Data Integration


Organisation:
Chair for Computer Science 6 (Data Management)

FAU Contact:
Lenz, Richard Prof. Dr.-Ing.

Description:


Database systems also play a major role in application integration. The kernel of each integration project is the data integration, which requires on one hand the semantic mapping and on the other the inter-system synchronization. Data must be exchanged and kept consistent among applications. Here, the semantic integration of data types and instances requires a substantial manual effort. It is a must to search for methods and technologies that minimize this effort.


Related Project(s)


SIML: Schema Inference and Machine Learning
Prof. Dr.-Ing. Richard Lenz
(01/08/2018)
OCEAN: Open and Collaborative Query-Driven Analytics
Prof. Dr.-Ing. Richard Lenz
(01/11/2013)
DQ-Step: DQ-Step - Verbesserung der Datenqualität bei AREVA NP / Abteilung NEM-G
Dr.-Ing. Juliane Blechinger; Prof. Dr.-Ing. Richard Lenz
(15/01/2009 - 15/02/2012)



Assigned publications

Go to first page Go to previous page 1 of 2 Go to next page Go to last page

Wahl, A.M., Endler, G., Schwab, P., Herbst, S., Rith, J., & Lenz, R. (2018). Crossing an OCEAN of queries: Analyzing SQL query logs with OCEANLog. In Proceedings of the 30th International Conference on Scientific and Statistical Database Management, SSDBM 2018. Association for Computing Machinery.
Wahl, A.M., Schwab, P., & Lenz, R. (2018). Minimally-Intrusive Augmentation of Data Science Workflows. In Proceedings of the Lernen. Wissen. Daten. Analysen. (LWDA 2018). Mannheim, DE.
Wahl, A.M., Sauerhammer, C., Schwab, P., Herbst, S., & Lenz, R. (2018). Query-Driven Data Profiling with OCEANProfile. In Proceedings of the Twelfth International Workshop on Real-Time Business Intelligence and Analytics (BIRTE 2018). Rio de Janeriro, BR.
Wahl, A.M., Sauerhammer, C., Schwab, P., Herbst, S., & Lenz, R. (2018). Query-Driven Data Profiling with OCEANProfile. In ACM (Eds.), Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics. Rio de Janeiro, BR: ACM.
Wahl, A.M., & Lenz, R. (2017). Analyzing SQL Query Logs using Multi-Relational Graphs. In Proc. Conf. "Lernen, Wissen, Daten, Analysen". Rostock, Germany, DE: CEUR-WS.
Wahl, A.M., Endler, G., Schwab, P., Herbst, S., & Lenz, R. (2017). Anfrage-getriebener Wissenstransfer zur Unterstützung von Datenanalysten. In Proceedings of the Datenbanksysteme für Business, Technologie und Web (BTW 2017), 17. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS). Stuttgart, DE: Springer.
Wahl, A.M., Endler, G., Schwab, P., Herbst, S., & Lenz, R. (2017). Query-Driven Knowledge-Sharing for Data Integration and Collaborative Data Science. In New Trends in Databases and Information Systems. Nicosia, CY.
Wahl, A.M., Endler, G., Schwab, P., Herbst, S., & Lenz, R. (2017). We Can Query More than We Can Tell: Facilitating Collaboration Through Query-Driven Knowledge-Sharing. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. Portland, Oregon, US: ACM.
Schwab, P., Wahl, A.M., Lenz, R., & Meyer-Wegener, K. (2016). Query-driven Data Integration (Short Paper). In Proc. Conf. "Lernen, Wissen, Daten, Analysen" (pp. 206-211). Potsdam, Germany, DE: CEUR-WS.
Kraus, S., Enders, M., Prokosch, H.-U., Castellanos, I., Lenz, R., & Sedlmayr, M. (2015). Accessing complex patient data from Arden Syntax Medical Logic Modules. Artificial Intelligence in Medicine. https://dx.doi.org/10.1016/j.artmed.2015.09.003

Last updated on 2019-14-08 at 17:02