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Gradoop auf FOSDEM in Brüssel

Martin Junghanns von der Uni Leipzig stellt am 30.01.2015 das Gradoop-Framework auf der Entwicklerkonferenz FOSDEM in Brüssel vor. Weitere Informationen finden Sie hier 

 

 

1. Big Data All-Hands-Meeting in Dresden

Zeitraum: 02.-03. Juni 2016 in Dresden

Ort: Tagungshotel Wyndham Garden, Dresden (https://www.wyndhamgardendresden.com)

Registrierung und Kontakt: Registrierung geschlossen. Für weitere Fragen wenden Sie sich bitte direkt an: Diese E-Mail-Adresse ist vor Spambots geschützt! Zur Anzeige muss JavaScript eingeschaltet sein!

Unterbringung:  Es besteht ein Zimmerkontingent im Tagungshotel Wyndham Garden Dresden  (60 Zimmer, abrufbar bis 25.05.) und im Gästehaus der TU Dresden am Weberplatz  (20 Zimmer, abrufbar bis 19.05.). Wenn Sie in den vorgeschlagenen Unterbringungsmöglichkeiten reservieren möchen, benutzen Sie dazu bitte das Stichwort „ScaDS: All-Hands-Meeting“.

Weiter Hotels in Dresden sind u.a.:

Ibis Hotel Königstein
Prager Str. 9, 01069 Dresden
Tel.: +49-351-48562000
Fax: +49-351-48566666
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Motel One Dresden am Zwinger
Postplatz 5, 01067 Dresden
Tel. : +49-351-438 38 - 0
Fax : +49-351-438 38 - 10
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ACHAT Comfort Dresden
Budapester Str. 34, 01069 Dresden
Tel. : +49-351-47380-0
Fax : +49-351-47380-999
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Das 1. All-Hands-Meeting im Themenfeld „Big Data“ findet vom  2.-3. Juni in Dresden statt. Die beiden vom BMBF geforderten Big-Data-Kompetenzzentren "ScaDS Dresden/Leipzig - Competence Center for Scalable Data Services and Solutions" und das "BBDC - Berlin Big Data Center" organisieren gemeinschaftlich diese Fachtagung, um eine Plattform zum Ideenaustausch und zur Information über aktuelle Forschungshighlights im Themengebiet Big Data zu bieten. Die Veranstaltung richtet sich an Projektbeteiligte der geförderten Kompetenzzentren, verschiedener Forschungs- und Entwicklungsprojekte sowie an Akteure  weiterer Big-Data- und Smart-Data-Initiativen. Im Fokus der Veranstaltung  stehen der fachliche Austausch zwischen Wissenschaftlern und Unternehmensvertretern und die Förderung von Synergien durch die Möglichkeiten zur Präsentation eigener Lösungen aus den Projekten und des Austausches verschiedener Ansätze. Dadurch wird die Vernetzung zwischen den Projekten und Initiativen intensiviert, um das Forschungsfeld Big Data auch zukünftig deutschlandweit zu stärken.

Vorläufiges Programm:

Day 1 - Thursday June 2nd
09:00 Registration and Welcome Coffee  
10:00 - 10:15 Welcome and opening speech  
10:15-11:45 Plenary Session (I) -
Recent Developments in the Big Data Competence Centers
 
10:15-11:00 Competence Center for Scalable Data Services and Solutions – ScaDS Dresden/Leipzig Prof. Wolfgang E. Nagel, TU Dresden (ZIH), ScaDS Dresden/Leipzig
11:00-11:45 Berlin Big Data Center – BBDC Prof. Volker Markl, TU Berlin (DIMA), BBDC
11:45-13:00 Get Together + lunch break  
13:00-15:00 Plenary Session (II) - Big and Smart Data Projects
 
13:00-13:30   Algorithm Engineering for Large Data Sets Prof. Dr. Peter Sanders, Karlsruher Institut für Technologie (KIT)
13:30-14:00 SD4M - Smart Data for Mobility Ingo Schwarzer, DB Systel
14:00-14:30 GeoMulitSens - Scalable Analysis of Big Remote Sensing Data Dr. Mike Sips, German Research Center for GeoSciences (GFZ)
14:30-15:00 BigGis - Prescriptive geographical information systems (GIS) based on big data analytics infrastructures Prof. Dr. Thomas Setzer, Forschungszentrum Informatik (KIT-FZI)
15:00-15:30 Poster session + coffee break  
15:30-16:00 Plenary Session (II) - continued
 
15:30-16:00 Direct From Academia to Market: Time of Great Opportunities for Big Data Researchers Prof. Sang Kyun Cha, Seoul National University Big Data Institute
16:00-18:00 Parallel Sessions/Workshops (I)  
Track A: Data Analytics
16:00-16:30

Graph Analytics with Gradoop

Martin Junghans, André Petermann, ScaDS Dresden/Leipzig (Gradoop)
16:30-17:00 From .csv to Spark: Tool and Data Integration in KNIME Tobias Kötter, KNIME.com GmbH
17:00-17:30 Data Deduplication for Simulation Input Data in the Auto Industry Matthias Büchse, Scale-GmbH
17:30-18:00 BigPro: Big Data Technology for Resilient Failure Management in Production Systems Suad Sejdovic, Forschungszentrum Informatik (KIT-FZI)
Track B: Visualization/Machine Learning
16:00-16:30 Towards Visual Analytics for Multi-Sensor Analysis of Remote Sensing Archives Daniel Eggert, German Research Center for GeoSciences (GFZ)
16:30-17:00 Machine Learning Alexander Bauer, TU Berlin
17:00-17:30 Trends in Computer Vision Dr. Dmitrij Schlesinger ScaDS Dresden/Leipzig)
17:30-18:00 BigGIS – Considering uncertainty and heterogeneity in geo-spatial Big Data Julian Bruns, Forschungszentrum Informatik (FZI)
18:30 Conference dinner  
Day 2 - Friday, June 3rd
09:00-10:30 Plenary Session (III)  
 09:00-10:00 Keynote

Building a Library at the nexus of High Performance Computing and Big Data

Geoffrey Charles Fox
Director of Data Science, Indiana University Bloomington
10:00-10:30 The DFG Priority Program "Scalable Data Management for Future Hardware" Prof. Kai-Uwe Sattler, Technische Universität Ilmenau
10:30-11:00 Poster session + coffee break  
11:00-12:30 Plenary Session (IV) - Big and Smart Data Projects  
11:00-11:30 iProdict – Intelligent Process Forecasting using Big Data Analytics Andreas Emrich (DFKI)
11:30-12:00 iTESA - intelligent Traveller Early Situation Awareness Uwe Gabriel, travelbasys
12:00-12:30 SAKE - Big Data Architecture for the Semantic Analysis of Complex Events Simon Bin, Universität Leipzig
12:30-13:30 Lunch break  
13:30-16:45 Parallel Sessions/Workshops (II)  
Track A: Data Handling/Business Modells
13:30-14:00 HUMIT - Interactive Data Integration in a Data Lake System for the Life Sciences Dr. Christoph Quix, Fraunhofer FIT
14:00-14:30 Gesellschaftliche Aspekte von Big Data Dr. Barbara Kolany-Raiser, ABIDA
14:30-15:00 Challenges for Data-Intensive Business Processes in the Age of Big Data Andreas Emrich, DFKI
15.00-15.30 Poster session + coffee break  
Track A (continued): Data Handling/Business Modells
15:30-16:00 FEE - Frühzeitige Erkennung und Entscheidungsunterstützung kritischer Situationen im Produktionsumfeld Dr. Martin Atzmüller, Universität Kassel
16:00-16:30 Architecture of a Multi-Domain Processing and Storage Engine Johannes Luong, TU Dresden
Track B: Big Data Processing
13:30-14:30 Introduction in Flink Dr. Tilmann Rabl, BBDC
  Flink-Use Cases  
14:30-15:00 KNIME Cluster Extension Patrick Winter, Universität Konstanz
15.00-15.30 Poster session + coffee break  
Track B (continued): Big Data Processing
15:30-16:00 Big Data Analytics @HPC Jan Frenzel, ScaDS Dresden/Leipzig
16:00-16:30 SAP HANA Vora: Handling Big Data at SAP Lars Dannecker, SAP
16:30-17:00 Final Get-Together / Outlook  
17:00  End of meeting  

 

1. Big Data All-Hands-Meeting in Dresden

02.-03. Juni 2016

Vom 02. bis 03. Juni 2016 treffen sich Forscher rund um Big Data auf einem Vernetzungsworkshop in Dresden. Dieser bietet die Möglichkeit zum Austausch der Beteiligten unterschiedlicher durch die Big-Data- und Smart-Data-Initiativen geförderten Projekte.

Weitere Informationen zum All-Hands-Meeting

On Friday, 22. January,  we hosted the seminar talk by Prof. Themis Palpanas from the Paris Descartes University (France). The slides of the talk are available via this link:

Announcement:

We are happy to invite you to a talk by Prof. Themis Palpanas from the Paris Descartes University (France) within the ScaDS-Colloquium.

Speaker: Prof. Themis Palpanas
Title: Data Series Management: The Road to Big Sequence Analytics
Date: 22. January 2016; 11:00 - 12:30
Location: TU Dresden - Andreas Pfitzmann Bau (APB 3105)

Abstract:

There is an increasingly pressing need, by several applications in diverse domains, for developing techniques able to index and mine very large collections of sequences, or data series. Examples of such applications come from social media analytics and internet service providers, as well as from a multitude of scientific domains. It is not unusual for these applications to involve numbers of data series in the order of hundreds of millions to billions, which are often not analyzed in their full detail due to their sheer size.

In this talk, we describe recent efforts in designing techniques for indexing and mining truly massive collections of data series that will enable scientists to easily analyze their data. We show that the main bottleneck in mining such massive datasets is the time taken to build the index, and we thus introduce solutions to this problem. Furthermore, we discuss novel techniques that adaptively create data series indexes, allowing users to correctly answer queries before the indexing task is finished. We also show how our methods allow mining on datasets that would otherwise be completely untenable, including the first published experiments using one billion data series.

Finally, we present our vision for the future in big sequence management research, including the promising directions in terms of distributed processing.

Short Bio:

Themis Palpanas is a professor of computer science at the Paris Descartes University (France), here he is a director of the Data Intensive and Knowledge Oriented Systems (diNo) group. He received the BS degree from the National Technical University of Athens, Greece, and the MSc and PhD degrees from the University of Toronto, Canada. He has previously held positions at the University of Trento and the IBM T.J. Watson Research Center. He has also worked for the University of California, Riverside, and visited Microsoft Research and the IBM Almaden Research Center. His research solutions have been implemented in world-leading commercial data management products and he is the author of nine US patents. He is the recipient of three Best Paper awards (including ICDE and PERCOM), and the IBM Shared University Research (SUR) Award in 2012, which represents a recognition of research excellence at worldwide level. He has been a member of the IBM Academy of Technology Study on Event Processing, and is a founding member of the Event Processing Technical Society. He has served as General Chair for VLDB 2013, the top international conference on databases.

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