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Authors: C. Beckstein 1 ; S. Böcker 1 ; M. Bogdan 2 ; H. Bruehlheide 3 ; H. M. Bücker 1 ; J. Denzler 1 ; P. Dittrich 1 ; I. Grosse 3 ; A. Hinneburg 4 ; B. König-Ries 5 ; F. Löffler 1 ; M. Marz 1 ; M. Müller-Hannemann 4 ; M. Winter 6 and W. Zimmermann 4

Affiliations: 1 Friedrich Schiller University Jena, Germany ; 2 Leipzig University, Germany ; 3 German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and Martin Luther University Halle Wittenberg, Germany ; 4 Martin Luther University Halle Wittenberg, Germany ; 5 Friedrich Schiller University Jena and German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Germany ; 6 German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Germany

ISBN: 978-989-758-035-2

Keyword(s): Data Analysis, Biodiversity Informatics, Research Strategy.

Related Ontology Subjects/Areas/Topics: Architectural Concepts ; Big Data ; Data Engineering ; Data Management and Quality ; Organizational Concepts and Best Practices

Abstract: 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.

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Paper citation in several formats:
Beckstein, C.; Böcker, S.; Bogdan, M.; Bruehlheide, H.; M. Bücker, H.; Denzler, J.; Dittrich, P.; Grosse, I.; Hinneburg, A.; König-Ries, B.; Löffler, F.; Marz, M.; Müller-Hannemann, M.; Winter, M. and Zimmermann, W. (2014). Explorative Analysis of Heterogeneous, Unstructured, and Uncertain Data - A Computer Science Perspective on Biodiversity Research.In Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA, ISBN 978-989-758-035-2, pages 251-257. DOI: 10.5220/0005098402510257

@conference{data14,
author={C. Beckstein. and S. Böcker. and M. Bogdan. and H. Bruehlheide. and H. M. Bücker. and J. Denzler. and P. Dittrich. and I. Grosse. and A. Hinneburg. and B. König{-}Ries. and F. Löffler. and M. Marz. and M. Müller{-}Hannemann. and M. Winter. and W. Zimmermann.},
title={Explorative Analysis of Heterogeneous, Unstructured, and Uncertain Data - A Computer Science Perspective on Biodiversity Research},
booktitle={Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA,},
year={2014},
pages={251-257},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005098402510257},
isbn={978-989-758-035-2},
}

TY - CONF

JO - Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA,
TI - Explorative Analysis of Heterogeneous, Unstructured, and Uncertain Data - A Computer Science Perspective on Biodiversity Research
SN - 978-989-758-035-2
AU - Beckstein, C.
AU - Böcker, S.
AU - Bogdan, M.
AU - Bruehlheide, H.
AU - M. Bücker, H.
AU - Denzler, J.
AU - Dittrich, P.
AU - Grosse, I.
AU - Hinneburg, A.
AU - König-Ries, B.
AU - Löffler, F.
AU - Marz, M.
AU - Müller-Hannemann, M.
AU - Winter, M.
AU - Zimmermann, W.
PY - 2014
SP - 251
EP - 257
DO - 10.5220/0005098402510257

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