Article in Proceedings INPROC-2015-33

BibliographyHirmer, Pascal; Reimann, Peter; Wieland, Matthias; Mitschang, Bernhard: Extended Techniques for Flexible Modeling and Execution of Data Mashups.
In: Markus Helfert (ed.); Andreas Holzinger (ed.); Orlando Belo (ed.); Chiara Francalanci (ed.): Proceedings of the 4th International Conference on Data Management Technologies and Applications (DATA).
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 111-122, english.
Colmar: SciTePress, July 20, 2015.
ISBN: 978-989-758-103-8.
Article in Proceedings (Conference Paper).
CorporationINSTICC
CR-SchemaE.1 (Data Structures)
E.5 (Data Files)
KeywordsData Mashups, Ad-hoc Integration, Patterns, Data Flow
Abstract

Today, a multitude of highly-connected applications and information systems hold, consume and produce huge amounts of heterogeneous data. The overall amount of data is even expected to dramatically increase in the future. In order to conduct, e.g., data analysis, visualizations or other value-adding scenarios, it is necessary to integrate specific, relevant parts of data into a common source. Due to oftentimes changing environments and dynamic requests, this integration has to support ad-hoc and flexible data processing capabilities. Furthermore, an iterative and explorative trial-and-error integration based on different data sources has to be possible. To cope with these requirements, several data mashup platforms have been developed in the past. However, existing solutions are mostly non-extensible, monolithic systems or applications with many limitations regarding the mentioned requirements. In this paper, we introduce an approach that copes with these issues (i) by the introduction of patterns to enable decoupling from implementation details, (ii) by a cloud-ready approach to enable availability and scalability, and (iii) by a high degree of flexibility and extensibility that enables the integration of heterogeneous data as well as dynamic (un-)tethering of data sources. We evaluate our approach using runtime measurements of our prototypical implementation.

CopyrightCopyright 2015 SCITEPRESS Science and Technology Publications All rights reserved
Contactpascal.hirmer@ipvs.uni-stuttgart.de
Department(s)University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems
Project(s)SitOPT
SimTech - DP4SW
Entry dateJuly 24, 2015
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