Work

Explorative Analysis of Heterogeneous, Unstructured, and Uncertain Data - A Computer Science Perspective on Biodiversity Research

Year: 2014

Type: conference-paper

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.

Source: International Conference on Data Science, Technology and Applications (DATA)

DOI: 10.5220/0005098402510257

Authors: C. Beckstein, S. Böcker, M. Bogdan, H. Bruehlheide, 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

Institutions: Friedrich Schiller University Jena, Leipzig University, German Centre for Integrative Biodiversity Research, Martin Luther University Halle-Wittenberg

Language: English

Topic: Big Data Technologies and Applications

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

SDG: Life on land

Open Access status: hybrid

OpenAlex ID: W2061124807

FWCI: 0.734

Cites:

Cited by: 3

Related to: 10