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    <UserNotes>Visual Understanding Environment (VUE)
https://vue.tufts.edu
https://github.com/VUE/VUE

  Flexible concept mapping tools for managing and integrating digital resources in support of 
teaching, learning and research.
  At its core, the Visual Understanding Environment (VUE) is a concept and content mapping 
application, developed to support teaching, learning and research and for anyone who needs 
to organize, contextualize, and access digital information. Using a simple set of tools and 
a basic visual grammar consisting of nodes and links, faculty and students can map 
relationships between concepts, ideas and digital content.
  Concept mapping is not new to the educational field. In fact, the benefits of concept 
mapping as a learning tool have been documented by over 40 years of cognitive science 
research. VUE provides a concept mapping interface, which can be used as such, or as an 
interface to organize digital content in non-linear ways.
  Numerous tools currently exist for locating digital information, but few applications are 
available for making sense of the information available to us. As the availability of 
digital information continues to increase, VUE sets itself apart as a flexible tool to help 
faculty and students integrate, organize and contextualize electronic content in their work. 
Digital content can be accessed via the Web, or using the VUE’s “Resources” panel to tap 
into digital repositories, FTP servers and local file systems.
  Sharing and presenting information are important aspects of academic work. VUE’s pathways 
feature allows presenters to create annotated trails through their maps, which become expert 
guided walk-throughs of the information. The pathways feature also provides a “slide view” 
of the information on the map. The power of VUE’s slide mode is the ability for presenters 
to focus on content (slide view) while preserving the information’s context (map view), by 
way of a single toggle between the two views.
  VUE also provides supports for in-depth analysis of maps, with the ability to merge maps and 
export connectivity matrices to import in statistical packages. VUE also provide tools to 
apply semantic meaning to the maps, by way of ontologies and metadata schemas.
  VUE can be used by anyone interested in visually structuring digital content, whether in 
support of teaching difficult to understand concepts or more generally, a tool for 
organizing personal digital resources.
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