A crucial issue in terminology management is how specialized concepts should be represented so as to provide the user with an adequate understanding of their meaning as well as sufficient knowledge of their location within the general knowledge structure of a scientific or technical domain. Such a conceptual representation should contain information in various formats. In this regard, linguistic and graphical descriptions of specialized entities play a major role in knowledge representation, especially when both converge to highlight the multidimensional nature of concepts as well as the conceptual relations within a specialized domain. In this article, we explore the nature of the links between the linguistic and graphical description of specialized concepts. In a multimodal conceptual description, we believe that the structured information in terminographic definitions should mesh with the visual information in images for a better understanding of complex and dynamic concept systems.

This article describes the theoretical premises and methodology presently being used in the development of the PuertoTerm database on Coastal Engineering. In our project there are three foci, which are highly relevant to the elaboration of lexicographic and terminological products: (1) the conceptual organization underlying any knowledge resource; (2) the multidimensional nature of conceptual representations; and (3) knowledge extraction through the use of multilingual corpora. In this sense we propose a frame-based organization of specialized fields in which a dynamic, process-oriented event frame provides the conceptual underpinnings for the location of sub-hierarchies of concepts within a specialized domain event. We explain how frames with semantic and syntactic information can be specified within this type of framework, and also discuss issues regarding concept denomination and terminological meaning, based on the use of definitional schemas for each conceptual category. We also offer a typology of images for the inclusion of graphic information in each entry, depending on the nature of the concept. Notes* This research is part of the project PuertoTerm: Knowledge representation and the generation of terminological resources within the domain of Coastal Engineering, BFF2003-04720, funded by the Spanish Ministry of Education. .Although the corpus also has a significant number of German texts, for the sake of simplicity we are limiting our analysis here to English and Spanish. 2.These statistics were obtained with the Wordlist tool of the computer application Wordsmith Tools®.3. The overall difference in the type/token ratio is probably due to the fact that the relative scarcity of Coastal Engineering texts in Spanish has led to the inclusion of texts belonging to 20 Pamela Faber et al.closely related fields of knowledge, such as Environmental Science, Geology or Hydrology. This leads to a similar standardized type/token ratio (if analyzed in comparable chunks) but a differing overall type/token ratio, where the highly homogeneous English corpus is compared as a whole to the more heterogeneous Spanish corpus.

Though instrumental in numerous disciplines, context has no universally accepted definition. In specialized knowledge resources it is timely and necessary to parameterize context with a view to more effectively facilitating knowledge representation, understanding, and acquisition, the main aims of terminological knowledge bases. This entails distinguishing different types of context as well as how they interact with each other. This is not a simple objective to achieve despite the fact that specialized discourse does not have as many contextual variables as those in general language (i.e., figurative meaning, irony, etc.). Even in specialized text, context is an extremely complex concept. In fact, contextual information can be specified in terms of scope or according to the type of information conveyed. It can be a textual excerpt or a whole document; a pragmatic convention or a whole culture; a concrete situation or a prototypical scenario. Although these versions of context are useful for the users of terminological resources, such resources rarely support context modeling. In this paper, we propose a taxonomy of context primarily based on scope (local and global) and further divided into syntactic, semantic, and pragmatic facets. These facets cover the specification of different types of terminological information, such as predicate-argument structure, collocations, semantic relations, term variants, grammatical and lexical cohesion, communicative situations, subject fields, and cultures.

EcoLexicon is a terminological knowledge base (TKB) on the environment which seeks to enhance both cognitive and communicative needs of different users. In order to achieve this, TKBs should reflect conceptual structures in a similar way to how concepts relate in the human mind (Meyer et al. 1992). Categorization itself is a dynamic context-dependent process. Therefore, representation and acquisition of specialized knowledge should certainly focus on contextual variation. In EcoLexicon, such contextualization takes the form of dynamic information modules, such as conceptual networks, images, textual information, and terminological variance. Recontextualization provides a way of representing the dynamic and multidimensional nature of conceptualization processes in the mind. On the one hand, it offers a qualitative criterion for the representation of specialized concepts in line with the workings of the human conceptual system. On the other hand, it provides a quantitative solution to the problem of information overload, as it significantly reduces irrelevant context-free information.

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