Abstract.We concentrate on the use of ontologies for the categorization of objects, e.g., photos, books, web pages. Lightweight ontologies are ontologies with a tree structure where each node is associated a natural language label. Faceted lightweight ontologies are lightweight ontologies where the labels of nodes are organized according to certain predefined patterns which capture different aspects of meaning, i.e., facets. We introduce facets based on the Analytico-Synthetic approach, a well established methodology from Library Science which has been successfully used for decades for the classification of books. Faceted lightweight ontologies have a well defined structure and, as such, they are easier to create, to share among users, and they also provide more organized input to semantics based applications, such as semantic search and navigation.
So far, within the Library and Information Science (LIS) community, Knowledge Organization (KO) has developed its own very successful solutions to document search, allowing for the classification, indexing and search of millions of books. However, current KO solutions are limited in expressivity as they only support queries by document properties, e.g., by title, author and subject. In parallel, within the Artificial Intelligence and Semantic Web communities, Knowledge Representation (KR), has developed very powerful end expressive techniques which, via the use of ontologies, support queries by any entity property (e.g., the properties of the entities described in a document). However, KR has not scaled yet to the level of KO, mainly because of the lack of a precise and scalable entity specification methodology. In this paper we present DERA, a new methodology, inspired by the faceted approach, as introduced in KO, that retains all the advantages of KR and compensates for the limitations of KO. DERA guarantees at the same time quality, extensibility, scalability and effectiveness in search. searches exploiting document properties. A typical example of supported query is the following:
The article identifies the core literature available on flood ontologies and presents a review on these ontologies from various perspectives like its purpose, type, design methodologies, ontologies (re)used, and also their focus on specific flood disaster phases. The study was conducted in two stages: i) literature identification, where the systematic literature review methodology was employed; and, ii) ontological review, where the parametric approach was applied. The study resulted in a set of fourteen papers discussing the flood ontology (FO). The ontological review revealed that most of the flood ontologies were task ontologies, formal, modular, and used web ontology language (OWL) for their representation. The most (re)used ontologies were SWEET, SSN, Time, and Space. METHONTOLOGY was the preferred design methodology, and for evaluation, application-based or data-based approaches were preferred. The majority of the ontologies were built around the response phase of the disaster. The unavailability of the full ontologies somewhat restricted the current study as the structural ontology metrics are missing. But the scientific community, the developers, of flood disaster management systems can refer to this work for their research to see what is available in the literature on flood ontology and the other major domains essential in building the FO.
Abstract. Geo-spatial ontologies provide knowledge about places in the world and spatial relations between them. They are fundamental in order to build semantic information retrieval systems and to achieve semantic interoperability in geo-spatial applications. In this paper we present GeoWordNet, a semantic resource we created from the full integration of GeoNames, other high quality resources and WordNet. The methodology we followed was largely automatic, with manual checks when needed. This allowed us accomplishing at the same time a never reached before accuracy level and a very satisfactory quantitative result, both in terms of concepts and geographical entities.
We concentrate on geospatial ontologies. Our main contribution in this paper is a methodology and a minimal set of guiding principles, inspired by the faceted approach, as originally developed in library science, and a large-scale ontology for Space that we have constructed following the methodology proposed. The approach we propose, centered on the fundamental notions of domain and facet, guarantees the creation of high-quality ontologies in terms of robustness, extensibility, reusability, compactness and flexibility. Taking into account the different aspects of Space, the ontology we have developed, and that we have obtained from the refinement and extension of some existing resources including GeoNames, WordNet and the Italian part of MultiWordNet, provides knowledge about places of the world, their classes, their attributes and the spatial relations between them. The construction procedure was manual for the identification and categorization into facets of the terms denoting classes, relations and attribute names, while it was automatic for the population of the ontology with entities and corresponding attribute values. This has allowed us to obtain a very satisfactory quantitative and qualitative result. This paper is a substantially revised and extended version of two papers. The first was entitled "GeoWordNet: a resource for geospatial applications" and was presented at the ESWC 2010 conference [20]; the second was entitled "A facet-based methodology for geospatial modeling" and was presented at the GEOS 2011 conference [10]. The ontology presented in this paper is an extension of GeoWordNet, a semantic and linguistic resource distributed as open source that can be freely downloaded from http://geowordnet.semanticmatching.org/.
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