We investigate how author name homonymy distorts clustered large-scale
co-author networks, and present a simple, effective, scalable and generalizable
algorithm to ameliorate such distortions. We evaluate the performance of the
algorithm to improve the resolution of mesoscopic network structures. To this
end, we establish the ground truth for a sample of author names that is
statistically representative of different types of nodes in the co-author
network, distinguished by their role for the connectivity of the network.
Work in the Open Archives Initiative - Object Reuse and Exchange (OAI-ORE)
focuses on an important aspect of infrastructure for eScience: the
specification of the data model and a suite of implementation standards to
identify and describe compound objects. These are objects that aggregate
multiple sources of content including text, images, data, visualization tools,
and the like. These aggregations are an essential product of eScience, and will
become increasingly common in the age of data-driven scholarship. The OAI-ORE