primary language for this purpose i

Dwelling on ontology - semantic reasoning over topographic maps

The thesis builds upon the hypothesis that the spatial arrangement of topographic features, such as buildings, roads and other land cover parcels, indicates how land is used. The aim is to make this kind of high-level semantic information explicit within topographic data. There is an increasing need to share and use data for a wider range of purposes, and to make data more definitive, intelligent and accessible. Unfortunately, we still encounter a gap between low-level data representations and high-level concepts that typify human qualitative spatial reasoning. The thesis adopts an ontological approach to bridge this gap and to derive functional information by using standard reasoning mechanisms offered by logic-based knowledge representation formalisms. It formulates a framework for the processes involved in interpreting land use information from topographic maps. Land use is a high-level abstract concept, but it is also an observable fact intimately tied to geography. By decomposing this relationship, the thesis correlates a one-to-one mapping between high-level conceptualisations established from human knowledge and real world entities represented in the data. Based on a middle-out approach, it develops a conceptual model that incrementally links different levels of detail, and thereby derives coarser, more meaningful descriptions from more detailed ones. The thesis verifies its proposed ideas by implementing an ontology describing the land use ‘residential area’ in the ontology editor Protégé. By asserting knowledge about high-level concepts such as types of dwellings, urban blocks and residential districts as well as individuals that link directly to topographic features stored in the database, the reasoner successfully infers instances of the defined classes. Despite current technological limitations, ontologies are a promising way forward in the manner we handle and integrate geographic data, especially with respect to how humans conceptualise geographic space

Combining Spatial and Terminological Reasoning

The paper presents a method for terminological reasoning about spatial objects on the basis of a KL-ONE-like framework (LOOM). We apply this method to the domain of deductive geographic information systems and parsing of visual languages. In contrast to existing work, which mainly focusseson reasoning about qualitative spatial relations, we integrate quantitative information with conceptual or terminological reasoning by the use of "generative" qualitative relations. These relations allow a modularization of systems for terminological reasoning and domain-specificstorage and indexing of, e.g., spatial data. Qualitative relations are computed on demand from quantitative data during forward-chaining assertional reasoning. 1 Introduction A lot of inference processes of knowledge-based systems are based on different kinds of spatial reasoning. In this paper we present an inference scheme which combines terminological reasoning with inferences about spatial data. This scheme is useful for ..