The DataPorts project has produced so far the following publications :
2022
Design of a Next-Generation Interoperable Cognitive Port Solution
Belsa Pellicer, A. et al. (2022). “Design of a Next-Generation Interoperable Cognitive Port Solution”. In: González-Vidal, A., Mohamed Abdelgawad, A., Sabir, E., Ziegler, S., Ladid, L. (eds) Internet of Things. GIoTS 2022. Lecture Notes in Computer Science, vol 13533. Springer, Cham.
Explaining Online Reinforcement Learning Decisions of Self-Adaptive Systems
Feit, F., Metzger, A. and Pohl, K., “Explaining Online Reinforcement Learning Decisions of Self-Adaptive Systems”, in 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS) 2022 Sep 19 (pp. 51-60). IEEE.
SCAL-E: An Auto Scaling Agent for Optimum Big Data Load Balancing in Kubernetes Environments
Karypiadis, E., Nikolakopoulos, A., Marinakis, A., Moulos, V. and Varvarigou, T., “SCAL-E: An Auto Scaling Agent for Optimum Big Data Load Balancing in Kubernetes Environments”, 2022 International Conference on Computer, Information and Telecommunication Systems (CITS), 2022, pp. 1-5.
Efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases
Marinakis, A. et al. (2022). “Efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases”. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022 IFIP WG 12.5 International Workshops. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 652. Springer, Cham.
A Novel Approach for Calculating Real-Time Composite Indicators Relying on Internet of Things and Industrial Data Spaces
Belsa, A., Vaño, R., Lacalle, I., Julián, M., Boronat, F., Palau, C.E. (2022). “A Novel Approach for Calculating Real-Time Composite Indicators Relying on Internet of Things and Industrial Data Spaces”. In: Camacho, D., Rosaci, D., Sarné, G.M.L., Versaci, M. (eds) Intelligent Distributed Computing XIV. IDC 2021. Studies in Computational Intelligence, vol 1026. Springer, Cham.
Towards Cognitive Ports of the Future
Cáceres, S. et al. (2022). “Towards Cognitive Ports of the Future”, in Curry, E., Auer, S., Berre, A.J., Metzger, A., Perez, M.S., Zillner, S. (eds) Technologies and Applications for Big Data Value . Springer, Cham.
2021
Counterfactual Explanations for Predictive Business Process Monitoring
Huang TH., Metzger A., Pohl K. (2022) “Counterfactual Explanations for Predictive Business Process Monitoring”. In: Themistocleous M., Papadaki M. (eds) Information Systems – 18th European, Mediterranean, and Middle Eastern Conference (EMCIS 2021), Virtual Event, December 8-9, 2021, Proceedings, Lecture Notes in Business Information Processing, vol 437, Springer, 2021, 399-413.
Hoplite Antivirus for Adversarial Attacks: A Theoretical Approach
Nikolakopoulos, A.; Marinakis, A.; Moulos, V. and Varvarigou, T. (2021). “Hoplite Antivirus for Adversarial Attacks: A Theoretical Approach”. In Proceedings of the 17th International Conference on Web Information Systems and Technologies – DMMLACS, ISBN 978-989-758-536-4; ISSN 2184-3252, pages 585-592.
AI: Opportunities and Challenges - The Optimal Exploitation of (Telecom) Corporate Data
Palaiogeorgou P., Gizelis C.A., Misargopoulos A., Nikolopoulos-Gkamatsis F., Kefalogiannis M., Christonasis A.M. (2021) “AI: Opportunities and Challenges – The Optimal Exploitation of (Telecom) Corporate Data”, in Dennehy D., Griva A., Pouloudi N., Dwivedi Y.K., Pappas I., Mäntymäki M. (eds) Responsible AI and Analytics for an Ethical and Inclusive Digitized Society. I3E 2021. Lecture Notes in Computer Science, vol 12896. Springer, Cham.
Ensemble Deep Learning for Proactive Terminal Process Management at the Port of Duisburg “duisport”
Metzger A., Franke J., Jansen T. (2021) “Ensemble Deep Learning for Proactive Terminal Process Management at the Port of Duisburg duisport”, in vom Brocke J., Mendling J., Rosemann M. (eds) Business Process Management Cases Vol. 2. Springer, Berlin, Heidelberg.
A Reference Model for Big Data Technologies
Curry E., Metzger A., Berre A.J., Monzón A., Boggio-Marzet A. (2021) “A Reference Model for Big Data Technologies”, in Curry E., Metzger A., Zillner S., Pazzaglia JC., García Robles A. (eds) The Elements of Big Data Value. Springer, Cham.
Ontology-driven evolution of software security
Sven Peldszus, Jens Bürger, Timo Kehrer, Jan Jürjens, “Ontology-driven evolution of software security”, Data & Knowledge Engineering, Volume 134, 2021, 101907, ISSN 0169-023X.
2020
Cost Fairness for Blockchain-Based Two-Party Exchange Protocols
M. Lohr, B. Schlosser, J. Jürjens and S. Staab, “Cost Fairness for Blockchain-Based Two-Party Exchange Protocols”, 2020 IEEE International Conference on Blockchain (Blockchain), Rhodes Island, 2020, pp. 428-435.
Towards a smart port: the role of the telecom industry
Gizelis, C. A., Mavroeidakos, T., Marinakis, A., Litke, A., & Moulos, V. (2020). “Towards a Smart Port: The Role of the Telecom Industry”. Artificial Intelligence Applications and Innovations. AIAI 2020 IFIP WG 12.5 International Workshops: MHDW 2020 and 5G-PINE 2020, Neos Marmaras, Greece, June 5–7, 2020, Proceedings, 585, 128–139.
Online Reinforcement Learning for Self-adaptive Information Systems
A. Palm, A. Metzger, and K. Pohl, “Online reinforcement learning for self-adaptive information systems”, in 32nd Int’l Conference on Advanced Information Systems Engineering (CAiSE 2020), Grenoble, France, June 8-12, 2020, ser. LNCS, S. Dustdar, E. Yu, C. Salinesi, D. Rieu, and V. Pant, Eds., vol. 12127. Springer, 2020, pp. 169–184.
Triggering Proactive Business Process Adaptations via Online Reinforcement Learning
A. Metzger, T. Kley, and A. Palm, “Triggering proactive business process adaptations via online reinforcement learning”, in 18th Int’l Conference on Business Process Management (BPM 2020), Sevilla, Spain, September 13-18, 2020, ser. Lecture Notes in Computer Science, D. Fahland, C. Ghidini, J. Becker, and M. Dumas, Eds., vol. 12168. Springer, 2020.
A Scalable and Semantic Data as a Service Marketplace for Enhancing Cloud-Based Applications
Psomakelis, E.; Nikolakopoulos, A.; Marinakis, A.; Psychas, A.; Moulos, V.; Varvarigou, T.; Christou, A. “A Scalable and Semantic Data as a Service Marketplace for Enhancing Cloud-Based Applications”. Future Internet 2020, 12, 77.
Framework and Methodology for Establishing Port-City Policies Based on Real-Time Composite Indicators and IoT: A Practical Use-Case
Lacalle, I.; Belsa, A.; Vaño, R.; Palau, C.E. “Framework and Methodology for Establishing Port-City Policies Based on Real-Time Composite Indicators and IoT: A Practical Use-Case”. Sensors 2020, 20, 4131.