摘要：Access to public data in the United States and elsewhere has steadily increased as governments have launched geospatially-enabled web portals like Socrata, CKAN, and Esri Hub. However, data discovery in these portals remains a challenge for the average user. Differences between users' colloquial search terms and authoritative metadata impede data discovery. For example, a motivated user with expertise can leverage valuable public data about transportation, real estate values, and crime, yet it remains difficult for the average user to discover and leverage data. To close this gap, community dashboards that use public data are being developed to track initiatives for public consumption; however, dashboards still require users to discover and interpret data. Alternatively, local governments are now developing data discovery systems that use voice assistants like Amazon Alexa and Google Home as conversational interfaces to public data portals. We explore these emerging technologies, examining the application areas they are designed to address and the degree to which they currently leverage existing open public geospatial data. In the context of ongoing technological advances, we envision using core concepts of spatial information to organize the geospatial themes of data exposed through voice assistant applications. This will allow us to curate them for improved discovery, ultimately supporting more meaningful user questions and their translation into spatial computations.
关键词：data discovery; open public data; voice assistants; essential model; GIS
