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Details

Autor(en) / Beteiligte
Titel
Toward a knowledge infrastructure for traits-based ecological risk assessment
Ist Teil von
  • Integrated environmental assessment and management, 2011-04, Vol.7 (2), p.209-215
Ort / Verlag
Hoboken, USA: John Wiley & Sons, Inc
Erscheinungsjahr
2011
Link zum Volltext
Quelle
Wiley-Blackwell Full Collection
Beschreibungen/Notizen
  • The trait approach has already indicated significant potential as a tool in understanding natural variation among species in sensitivity to contaminants in the process of ecological risk assessment. However, to realize its full potential, a defined nomenclature for traits is urgently required, and significant effort is required to populate databases of species–trait relationships. Recently, there have been significant advances in the area of information management and discovery in the area of the semantic web. Combined with continuing progress in biological trait knowledge, these suggest that the time is right for a reevaluation of how trait information from divergent research traditions is collated and made available for end users in the field of environmental management. Although there has already been a great deal of work on traits, the information is scattered throughout databases, literature, and undiscovered sources. Further progress will require better leverage of this existing data and research to fill in the gaps. We review and discuss a number of technical and social challenges to bringing together existing information and moving toward a new, collaborative approach. Finally, we outline a path toward enhanced knowledge discovery within the traits domain space, showing that, by linking knowledge management infrastructure, semantic metadata (trait ontologies), and Web 2.0 and 3.0 technologies, we can begin to construct a dedicated platform for TERA science. Integr Environ Assess Manag 2011;7:209–215. © 2010 SETAC
Sprache
Englisch
Identifikatoren
ISSN: 1551-3777
eISSN: 1551-3793
DOI: 10.1002/ieam.129
Titel-ID: cdi_proquest_miscellaneous_859052521

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