Localizing Ontologies in OWL

This paper presents a model for linguistic/terminological information, which can be used in tandem with an ontological model, in order to link lexicalizations and concepts. The main aim of the proposed model is to provide multilingual information to ontologies. Interoperability with existing standard models of terminological description as well as access to authoritative linguistic resources are crucial aspects that have been considered in the design of the proposed model

Multilingual Lexical Semantic Resources for Ontology Translation

We describe the integration of some multilingual language resources in ontological descriptions, with the purpose of providing ontologies, which are normally using concept labels in just one (natural) language, with multilingual facility in their design and use in the context of Semantic Web applications, supporting both the semantic annotation of textual documents with multilingual ontology labels and ontology extraction from multilingual text sources

LIME: Towards a Metadata Module for Ontolex

The OntoLex W3C Community Group has been working for more than a year on realizing a proposal for a standard ontol-ogy lexicon model. As the core-specification of the model is almost com-plete, the group started development of additional modules for specific tasks and use cases. We think that in many usage scenarios (e.g. linguistic enrichment, lo-calization and alignment of ontologies) the discovery and exploitation of linguis-tically grounded datasets may benefit from summarizing information about their linguistic expressivity. While the VoID vocabulary covers the need for general metadata about linked datasets, this more specific information demands a dedicated extension. In this paper, we fill this gap by introducing LIME (Linguistic Metadata), a new vocabulary aiming at completing the OntoLex standard with specifications for linguistic metadata.

An Analyst’s Geospatial and Ontological Assistant

We discuss an Intelligence Analyst’s Geospatial and Ontological Assistant (IAGOA) under development that associates an intelligence analyst’s understanding of an agent’s activities with the geospatial features of the area of operation where they take place. Activities are identified with frames for the corresponding verbs from the FrameNet lexical database. A modeler, using the FrameNet OWL distribution, produces software used by the analyst to update a KML file with annotations identifying instantiations of the frames elements of the relevant frames. The Google Earth API is used for rendering KML files and scripting. The agent is tracked and the analyst’s conjecture of its activity is simulated; the analyst can redo her conjecture if need be. IAGOA’s FrameNet-based approach instantiates concepts inherent in language, making explicit the activities and the constellation of role-fillers involved in these activities

Towards a FrameNet Resource for the Legal Domain

In the AI&Law community, the importance of frame-based ontologies has been acknowledged since the early 90\u27s with the Van Kralingen\u27s proposal of a frame language for legal knowledge representation. This still appears to be a strongly felt need within the community. In this paper, we propose to face this need by developing a FrameNet resource for the legal domain based on Fillmore\u27s Frame Semantics, whose final outocme will include a frame-based lexical ontology and a legal corpus annotated with frame information. In particular, the paper focuses on methodological and design issues, ranging from the customization and extension of the general FrameNet for the legal domain to the linking of the developed resource with already existing Legal Ontologies

Challenges for the Multilingual Web of Data

The Web has witnessed an enormous growth in the amount of semantic information published in recent years. This growth has been stimulated to a large extent by the emergence of Linked Data. Although this brings us a big step closer to the vision of a Semantic Web, it also raises new issues such as the need for dealing with information expressed in different natural languages. Indeed, although the Web of Data can contain any kind of information in any language, it still lacks explicit mechanisms to automatically reconcile such information when it is expressed in ifferent languages. This leads to situations in which data expressed in a certain language is not easily accessible to speakers of other languages. The Web of Data shows the potential for being extended to a truly multilingual web as vocabularies and data can be published in a language-independent fashion, while associated language-dependent (linguistic) information supporting the access across languages can be stored separately. In this sense, the multilingual Web of Data can be realized in our view as a layer of services and resources on top of the existing Linked Data infrastructure adding i) linguistic information for data and vocabularies in different languages, ii) mappings between data with labels in different languages, and iii) services to dynamically access and traverse Linked Data across different languages. In this article we present this vision of a multilingual Web of Data. We discuss challenges that need to be addressed to make this vision come true and discuss the role that techniques such as ontology localization, ontology mapping, and cross-lingual ontology-based information access and presentation will play in achieving this. Further, we propose an initial architecture and describe a roadmap that can provide a basis for the implementation of this vision

Challenges for the multilingual Web of Data

Garcia J, Montiel-Ponsoda E, Cimiano P, Gómez-Pérez A, Buitelaar P, McCrae J. Challenges for the multilingual Web of Data. Journal of Web Semantics: Science, Services and Agents on the World Wide Web. 2012;11:63-71

How ontology based information retrieval systems may benefit from lexical text analysis

International audienceThe exponential growth of available electronic data is almost useless without efficient tools to retrieve the right information at the right time. It is now widely acknowledged that information retrieval systems need to take semantics into account to enhance the use of available information. However, there is still a gap between the amounts of relevant information that can be accessed through optimized IRSs on the one hand, and users' ability to grasp and process a handful of relevant data at once on the other. This chapter shows how conceptual and lexical approaches may be jointly used to enrich document description. After a survey on semantic based methodologies designed to efficiently retrieve and exploit information, hybrid approaches are discussed. The original approach presented here benefits from both lexical and ontological document description, and combines them in a software architecture dedicated to information retrieval and rendering in specific domains