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Natural language generation is now moving away from research prototypes into more practical applications. Generation functionality is also being asked to play a more significant role in established applications such as machine translation. In both cases, multilingual generation techniques have much to offer. However, the take-up of multilingual generation is being restricted by a critical lack both of large-scale linguistic resources suited to the generation task and of appropriate development environments. This paper describes kpml, a multilingual development environment that offers one possible solution to these problems. kpml aims to provide generation projects with standardized, broad-coverage, reusable resources and a basic engine for using such resources for generation. A variety of focused debugging aids ensure efficient maintenance, while supporting multilingual work such as contrastive language development and automatic merging of independently developed resources. kpml is based on a new, generic approach to multilinguality in resource description that extends significantly beyond previous approaches. The system has already been used in a number of large generation projects and is freely available to the generation community.

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This article demonstrates how a digital environment offers new opportunities for transforming qualitative data into quantitative data in order to use data mining and information visualization for mixed methods research. The digital approach to mixed methods research is illustrated by a framework which combines qualitative methods of multimodal discourse analysis with quantitative methods of data mining and information visualization in a multilevel, contextual model that will result in an integrated, theoretically well-founded, and empirically evaluated technology for analyzing large data sets of multimodal texts. The framework is applicable to situations in which critical information needs to be extracted from geotagged public data: for example, in crisis informatics, where public reports of extreme events provide valuable data sources for disaster management.Keywords multimodal discourse analysis, social semiotics, data mining, information visualization, digital mixed methods design Mixed methods research is defined as:[a]n approach to research in the social, behavioural, and health sciences in which the investigator gathers both quantitative (closed-ended) and qualitative (open-ended) data, integrates the two, and then draws interpretations based on the combined strengths of both sets of data to [better] understand research problems. (Creswell, 2015, p. 2)