Data Science - Analytics and Applications

Advances in technology and changes in the business and social environment have led to an increasing flood of data, fueling both the need and the desire to generate value from these assets. The emerging field of Data Science is poised to deliver theoretical and practical solutions to the pressing issues of data-driven applications. The 2nd International Data Science Conference (iDSC2019 / http://www.idsc.at) organized by Salzburg University of Applied Sciences brings together researchers, scientists, and business experts to discuss new ways of embracing agile approaches within the various domains of data science, e.g. machine learning and AI, data mining, visualization and communication, as well as case studies and best practices from leading research institutions and businesses.The proceedings include all full papers presented in the scientific track and the short papers from the student track. Editors Peter Haber is a Professor of Information and Communication Technology, in particular for analog and digital signal processing, and responsible coordinator for system theory and electrical engineering at Salzburg University of Applied Sciences. He is a researcher and project manager, leading and coordinating national and international projects in the field of IT and IT management, while also integrating data science solutions at businesses. Since 2009 he has been a member of the international advisory board for the IATED conferences. Thomas Lampoltshammer is an Assistant Professor for ICT and Deputy Head of the Centre for E-Governance at the Department of E-Governance and Administration, Danube University Krems, Austria. His current research focus is on the domain of data governance, the effects of ICT application in a connected society, and the effects on a data-driven society. He has a substantial background in the design and implementation of expert and decision-making systems, data analytics, and semantic-based reasoning. Manfred Mayr is the Academic Program Director for Business Informatics and Digital Transformation as well department head for IT Management at Salzburg University of Applied Sciences. He is a lecturer at international conferences and the author of various publications in the field of IT management and business informatics. In addition, he has coordinated several national and international research projects. The editors are the conference chairs of the International Data Science Conference.

Peter Haber is a Professor of Information and Communication Technology, in particular for analog and digital signal processing, and responsible coordinator for system theory and electrical engineering at Salzburg University of Applied Sciences. He is a researcher and project manager, leading and coordinating national and international projects in the field of IT and IT management, while also integrating data science solutions at businesses. Since 2009 he has been a member of the international advisory board for the IATED conferences. Thomas Lampoltshammer is an Assistant Professor for ICT and Deputy Head of the Centre for E-Governance at the Department of E-Governance and Administration, Danube University Krems, Austria. His current research focus is on the domain of data governance, the effects of ICT application in a connected society, and the effects on a data-driven society. He has a substantial background in the design and implementation of expert anddecision-making systems, data analytics, and semantic-based reasoning. Manfred Mayr is the Academic Program Director for Business Informatics and Digital Transformation as well department head for IT Management at Salzburg University of Applied Sciences. He is a lecturer at international conferences and the author of various publications in the field of IT management and business informatics. In addition, he has coordinated several national and international research projects. The editors are the conference chairs of the International Data Science Conference.

German Abstracts.- Full Papers - Double Blind Reviewed.- Data Analytics | Complexity.- Data Analytics | NLP and Semantics.- Data Analytics | Modelling.- Data Analytics | Comprehensibility.- Short Papers