Towards an open, zoomable atlas for invasion science and beyond

被引:10
作者
Jeschke, Jonathan M. [1 ,2 ,3 ]
Heger, Tina [3 ,4 ,5 ]
Kraker, Peter [6 ]
Schramm, Maxi [6 ]
Kittel, Christopher [6 ]
Mietchen, Daniel [7 ]
机构
[1] Leibniz Inst Freshwater Ecol & Inland Fisheries I, Berlin, Germany
[2] Free Univ Berlin, Inst Biol, Berlin, Germany
[3] Berlin Brandenburg Inst Adv Biodivers Res BBIB, Berlin, Germany
[4] Univ Potsdam, Biodivers Res Systemat Bot, Potsdam, Germany
[5] Tech Univ Munich, Restorat Ecol, Freising Weihenstephan, Germany
[6] Open Knowledge Maps Verein Forderung Sichtbarkeit, Vienna, Austria
[7] Univ Virginia, Sch Data Sci, Charlottesville, VA USA
关键词
hierarchy-of-hypotheses (HoH) approach; hypothesis networks; interactive knowledge discovery; invasive alien species; invasion biology;   Open Knowledge Maps; open science; Wikidata;
D O I
10.3897/neobiota.68.66685
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Biological invasions are on the rise, and their global impacts on ecosystems, economies and human health are a major challenge. Invasion science is critical to mitigate invader impacts, yet due to the strong increase of data and information in this area, it has become difficult to acquire and maintain an overview of the field. As a result, existing evidence is often not found, knowledge is too rarely transferred to practice, and research is sometimes conducted in pursuit of dead ends. We propose to address these challenges by developing an interactive atlas of invasion science that can be extended to other disciplines in the future. This online portal, which we aim to create in the course of the project described here, will be an evolving knowledge resource and open for anyone to use, including researchers, citizen scientists, practitioners and policy makers. Users will be able to zoom into the major research questions and hypotheses of invasion science, which are connected to the relevant studies published in the field and, if available, the underly-ing raw data. The portal will apply cutting-edge visualization techniques, artificial intelligence and novel methods for knowledge synthesis.
引用
收藏
页码:5 / 18
页数:14
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