  Emerging methods and tools are changing the ways participants in global
creative networks become aware of each other and proceed to interact. Some
web-based resources intended to spark new collaborations in creative networks
have been plagued by dependence on fragmented or out-of-date information,
having shallow recall (e.g. limited to a list of manually curated keywords),
offering poor interconnectivity with other systems, and/or obtaining low
end-user adoption. Increased availability of information about creative network
participants' activities and outputs (e.g. completed sponsored research
projects and published results, aggregated into global databases), coupled with
advancement in information processing techniques like Natural Language
Processing, enables new web-based technologies for discovering subject matter
experts, facilities, and networks of current and potential collaborators.
Large-scale data resources and NLP allow modern versions of these tools to
avoid the problems of having sparse data and also provide for deep recall
across many disciplinary vocabularies. These are "passive" technologies, from
the perspective of the network participant, because the agent must undertake an
action to use the information resources. Emerging "active" methods and tools
utilize the same types of information and technologies, but actively intervene
in the formation of the creative network by suggesting connections and
arranging virtual or physical interactions. Active approaches can achieve very
high end-user adoption rates. Both active and passive methods strive to use
data-driven approaches to form better-than-chance awareness among networks of
potential collaborators. Recent case studies suggest the existence of
repeatable strategies for facilitating data-driven matching and
better-than-chance interactions designed to spark new global creative networks.
