{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/35975"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/35975","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Enabling Locative Experiences","abstract":"The appropriate framework to capture and share location information with mobile applications enable the development of interfaces and interface techniques that empower users to obtain and share information on the go. As such, the work in this thesis makes two major contributions. First is the SeeVT framework, a locative backbone that uses currently-available data and equipment in the Virginia Tech and Blacksburg VA environments (e.g., wireless signal triangulation, GPS signals) to make available to applications the location of the device in use. Applications built on this framework have available knowledge of the region in which the user's device is located. Second is a set of four applications built on the SeeVT framework: SeeVT – Alumni Edition (a guide for alumni returning to campus, often after lengthy absences), the Newman Project (a library information system for finding books and other library resources), VTAssist (a information sharing system for disabled users), and SeeVT-Art (a guide for users in our local inn and conference center to learn about the art on display). Key in this contribution is our identification and discussion of three interface techniques that emerged from our development efforts: an images-first presentation of information, a lightweight mobile augmented reality style of interaction, and locative content affordances that provide ways to quickly input focused types of information in mobile situations.","abstract_html":"The appropriate framework to capture and share location information with mobile applications enable the development of interfaces and interface techniques that empower users to obtain and share information on the go. As such, the work in this thesis makes two major contributions. First is the SeeVT framework, a locative backbone that uses currently-available data and equipment in the Virginia Tech and Blacksburg VA environments (e.g., wireless signal triangulation, GPS signals) to make available to applications the location of the device in use. 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