ScaDS Dresden/Leipzig – A competence center for collaborative big data research
-
René Jäkel
René Jäkel is Management Director of the national Big Data Competence Center ScaDS Dresden/Leipzig. He studied physics and finished his PhD in hadron physics at the TU Dresden. His research interests cover analytics pipelines for big data applications on High Performance Computing systems and the performance characteristics of analytics applications, especially in presence of data-intensive settings. He heads the Service Center of the Competence Center as a central contact point for research requests and collaborations from industry and science and is active in numerous activities in education.
,
Eric Peukert
Eric Peukert coordinates service center activities at the University of Leipzig. He studied Computer Science and Media at the TU Dresden and worked at SAP Research in the field of data integration and schema mapping within various BMBF and EU research projects. After completing his doctorate at the University of Leipzig and two more years with SAP, he now coordinates the activities of the center in Leipzig with a special focus on industry contacts and cooperations. His research includes big data technologies, data integration and learning-based duplicate detection methods.
Wolfgang E. Nagel holds the chair for computer architecture at TU Dresden and is director of the Center for Information Services and HPC (ZIH). His research covers programming concepts and software tools to support the development of scalable and data intensive applications, analysis of computer architectures, and development of efficient parallel algorithms and methods. Prof. Nagel is chairman of the Gauß-Allianz e.V. and member of the international Big Data and Extreme-scale Computing (BDEC) project. He is leading the Big Data competence center ScaDS – Competence Center for Scalable Data Services and Solutions Dresden/Leipzig.
Erhard Rahm is full professor for databases at the computer science institute of the University of Leipzig, Germany. His current research focuses on big data and data integration. His research on data integration and schema matching has been awarded several times, in particular with the renowned 10-year best-paper award of the conference series VLDB (Very Large Databases) and the Influential Paper Award of the conference series ICDE (Int. Conf. on Data Engineering). Prof. Rahm is deputy scientific coordinator of the new German center of excellence on Big Data ScaDS Dresden/Leipzig.
Abstract
The efficient and intelligent handling of large, often distributed and heterogeneous data sets increasingly determines the scientific and economic competitiveness in most application areas. Mobile applications, social networks, multimedia collections, sensor networks, data intense scientific experiments, and complex simulations nowadays generate a huge data deluge. Nonetheless, processing and analyzing these data sets with innovative methods open up new opportunities for its exploitation and new insights. Nevertheless, the resulting resource requirements exceed usually the possibilities of state-of-the-art methods for the acquisition, integration, analysis and visualization of data and are summarized under the term big data. ScaDS Dresden/Leipzig, as one Germany-wide competence center for collaborative big data research, bundles efforts to realize data-intensive applications for a wide range of applications in science and industry. In this article, we present the basic concept of the competence center and give insights in some of its research topics.
Funding source: Bundesministerium für Bildung und Forschung
Award Identifier / Grant number: 01IS14014A-D
Funding statement: This work was supported by the German Federal Ministry of Education and Research (BMBF, 01IS14014A-D) by funding the competence center for Big Data “ScaDS Dresden/Leipzig”.
About the authors
René Jäkel is Management Director of the national Big Data Competence Center ScaDS Dresden/Leipzig. He studied physics and finished his PhD in hadron physics at the TU Dresden. His research interests cover analytics pipelines for big data applications on High Performance Computing systems and the performance characteristics of analytics applications, especially in presence of data-intensive settings. He heads the Service Center of the Competence Center as a central contact point for research requests and collaborations from industry and science and is active in numerous activities in education.
Eric Peukert coordinates service center activities at the University of Leipzig. He studied Computer Science and Media at the TU Dresden and worked at SAP Research in the field of data integration and schema mapping within various BMBF and EU research projects. After completing his doctorate at the University of Leipzig and two more years with SAP, he now coordinates the activities of the center in Leipzig with a special focus on industry contacts and cooperations. His research includes big data technologies, data integration and learning-based duplicate detection methods.
Wolfgang E. Nagel holds the chair for computer architecture at TU Dresden and is director of the Center for Information Services and HPC (ZIH). His research covers programming concepts and software tools to support the development of scalable and data intensive applications, analysis of computer architectures, and development of efficient parallel algorithms and methods. Prof. Nagel is chairman of the Gauß-Allianz e.V. and member of the international Big Data and Extreme-scale Computing (BDEC) project. He is leading the Big Data competence center ScaDS – Competence Center for Scalable Data Services and Solutions Dresden/Leipzig.
Erhard Rahm is full professor for databases at the computer science institute of the University of Leipzig, Germany. His current research focuses on big data and data integration. His research on data integration and schema matching has been awarded several times, in particular with the renowned 10-year best-paper award of the conference series VLDB (Very Large Databases) and the Influential Paper Award of the conference series ICDE (Int. Conf. on Data Engineering). Prof. Rahm is deputy scientific coordinator of the new German center of excellence on Big Data ScaDS Dresden/Leipzig.
Acknowledgment
We thank the Center for Information Services and High Performance Computing (ZIH) at TU Dresden for generous allocations of computer time. Furthermore the authors would like to express their gratitude to Hendrik Herold, Florian Jug, Jochen Tiepmar, Joachim Staib, Peter Winkler, Richard Grunzke and Bernd Schuller for providing insights into their research fields.
References
1. D. Gershon, Dealing with the data deluge. Nature 416 (2002), no. 6883, p. 889–891.10.1038/416889aSuche in Google Scholar
2. G. Bell, T. Hey, and A. Szalay, Beyond the data deluge, Science 323 (2009). no. 5919, p. 1297–1298.10.1126/science.1170411Suche in Google Scholar PubMed
3. M. Asch et al.Big data and extreme-scale computing: Pathways to Convergence-Toward a shaping strategy for a future software and data ecosystem for scientific inquiry. The International Journal of High Performance Computing Applications, vol. 32, (2018), no. 4, p. 435–479.10.1177/1094342018778123Suche in Google Scholar
4. G. Fox, J. Qiu, S. Jha, S. Ekanayake, and S. Kamburugamuve, Big Data, Simulations and HPC Convergence. In: 7th Workshop on Big Data Benchmarking, 2015.10.1007/978-3-319-49748-8_1Suche in Google Scholar
5. R. Jäkel, R. Müller-Pfefferkorn, M. Kluge, R. Grunzke, and W. E. Nagel, Architectural implications for exascale based on big data workflow requirements. In: Big Data and High Performance Computing, vol. 26, Advances in Parallel Computing, IOS Press, 2015, p. 101–113.Suche in Google Scholar
6. W. E. Nagel, R. Jäkel, and R. Müller-Pfefferkorn. Execution Environments for Big Data: Challenges for User Centric Scenarios, BDEC white paper, Barcelona 2015.Suche in Google Scholar
7. Press release (German, July 2018): Fusion von HPC und Data Analytics, https://tu-dresden.de/zih/die-einrichtung/news/fusion-von-hpc-und-data-analytics-hpc-da.Suche in Google Scholar
8. D. Schemala, D. Schlesinger, P. Winkler, H. Herold, and G. Meinel. Semantic segmentation of settlement patterns in gray-scale map images using RF and CRF within an HPC environment. In: Proceedings of the GEOBIA 2016, Enschede, Holland.10.3990/2.420Suche in Google Scholar
9. H. Herold, R. Hecht, and G. Meinel. Old maps for land use change monitoring – analysing historical maps for long-term land use change monitoring. In: Proceedings of the International Workshop Exploring Old Maps (EOM 2016), University of Luxembourg, 2016, p. 11–12.Suche in Google Scholar
10. J. Tiepmar, T. Eckart, D. Goldhahn, C. Kuras. Integrating Canonical Text Services into CLARIN’s Search Infrastructure, Linguistics and Literature Studies, vol. 5, (2017), p. 99–104.10.13189/lls.2017.050205Suche in Google Scholar
11. J. Staib, S. Grottel, and S. Gumhold. Visualization of Particle-based Data with Transparency and Ambient Occlusion, Computer Graphics Forum, vol. 34, p. 151–160.10.1111/cgf.12627Suche in Google Scholar
12. J. Staib, S. Grottel, and S. Gumhold. Enhancing Scatterplots with Multi-Dimensional Focal Blur, Computer Graphics Forum, vol. 35, p. 11–20.10.1111/cgf.12877Suche in Google Scholar
13. M. Junghanns, A. Petermann, K. Gomez, E. Rahm. Distributed Grouping of Property Graphs with GRADOOP. In: Proc. Datenbanksysteme für Business, Technologie und Web (BTW) 2017, 3 2017.Suche in Google Scholar
14. A. Petermann, M. Junghanns, S. Kemper, K. Gomez, N. Teichmann, and E. Rahm, Graph Mining for Complex Data Analytics. In: ICDM, 2016.10.1109/ICDMW.2016.0193Suche in Google Scholar
15. M. Junghanns, M. Kießling, N. Teichmann, K. Gomez, A. Petermann, E. Rahm, Declarative and distributed graph analytics with GRADOOP, PVLDB, vol. 11, (2018), no. 12, p. 2006–2009.10.14778/3229863.3236246Suche in Google Scholar
16. R. Grunzke, F. Jug, B. Schuller, R. Jäkel, G. Myers, and W. E. Nagel. Seamless HPC Integration of Data-intensive KNIME Workflows via UNICORE. In: Desprez F. et al., (eds), Euro-Par 2016: Parallel Processing Workshops, Euro-Par 2016. Lecture Notes in Computer Science, vol. 10104. Springer, Cham.10.1007/978-3-319-58943-5_39Suche in Google Scholar
17. M. R. Berthold, N. Cebron, F. Dill, T. R. Gabriel, T. Kötter, T. Meinl, P. Ohl, K. Thiel, and B. Wiswedel. KNIME – the Konstanz information miner: version 2.0 and beyond. SIGKDD Explor. Newsl. 11 (November 2009), no. 1, p. 26–31.10.1145/1656274.1656280Suche in Google Scholar
18. K. Benedyczak, B. Schuller, M. Petrova-ElSayed, J. Rybicki, R. Grunzke. UNICORE 7 – Middleware Services for Distributed and Federated Computing. In: International Conference on High Performance Computing & Simulation, HPCS2016, Innsbruck, Austria, IEEE 2016, p. 613–620.10.1109/HPCSim.2016.7568392Suche in Google Scholar
© 2018 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Editorial
- Application of blockchain technology
- Research Papers
- Message exchange on base of a blockchain-based layered architecture
- Mapping the sea of opportunities: Blockchain in supply chain and logistics
- OriginStamp: A blockchain-backed system for decentralized trusted timestamping
- On-chain vs. off-chain storage for supply- and blockchain integration
- Brokerless inter-domain virtual network embedding: A blockchain-based approach
- A Peer-to-peer Purchase and Rental Smart Contract-based Application (PuRSCA)
- Current Research Projects
- The Berlin Big Data Center (BBDC)
- ScaDS Dresden/Leipzig – A competence center for collaborative big data research
- Distinguished Dissertations
- Software-based microarchitectural attacks
Artikel in diesem Heft
- Frontmatter
- Editorial
- Application of blockchain technology
- Research Papers
- Message exchange on base of a blockchain-based layered architecture
- Mapping the sea of opportunities: Blockchain in supply chain and logistics
- OriginStamp: A blockchain-backed system for decentralized trusted timestamping
- On-chain vs. off-chain storage for supply- and blockchain integration
- Brokerless inter-domain virtual network embedding: A blockchain-based approach
- A Peer-to-peer Purchase and Rental Smart Contract-based Application (PuRSCA)
- Current Research Projects
- The Berlin Big Data Center (BBDC)
- ScaDS Dresden/Leipzig – A competence center for collaborative big data research
- Distinguished Dissertations
- Software-based microarchitectural attacks
