Inhalt des Dokuments
DIMA Researchers@EDBT 2017
At the EDBT/ICDT 2017 Joint Conference in Venice, Italy, DIMA members presented the demonstration, I2: Interactive Real-Time Visualization for Streaming Data by Jonas Traub, Nikolaas Steenbergen, Philipp M. Grulich, Tilmann Rabl, and Volker Markl.
The authors introduced an innovative, interactive data visualization environment to aid the development of scalable real-time data analysis programs by providing insight into data streams. This paper earned the
Best Demonstration Award
… „The demo presents an interactive development environment for real-time visualization of stream analytics that coordinates running cluster applications and corresponding visualization. By coordinating the visualization properties, such as filter predicates, window properties or aggregates, and the analysis program running on a cluster the data to be transferred between cluster and visualization can be minimized. The committee has selected this demo for the award because of its innovative idea to the problem of visualizing data streams and its interesting combination of demonstrating a data management system with an attractive and interactive user interface.“ … [EDBT 2017 Best Demonstration Award (2017, March 29). Retrieved from htttp://edbticdt2017.unive.it/?awards]
Collocated with the EDBT/ICDE Conference 2017 the 1st International Workshop on Big Data Management in European Projects, EuroPro took place.
“… The main objective of this workshop is to share experiences and best practices, discuss challenges and effective solutions adopted, and investigate opportunities for collaboration among European projects. …” [EDBT/ICDT 2017 Joint Conference, Workshops (2017, March 31). Retrieved from edbticdt2017.unive.it]
At this workshop researchers from the Database & Information Management group, TU Berlin and the Intelligent Analytics for Massive Data - Smart Data research group, DFKI Berlin presented two more papers:
STREAMLINE -Streamlined Analysis of Data at Rest and Data in Motion, Philipp M. Grulich, Tilmann Rabl, Volker Markl, Csaba Sidló, and Andras Benczur.
PROTEUS: Scalable Online Machine Learning for Predictive Analytics and Real-Time Interactive Visualization, Bonaventura Del Monte, Jeyhun Karimov, Alireza Rezaei Mahdiraji, Tilmann Rabl, and Volker Markl.
Zusatzinformationen / Extras
Paper and Poster Download
- I2: Interactive Real-Time Visualization for Streaming Data (PDF, 665,5 KB)
- I2 Poster (PDF, 1,6 MB)
- PROTEUS: Scalable Online Machine Learning for Predictive Analytics and Real-Time Interactive Visualization (PDF, 89,3 KB)
- STREAMLINE - Streamlined Analysis of Data at Rest and Data in Motion (PDF, 117,0 KB)