4.5 Article

A workflow for standardising and integrating alien species distribution data

期刊

NEOBIOTA
卷 -, 期 59, 页码 39-59

出版社

PENSOFT PUBLISHERS
DOI: 10.3897/neobiota.59.53578

关键词

databases; Darwin Core; GBIF; invasive alien species; R software environment; reproducibility; standardisation; taxonomy; workflow

资金

  1. sDiv, the Synthesis Centre of iDiv [DFG FZT 118 202548816]
  2. Belmont Forum-BiodivERsA project AlienScenarios through German Federal Ministry of Education and Research (BMBF) [01LC1807A]
  3. Australian Research Council [DP200101680]
  4. BiodivERsABelmont Forum Project AlienScenarios (FWF project) [I 4011-B32]
  5. South African Department of Forestry, Fisheries and the Environment (DFFtE)
  6. Australian Government Research Training Program (RTP) scholarship
  7. Spanish Ministry of Science and Innovation [CGL2016-80820-R, PCIN2016-168, RED2018-102571-T]
  8. Government of Catalonia [2017 SGR 548]
  9. Belgian Science Policies Brain program [BR/165/A1/TrIAS]
  10. Australian Research Council [DP200101680] Funding Source: Australian Research Council

向作者/读者索取更多资源

Biodiversity data are being collected at unprecedented rates. Such data often have significant value for purposes beyond the initial reason for which they were collected, particularly when they are combined and collated with other data sources. In the field of invasion ecology, however, integrating data represents a major challenge due to the notorious lack of standardisation of terminologies and categorisations, and the application of deviating concepts of biological invasions. Here, we introduce the SInAS workflow, short for Standardising and Integrating Alien Species data. The SInAS workflow standardises terminologies following Darwin Core, location names using a proposed translation table, taxon names based on the GBIF backbone taxonomy, and dates of first records based on a set of predefined rules. The output of the SInAS workflow provides various entry points that can be used both to improve coherence among the databases and to check and correct the original data. The workflow is flexible and can be easily adapted and extended to the needs of different users. We illustrate the workflow using a case-study integrating five widely used global databases of information on biological invasions. The comparison of the standardised databases revealed a surprisingly low degree of overlap, which indicates that the amount of data may currently not be fully exploited in the original databases. We highly recommend the use and development of publicly available workflows to ensure that the integration of databases is reproducible and transparent. Workflows, such as SInAS, ultimately increase trust in data, study results, and conclusions.

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