{"id":563625,"date":"2019-01-22T13:10:01","date_gmt":"2019-01-22T21:10:01","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=563625"},"modified":"2019-05-17T09:21:13","modified_gmt":"2019-05-17T16:21:13","slug":"affinity-lens-data-assisted-affinity-diagramming-with-augmented-reality","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/affinity-lens-data-assisted-affinity-diagramming-with-augmented-reality\/","title":{"rendered":"Affinity Lens: Data-Assisted Affinity Diagramming with Augmented Reality"},"content":{"rendered":"<div>Despite the availability of software to support Affinity Diagramming (AD), practitioners still largely favor physical\u00a0sticky-notes. Physical notes are easy to set-up, can be moved\u00a0around in space and offer flexibility when clustering unstructured data. However, when working with mixed data\u00a0sources such as surveys, designers often trade off the physicality of notes for analytical power. We propose Affinity\u00a0Lens, a mobile-based augmented reality (AR) application for\u00a0Data-Assisted Affinity Diagramming (DAAD). Our application provides just-in-time quantitative insights overlaid on\u00a0physical notes. Affinity Lens uses several different types of\u00a0AR overlays (called lenses) to help users find specific notes,\u00a0cluster information, and summarize insights from clusters.\u00a0Through a formative study of AD users, we developed design\u00a0principles for data-assisted AD and an initial collection of\u00a0lenses. Based on our prototype, we find that Affinity Lens supports easy switching between qualitative and quantitative \u2018views\u2019 of data, without surrendering the lightweight benefits of existing AD practice.<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Despite the availability of software to support Affinity Diagramming (AD), practitioners still largely favor physical\u00a0sticky-notes. Physical notes are easy to set-up, can be moved\u00a0around in space and offer flexibility when clustering unstructured data. However, when working with mixed data\u00a0sources such as surveys, designers often trade off the physicality of notes for analytical power. We propose 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