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Regular version of the site

Annual Workshop on Big Data Application organised by SIG BDA

The Special Interest Group (SIG) on Big Data Application, recently acknowledged as "the outstanding SIG" by the AIS, is pleased to announce that ICIS 2019 in Munich will host 4th International Workshop devoted to Big Data research in academia and industry.


  • Big Data and Industry 4.0 Production Networks
  • Big Data and Industry 4.0 
  • Industry 4.0 / Smart Manufacturing
  • Big Data Analytics and Enterprise architecture
  • AI and Predictive Analytics 
  • Smart processes
  • New business models
  • Big data ethics


  • To discuss industrial and academia experience of Big Data application.
  • To provide networking for future collaboration on the European projects linking industrial demand and academia capabilities.


Prof. Svetlana Maltseva, President of the SIG BDA, National Research University Higher School of Economics.
Dr. Dijo Alexander, Head of Technology at SAP Litmos, "Organizing Around Big Data: Analytic Capabilities for Improved Performance". (CONFIRMATION PENDING)
FH-Prof. Dr. Julian M. Müller, University of Salzburg,"How SMEs can participate in the potentials of Big Data within Industry 4.0"; "Archetypes for data-driven business models in Industry 4.0".   
Dr. Mohammed Bahja, University of Birmingham. "Optimizing Data Centre Operations to Minimize Energy Consumption: A Simulation-based Analytical Approach".
Prof. Peter Golubtsov, University of Montana. "How to Encourage Sharing Sensitive Data for Large-Scale Research through Blockchain and Smart Contract".
Prof. Mikhail Komarov, National Research University Higher School of Economics, "Approach to check distributed ledger technology applicability in business".


Elizaveta Prokofyeva and Prof. Svetlana V. Maltseva, National Research University Higher School of Economics, "Data-Driven Approaches for Efficient Patient Flow Segmentation in Polyclinics".
Roman Bogdanov, Ostbayerischen Technischen Hochschule Regensburg, "Industry 4.0 from an empirical perspective: a literature overview paper".
Dr. Andrey Shcherbovich, National Research University Higher School of Economics, "Big Data issue and the personal data protection in the Russian Federation".
Kristina Dudkovskaya and Dr. Dr. Victor Taratukhin, National Research University Higher School of Economics, University of Muenster, "Advanced methods of smart predictive maintenance systems adaptation"


International Congress Center München (ICM)Messe München GmbH, Messegelände, 81823 München, Germany Room 11ab


Saturday 14th December, 2019, 17:00 – 19:00 


Please register online through the official conference website.


ICIS 2019 special conference rates are available at several hotels. CLICK HERE to access the list of hotels, special codes, hotel reservation links (coming soon) and more information on hotel accommodations.

We strongly suggest you book your hotel rooms well in advance as the hotels have early release dates at these special rates. 

The organisers may support remote participation.


If you consider speaking at the event, you are kindly requested to send an abstract or work-in-progress paper describing the key ideas till 8 December 23:59 CET.

All submissions must be uploaded to EasyChair. Please find submission requirementes in the section SUBMISSION FORMAT. For any other question please contact Nikolai Kazantsev via e-mail: nikolai.kazantsev@postgrad.manchester.ac.uk.  


All abstracts presented during the workshop will be included into the AIS Library.

All authors will be invited to submit an extended version to the Journal «Business Informatics» (ISSN 1998-0663). The Journal is highly visible for Russian-speaking countries professionals and since 2010 it is included into the list of peer reviewed scientific editions established by the Supreme Certification Commission of the Ministry of Education and Science of the Russian Federation. The journal is published quarterly and distributed both in printed and electronic forms.


  • Text files should be submitted in electronic form, as a MS Word document (version 2003 or higher).
  • The recommended structure: purpose (mandatory), design / methodology / approach (mandatory), findings (mandatory), research limitations / implications (if applicable), practical implications (if applicable), originality / value (mandatory).
  • It is appropriate to describe the research methods/methodology if they are original or of interest for this particular research. For papers concerned with experimental work the data sources and data procession technique should be described.
  • The results should be described as precisely and informatively as possible. Include your key theoretical and experimental results, factual information, revealed interconnections and patterns. Give special priority in the abstract to new results and long-term impact data, important discoveries and verified findings that contradict previous theories as well as data that you think have practical value.
  • Font, spacing, margins: The text should be in Times New Roman 12 pt, 1.5 spaced, fit to the width, margins: left – 25 mm, all other – 15 mm.
  • The number of keywords are from 6 to 10 (separated by semicolons).
  • References should be presented in Harvard style and carefully checked for completeness, accuracy and consistency. 


For any questions please use this e-mail: nikolai.kazantsev@postgrad.manchester.ac.uk