Overview
Part of the book series: Lecture Notes in Business Information Processing (LNBIP, volume 375)
Included in the following conference series:
Conference proceedings info: CONFENIS 2019.
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About this book
This book constitutes the refereed proceedings of the 13th IFIP WG 8.9 Working Conference on Research and Practical Issues of Enterprise Information Systems, CONFENIS 2019, held in Prague, Czech Republic, in December 2019.
The 11 full and 2 short papers included in this volume were carefully reviewed and selected from 43 submissions. They were organized in topical sections named: EIS and industry; technical architecture and applications for EIS; collaborative networks and project management; and security and privacy issues.
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Keywords
Table of contents (14 papers)
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Technical Architecture and Applications for EIS
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Collaborative Networks and Project Management
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Security and Privacy Issues
Other volumes
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Research and Practical Issues of Enterprise Information Systems
Editors and Affiliations
Bibliographic Information
Book Title: Research and Practical Issues of Enterprise Information Systems
Book Subtitle: 13th IFIP WG 8.9 International Conference, CONFENIS 2019, Prague, Czech Republic, December 16–17, 2019, Proceedings
Editors: Petr Doucek, Josef Basl, A Min Tjoa, Maria Raffai, Antonin Pavlicek, Katrin Detter
Series Title: Lecture Notes in Business Information Processing
DOI: https://doi.org/10.1007/978-3-030-37632-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: IFIP International Federation for Information Processing 2019
Softcover ISBN: 978-3-030-37631-4Published: 14 December 2019
eBook ISBN: 978-3-030-37632-1Published: 13 December 2019
Series ISSN: 1865-1348
Series E-ISSN: 1865-1356
Edition Number: 1
Number of Pages: X, 163
Number of Illustrations: 15 b/w illustrations, 19 illustrations in colour
Topics: Information Systems Applications (incl. Internet), Enterprise Architecture, Systems and Data Security, Business Information Systems, Computer Appl. in Administrative Data Processing