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Journal Article

Using Google Earth to access language resources


Van Uytvanck,  Dieter
Technical Group, MPI for Psycholinguistics, Max Planck Society;


Dukers,  Alex
Technical Group, MPI for Psycholinguistics, Max Planck Society;


Ringersma,  Jacquelijn
Technical Group, MPI for Psycholinguistics, Max Planck Society;


Wittenburg,  Peter
Technical Group, MPI for Psycholinguistics, Max Planck Society;

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Van Uytvanck, D., Dukers, A., Ringersma, J., & Wittenburg, P. (2007). Using Google Earth to access language resources. Language Archive Newsletter, (9), 4-7.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-2835-A
Over the past ten years Geographic Information Systems (GIS) have evolved from a highly specialised niche technology to one that is used daily by a wide range of people. This article describes geographic browsing of language archives, which provides intuitive exploration of resources and permits integration and correlation of information from different archives, even across different research disciplines. In order to facilitate both exploration and management of resources, digital language archives are organised according to criteria such as language name, research topic, project information, researchers, countries, or genres. A set of such criteria can form a tree-like classification scheme, such as in the MPI-IMDI archive, which in turn forms the main method of searching and querying the archive resources. Searching for information can be difficult for occasional users because effective use of these search-fields typically requires specialised knowledge. We assume that many non-specialist users of language resources will search by language name, language family, or geographic area, so that geographic navigation would offer a very powerful search method. We also assume that such users are familiar with maps, and that geographic browsing is more intuitive than browsing classification trees, so these users would prefer to start with a large scale map and then zoom in to find the data that interests them. Therefore, classification trees and geographic maps provide complementary methods for accessing language resources to meet the needs of different user groups. We selected Google Earth (GE) as a geographic browsing system and overlaid it with linguistic information. GE was chosen because it is available via the web, it has good navigation controls, it is familiar to many web users, and because the overlaid linguistic information can be formulated in XML, making it comparatively easy to interchange with other geographic systems.