Regensburg 2019 – scientific programme
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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 4: Computational Social Science and Data Science II
SOE 4.2: Talk
Monday, April 1, 2019, 12:15–12:30, H17
There is more in your Data! - Analysis of Complex, Interconnected Datasets using Semantic Data Modeling — Timm Fitschen1, 2, •Alexander Schlemmer1, 3, Henrik tom Wörden1, 2, Daniel Hornung1, Ulrich Parlitz1, 2, 3, and Stefan Luther1, 2, 3, 4, 5 — 1Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany — 2Institute for Nonlinear Dynamics, Georg-August-Universität, Göttingen, Germany — 3German Center for Cardiovascular Research (DZHK), partner site Göttingen, Germany — 4Institute of Pharmacology and Toxicology, University Medical Center Göttingen, Göttingen, Germany — 5Department of Physics and Department of Bioengineering, Northeastern University, Boston, USA
An omnipresent challenge in the analysis of complex, heterogeneous data sets is the storage, systematic retrieval and processing of interconnected data. This especially holds for interdisciplinary fields where non-standard and rapidly evolving analysis algorithms are employed. Using a semantic data model implemented in the open source software CaosDB (https://arxiv.org/abs/1801.07653), we demonstrate in case examples from cardiac research how data from experiments and simulations can be efficiently managed and processed from data acquisition to the final publication. During this data life cycle all relevant information including metadata, analysis results, documentation and software information will be stored and linked together with the raw data. This procedure guarantees that data, results and publications are documented, findable and reproducible.