Upper ontology

About: Upper ontology is a research topic. Over the lifetime, 9767 publications have been published within this topic receiving 220721 citations. The topic is also known as: top-level ontology & foundation ontology.

A cooperative framework for integrating ontologies

Abstract: Nowadays, there are systems and frameworks that support Ontology construction processes. However, ontology integration processes have not sufficiently been specified to date. In this article, by making use of a cooperative philosophy, we describe a real framework for the integration of ontologies supplied by a predetermined set of (expert) users, who may be interconnected through a communication network. This framework is based on a set of well-defined assumptions that guarantee the consistency of the ontology derived from the ontology integration process. Moreover, in the approach presented here, every (expert) user may consult the so-derived ontology constructed until a given moment in order to refine his or her private ontology. In addition to this, the model proposed in this work allows the experts involved in the construction of the ontology to use their own terminology when querying the global ontology obtained until a given instant from their own co-operative work. The validation of the framework is also included in this work.

(ONTO)2 Agent: an Ontology-based WWW broker to select ontologies

Abstract: Knowledge reuse by means of ontologies now faces three important problems: (1) there are no standardized identifying features that characterize ontologies from the user point of view; (2) there are no web sites using the same logical organization, presenting relevant information about ontologies; and (3) the search for appropriate ontologies is hard, timeconsuming and usually fruitless. To solve the above problems, we present: (1) a living set of features that allow us to characterize ontologies from the user point of view and have the same logical organization; (2) a living domain ontology about ontologies (called Reference Ontology) that gathers, describes and has links to existing ontologies; and (3) (ONTO)2Agent, the ontology-based www broker about ontologies that uses the Reference Ontology as a source of its knowledge and retrieves descriptions of ontologies that satisfy a given set of constraints. (ONTO)2Agent is available at http://delicias.dia.fi.upm.es/REFERENCE_ONTOLOGY/

An Object-Based Semantic Classification Method for High Resolution Remote Sensing Imagery Using Ontology

Abstract: Geographic Object-Based Image Analysis (GEOBIA) techniques have become increasingly popular in remote sensing. GEOBIA has been claimed to represent a paradigm shift in remote sensing interpretation. Still, GEOBIA—similar to other emerging paradigms—lacks formal expressions and objective modelling structures and in particular semantic classification methods using ontologies. This study has put forward an object-based semantic classification method for high resolution satellite imagery using an ontology that aims to fully exploit the advantages of ontology to GEOBIA. A three-step workflow has been introduced: ontology modelling, initial classification based on a data-driven machine learning method, and semantic classification based on knowledge-driven semantic rules. The classification part is based on data-driven machine learning, segmentation, feature selection, sample collection and an initial classification. Then, image objects are re-classified based on the ontological model whereby the semantic relations are expressed in the formal languages OWL and SWRL. The results show that the method with ontology—as compared to the decision tree classification without using the ontology—yielded minor statistical improvements in terms of accuracy for this particular image. However, this framework enhances existing GEOBIA methodologies: ontologies express and organize the whole structure of GEOBIA and allow establishing relations, particularly spatially explicit relations between objects as well as multi-scale/hierarchical relations.

LexOnto: A Model for Ontology Lexicons for Ontology-based NLP

Abstract: In this paper we present a model and a corresponding ontology for associating lexical information to entities of a given domain ontology In particular, we focus on representing subcategorization frames as well as their mapping to ontological structures The lexicon model and ontology can thus be used to specify the syntax-semantic interface for ontology-based NLP systems which are expected to produce output compliant with a specific domain ontology Our lexicon ontology itself is formalized in the OWL language, thus allowing the lexica to be published together with the domain ontologies We also discuss different ways how the creation of appropriate lexica can be supported

Context dependency management in ontology engineering: a formal approach

Abstract: A viable ontology engineering methodology requires supporting domain experts in gradually building and managing increasingly complex versions of ontological elements and their converging and diverging interrelationships. Contexts are necessary to formalise and reason about such a dynamic wealth of knowledge. However, context dependencies introduce many complexities. In this article, we introduce a formal framework for supporting context dependency management processes, based on the DOGMA framework and methodology for scalable ontology engineering. Key notions are a set of context dependency operators, which can be combined to manage complex context dependencies like articulation, application, specialisation, and revision dependencies. In turn, these dependencies can be used in context-driven ontology engineering processes tailored to the specific requirements of collaborative communities. This is illustrated by a real-world case of interorganisational competency ontology engineering.