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Multimodal interfaces combining natural language and graphics take advantage of both the individual strength of each communication mode and the fact that several modes can be employed in parallel. The central claim of this paper is that the generation of a multimodal presentation can be considered as an incremental planning process that aims to achieve a given communicative goal. We describe the multimodal presentation system WIP which allows the generation of alternate presentations of the same content taking into account various contextual factors. We discuss how the plan-based approach to presentation design can be exploited so that graphics generation influences the production of text and vice versa. We show that wellknown concepts from the area of natural language processing like speech acts, anaphora, and rhetorical relations take on an extended meaning in the context of multimodal communication. Finally, we discuss two detailed examples illustrating and reinforcing our theoretical claims.

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This article presents our steps to integrate complex and partly unstructured medical data into a clinical research database with subsequent decision support. Our main application is an integrated faceted search tool, accompanied by the visualisation of results of automatic information extraction from textual documents. We describe the details of our technical architecture (open-source tools), to be replicated at other universities, research institutes, or hospitals. Our exemplary use cases are nephrology and mammography. The software was first developed in the nephrology domain and then adapted to the mammography use case. We report on these case studies, illustrating how the application can be used by a clinician and which questions can be answered. We show that our architecture and the employed software modules are suitable for both areas of application with a limited amount of adaptations. For example, in nephrology we try to answer questions about the temporal characteristics of event sequences to gain significant insight from the data for cohort selection. We present a versatile time-line tool that enables the user to explore relations between a multitude of diagnosis and laboratory values.

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