Explorative analysis of heterogeneous, unstructured, and uncertain data: A computer science perspective on biodiversity research.



  • C. Beckstein
  • S. Böcker
  • M. Bogdan
  • H. Bruelheide
  • H. M. Bücker
  • J. Denzler
  • P. Dittrich
  • I. Grosse
  • A. Hinneburg
  • B. König-Ries
  • F. Löffler
  • M. Marz
  • M. Müller-Hannemann
  • M. Winter
  • W. Zimmermann


We outline a blueprint for the development of new computer science approaches for the management and analysis of big data problems for biodiversity science. Such problems are characterized by a combination of different data sources each of which owns at least one of the typical characteristics of big data (volume, variety, velocity, or veracity). For these problems, we envision a solution that covers different aspects of integrating data sources and algorithms for their analysis on one of the following three layers: At the data layer, there are various data archives of heterogeneous, unstructured, and uncertain data. At the functional layer, the data are analyzed for each archive individually. At the meta-layer, multiple functional archives are combined for complex analysis.