Catálogo de publicaciones - libros

This paper reviews progress on the Ethnophysiography study of the Yindjibarndi language from the Pilbara region of Western Australia. Concentrating on terms for water-related features, it concludes that there are significant differences to the way such features are conceptualized and spoken of in English. Brief comments regarding a similar project with the Diné (Navajo) people of Southwestern USA are provided, together with conclusions regarding Ethnophysiography.

This paper examined cultural impacts on absolute and relative location estimates of 12 Eastern Chinese cities, based on questionnaires of each city’s latitude and distances between city pairs. Linear regression analysis of the latitude estimates revealed that the estimated latitude of a city is statistically significantly related to its actual latitude. MDS analysis of the distance estimates revealed the gap that divided Eastern China into two regions and cultural-related causation of the gap was explained in detail. In particular, the Chinese language and its impact on spatial cognition were addressed. Results were compared with North America; some important features of spatial cognition were similar: the categorical storage of spatial information and the absolute-relative location reasoning process.

How do we reason about topological relations? Do people with different cultural backgrounds differ in how they reason about such relations? We conducted two topological reasoning experiments, one in Germany and one in Mongolia to analyze such questions. Topological relations such as “A overlaps B”, “B lies within C” were presented to the participants as premises and they had to find a conclusion that was consistent with the premises (“What is the relation between A and C?”). The problem description allowed multiple possible “conclusions”. Our results, however, indicate that the participants had strong preferences: They consistently preferred one of the possible conclusions and neglected other conclusions, although they were also consistent with the premises. The preferred and neglected conclusions were quite similar in Germany and Mongolia.

Ancient Greek literature gives us many relevant traces of the way people represented maritime spaces. Greek narratives endow these spaces with meaning and make them legible. Indeed, these testimonies are a significant contribution to our knowledge of the “odological” space at sea, a space of description including numerous cultural features rather than a space described. This space is based on experiential data: Greek sailors did not have at their disposal scientific means of calculating a fix or using dead reckoning navigation techniques. In these conditions, their representation of maritime spaces integrates both qualitative and quantitative features, that somehow renew Aristotle’s of “quality” and “quantity”. These features are mainly based on chronological grounds and on an experiential vision of spatial relations, that match the organization of space with the organization of human maritime activities and modify the representation of boundaries.

This paper shows how to use a top-level ontology to create robust and logically coherent domain ontology in a way that facilitates computational implementation and interoperability. It uses a domain ontology of ecosystem classification and delineation outlined informally Bailey’s paper on ‘Delineation of Ecoregions’ as a running example. Baily’s (from an ontological perspective) rather imprecise and ambiguous definitions are made more logically rigorous and precise by (a) restating the informal definitions formally using the top-level terms whose semantics was specified rigorously in a logic-based top-level ontology and (b) by enforcing the clear distinction of types of relations as specified at the top-level and specific relations of a given type as they occur in the ecosystem domain. In this way it becomes possible to formally distinguish a number of relations which logical interrelations are important but which have been confused and been taken to be a single relation before.

This paper analyses the semantics of natural language expressions that are associated with the intuitive notion of ‘place’. We note that the nature of such terms is highly contested, and suggest that this arises from two main considerations: 1) there are a number of logically distinct categories of place expression, which are not always clearly distinguished in discourse about ‘place’; 2) the many place count nouns (such as ‘place’, ‘region’, ‘area’, etc.) employed in natural language are highly ambiguous. With respect to consideration 1), we propose that place-related expressions should be classified into the following distinct logical types: a) ‘place-like’ count nouns (further subdivided into abstract, spatial and substantive varieties), b) proper names of ‘place-like’ objects, c) locative property phrases, and d) definite descriptions of ‘place-like’ objects. We outline possible formal representations for each of these. To address consideration 2), we examine meanings, connotations and ambiguities of the English vocabulary of abstract and generic place count nouns, and identify underlying elements of meaning, which explain both similarities and differences in the sense and usage of the various terms.

Higher level semantics are considered useful in the geospatial domain, yet there is no general consensus on the form these semantics should take. Indeed, knowledge representation paradigms such as classification based ontologies do not always pay tribute to the complexity of geospatial semantics. Other approaches, originating from psychology, linguistics, philosophy or cognitive sciences are regularly investigated to enrich the GIScientist’s representational toolbox. However, each of these techniques is often used to the exclusion of others, creating new representational difficulties, or merely as a useful addendum to host theories with which they only superficially integrate. The present work is an attempt to introduce a common ground to these techniques by reducing them to the notion of or . Differences are discernible properties of the environment, detected or produced by a computational process. I describe the following semantic frameworks: category-based ontologies, conceptual spaces, affordance based models, image schemata, and multi representation, explaining how each of them can be projected to a model based on differences. Illustrative examples from table top and geographic space are produced in order to show the model in use.

Consistent and flawless communication between humans and machines is the precondition for a computer to process instructions correctly. While machines use well-defined languages and formal rules to process information, humans prefer natural language expressions with vague semantics. Similarity comparisons are central to the human way of thinking: we use similarity for reasoning on new information or new situations by comparing them to knowledge gained from similar experiences in the past. It is necessary to overcome the differences in representing and processing information to avoid communication errors and computation failures. We introduce an approach to formalize the semantics of natural language spatial relations and specify it in a computational model which allows for similarity comparisons. This paper describes an experiment that investigates human similarity perception between spatial relations and compares it to the similarity determined by the our semantic similarity measure.

When interacting with the environment subjects tend to classify entities with respect to the functionalities they offer for solving specific tasks. The theory of affordances accounts for this agent-environment interaction, while similarity allows for measuring resemblances among entities and entity types. Most similarity measures separate the similarity estimations from the context—the agents, their tasks and environment—and focus on structural and static descriptions of the compared entities and types. This paper argues that an affordance-based representation of the context in which similarity is measured, makes the estimations situation-aware and therefore improves their quality. It also leads to a better understanding of how unfamiliar entities are grouped together to ad-hoc categories, which has not been explained in terms of similarity yet. We propose that types of entities are the more similar the more common functionalities their instances afford an agent. This paper presents a framework for representing affordances, which allows determining similarity between them. The approach is demonstrated through a planning task.

How we categorize certain objects depends on the processes they afford: something is a vehicle because it affords transportation, a house because it offers shelter or a watercourse because water can flow in it. The hypothesis explored here is that image schemas (such as LINK, CONTAINER, SUPPORT, and PATH) capture abstractions that are essential to model affordances and, by implication, categories. To test the idea, I develop an algebraic theory formalizing image schemas and accounting for the role of affordances in categorizing spatial entities.