By uncovering the hierarchical structure of scholarly citation, we can identify key papers pertaining to any search query. For a reader new to the field we can find the classic and foundational papers; for an expert we can find the latest innovations.

From patterns of scholarly citation, we use Rosvall and Bergstrom's map equation to chart the topography of science and the relations among fields and subfields.
[journal map] [paper map]

By integrating a hierarchical clustering of citation networks with semantic analysis, we develop a scalable map of scientific fields and the key research terms and topics therein.

Scientific influence is often quantified using simple citation counts, but the structure of a citation network provides far more information than can be revealed by these simple counts. This is principle behind the Eigenfactor metrics; we can better rank the importance of scientific journals or papers by viewing them in the context of the full citation network.

Classifying knowledge domains is often carried out by appeal to established disciplinary boundaries. But as defined by the purview of academic departments or the scope of scholarly journals, the fields and subfields of scientific research reflect not so much the current structure of science but rather its past history. Networks of recent citations provide a more up-to-date view of the topography of science.