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We explore data management for longitudinal study survey instruments: (i) Survey instrument evolution presents a unique data integration challenge; and (ii) Longitudinal study data frequently requires repeated, task-specific integration efforts. We present DDM (Drag, Drop, Merge), a user interface for documenting relationships among attributes of source schemas into a form that can streamline subsequent efforts to generate task-specific datasets. DDM employs a "human-in-the-loop" approach, allowing users to validate and refine semantic mappings. Through a simulation of user interactions with DDM, we demonstrate its viability as a way to reduce cognitive overhead for longitudinal study data curators. 

With more than seventy named languages, and many more locally distinctive varieties, the Cameroonian Grassfields are known for their impressive linguistic diversity. At the same time, the languages of the Grassfields also show a considerable degree of structural homogeneity and lexical similarity which is suggestive of both genealogical relatedness and prolonged processes of contact-induced convergence. However, fine-grained comparative analyses reveal puzzling situations of similarities and differences among neighboring languages and varieties. Often left unaddressed or viewed as “irregularities”, these cases might in fact provide insights into low-level language dynamics that have contributed significantly to the development of the regional linguistic configuration. In this paper, we focus on two such cases involving noun classes and tense-aspect marking and propose a model of language change based on a notion that we term the social semiosis layer, which is viewed as a specific part of a linguistic feature pool. When paired with the existing notion of neighbor opposition, it can account for situations where there is evidence that specific forms have been deliberately manipulated to create salient distinctions among varieties in a given local sociolinguistic context. 

https://www.languageonthemove.com/message-vs-community-centered-models-in-risk-communication/