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Big data management refers to data that is voluminous, of heterogeneous nature and stemming from different sources, produced at tremendous rates, and as such cannot be handled by traditional database technology. As a consequence, the complete lifecycle of data management needs to be revisited and redesigned, in order to capture the unique requirements posed by big data, which is produced not only by industrial companies, research centers and scientific applications, but also lately due to high rate of user-generated data in Web 2.0. Fundamental research challenges that need to be effectively addressed in the context of big data include: storage, extraction and integration, indexing, query processing and optimization, analysis, and mining.
Our group is actively involved in the field of big data management in terms of optimizing parallel data processing of large-scale datasets, developing novel algorithms for advanced data analysis, and designing scalable platforms that will serve as the next-generation data management systems. People from our group have acted as principal investigators in research projects, funded both from the EU and national funds, such as CloudIX and Roadrunner, which aim to improve the efficiency and scalability of parallel data management platforms, such as MapReduce/Hadoop.
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[av_iconlist_item title=’Selected Publications’ link=” linktarget=” icon=’ue84d’ font=’entypo-fontello’]
| Michelioudakis, E., Skarlatidis, A., Paliouras, G., Artikis, A. OSLa: Online Structure Learning using Background Knowledge Axiomatisation. European Conference of Machine Learning and Principles and Practice of Knowledge Discovery, 2016. |
| Skarlatidis A., Paliouras G., Artikis A., and Vouros G. Probabilistic Event Calculus for Event Recognition, ACM Transactions on Computational Logic, 2015. |
| Alexander Artikis, Marek J. Sergot, Georgios Paliouras: An Event Calculus for Event Recognition. IEEE Trans. Knowl. Data Eng. 27(4): 895-908 (2015) |
| Anastasios Skarlatidis, Alexander Artikis, Jason Filipou, Georgios Paliouras: A probabilistic logic programming event calculus. TPLP 15(2): 213-245 (2015) |
| D. Pertesis, C. Doulkeridis. Efficient Skyline Query Processing in SpatialHadoop. In Information Systems (2014), DOI: 10.1016/j.is.2014.10.003. |
| C. Doulkeridis, K. Nørvåg. A Survey of Large-Scale Analytical Query Processing in MapReduce. In VLDB Journal, Vol. 23, Issue 3, pages 355-380, June 2014. |
| Alexander Artikis, Matthias Weidlich, François Schnitzler, Ioannis Boutsis, Thomas Liebig, Nico Piatkowski, Christian Bockermann, Katharina Morik, Vana Kalogeraki, Jakub Marecek, Avigdor Gal, Shie Mannor, Dimitrios Gunopulos, Dermot Kinane: Heterogeneous Stream Processing and Crowdsourcing for Urban Traffic Management. EDBT 2014: 712-723 |
| Alexander Artikis, Matthias Weidlich, Avigdor Gal, Vana Kalogeraki, Dimitrios Gunopulos: Self-adaptive event recognition for intelligent transport management. BigData Conference 2013: 319-325 |
| C. Doulkeridis, K. Nørvåg. On Saying “Enough Already!” in MapReduce. In Proceedings of 1st International Workshop on Cloud Intelligence (Cloud-I 2012, co-located with VLDB’2012), Istanbul, Turkey, August 31, 2012. |
| C. Doulkeridis, A. Vlachou, K. Nørvåg, Y. Kotidis and N. Polyzotis. Processing of Rank Joins in Highly Distributed Systems. In Proceedings of 28th IEEE International Conference on Data Engineering (ICDE’12), Washington, DC, USA, April 1-5, 2012. |
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