Essential elements of online information networks on invasive alien species |
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Authors: | Annie Simpson Elizabeth Sellers Andrea Grosse Yan Xie |
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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 |
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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. |
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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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