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Essential elements of online information networks on invasive alien species
Authors:Annie Simpson  Elizabeth Sellers  Andrea Grosse  Yan Xie
Institution:(1) National Biological Information Infrastructure, US Geological Survey, Mail stop 302, 12201 Sunrise Valley Drive, Reston, VA 20192, USA;(2) Institute of Zoology, Chinese Academy of Sciences, 25 Beisihuan Xilu, Beijing, 100080, China
Abstract:In order to be effective, information must be placed in the proper context and organized in a manner that is logical and (preferably) standardized. Recently, invasive alien species (IAS) scientists have begun to create online networks to share their information concerning IAS prevention and control. At a special networking session at the Beijing International Symposium on Biological Invasions, an online Eastern Asia–North American IAS Information Network (EA–NA Network) was proposed. To prepare for the development of this network, and to provide models for other regional collaborations, we compare four examples of global, regional, and national online IAS information networks: the Global Invasive Species Information Network, the Invasives Information Network of the Inter-American Biodiversity Information Network, the Chinese Species Information System, and the Invasive Species Information Node of the US National Biological Information Infrastructure. We conclude that IAS networks require a common goal, dedicated leaders, effective communication, and broad endorsement, in order to obtain sustainable, long-term funding and long-term stability. They need to start small, use the experience of other networks, partner with others, and showcase benefits. Global integration and synergy among invasive species networks will succeed with contributions from both the top-down and the bottom-up.
Keywords:GISIN  I3N  IABIN  NBII  ISIN  CSIS  EA–  NA Network  interoperability  IAS  invasive species  invasive species databases  multinational cooperation  transborder issues  information systems  information management  distributed networks  cross-search  online
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