IRDLHCJun 15, 2017

Research Topics Map: rtopmap

arXiv:1706.04979v12 citations
Originality Synthesis-oriented
AI Analysis

This system addresses the need for researchers and institutions to map and assess research landscapes, though it is incremental as it builds on existing data and visualization techniques.

The researchers tackled the problem of visualizing and analyzing global research topics by developing rtopmap, a system that creates a weighted topics graph from Google Scholar data with over 35,000 nodes and 646,000 edges, enabling interactive exploration and institutional analysis.

In this paper we describe a system for visualizing and analyzing worldwide research topics, {\tt rtopmap}. We gather data from google scholar academic research profiles, putting together a weighted topics graph, consisting of over 35,000 nodes and 646,000 edges. The nodes correspond to self-reported research topics, and edges correspond to co-occurring topics in google scholar profiles. The {\tt rtopmap} system supports zooming/panning/searching and other google-maps-based interactive features. With the help of map overlays, we also visualize the strengths and weaknesses of different academic institutions in terms of human resources (e.g., number of researchers in different areas), as well as scholarly output (e.g., citation counts in different areas). Finally, we also visualize what parts of the map are associated with different academic departments, or with specific documents (such as research papers, or calls for proposals). The system itself is available at \url{http://rtopmap.arl.arizona.edu/}.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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