Preface: modern data science technologies workshop Michael Emmerich1,2,3, ∗ ,†, Vasyl Lytvyn4,† and Victoria Vysotska4,5,† 1 Leiden Institute of Advanced Computer Science, LIACS Leiden University, Niels Bohrweg 1, 2333CA Leiden, The Netherlands 2 Department of IT, University of Jyväskylä, Mattilanniemi 2, 40100 Jyväskylä, Finland 3 Lead AI Scientist @ SILO.ai, Lapinlahdenkatu 1 C, 00180 Helsinki, Finland 4 Lviv Polytechnic National University, Stepan Bandera 12, 79013 Lviv, Ukraine 5 Osnabrück University, Friedrich-Janssen-Str. 1, 49076 Osnabrück, Germany Abstract This document is the preface of the 6th International Workshop on Modern Data Science Technologies (MoDaST-2024), May, 31 - June, 1, 2024, held in Lviv-Shatsk, Ukraine. The main purpose of the MoDaST Workshop is providing a forum for researchers to discuss models, methods and information technology for data science, data analysis and business analysis, and their real-life applications. Keywords data science, big data, machine learning, data analysis, information technology, system1 1. Introduction The main purpose of the Modern Data Science Technologies Workshop is providing a forum for researchers to discuss models, methods and information technology for data science, data analysis and business analysis, and their real-life applications [1-5]. In MoDaST Workshop, we encourage the submission of papers on machine learning, deep learning, decision making, and multicriteria decision analysis areas. The MoDaST Workshop is soliciting literature review, survey and research papers comments including, whilst not limited to, the following areas of interest:  Analytical methods;  Ontological engineering;  Business analysis of information processes; MoDaST-2024: 6th International Workshop on Modern Data Science Technologies, May, 31 - June, 1, 2024, Lviv-Shatsk, Ukraine ∗ Corresponding author. † These authors contributed equally. m.t.m.emmerich@liacs.leidenuniv.nl (M. Emmerich); Vasyl.V.Lytvyn@lpnu.ua (V. Lytvyn); victoria.a.vysotska@lpnu.ua (V. Vysotska) 0000-0002-7342-2090 (M. Emmerich); 0000-0002-9676-0180 (V. Lytvyn); 0000-0001-6417-3689 (V. Vysotska); © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR ceur-ws.org Workshop ISSN 1613-0073 Proceedings  Big data analysis;  Analytical data warehouses;  Cloud services;  Repositories and data spaces;  Data consolidation technologies;  Computer linguistics;  Machine Learning Applications;  Recommendation system with collaborative filtering;  Natural Language Processing;  Data Visualization;  Data Acquisition and Wrangling;  Machine Learning;  Clustering;  Neural Networks;  Classification algorithms;  Regression algorithms;  Training (weight optimization) using backpropagation;  Gradient descent;  Setting the learning rate of your neural network;  Deep neural networks;  Batch normalization;  Convolutional neural networks;  Image segmentation;  Object detection (YOLO, SSD, Faster R-CNN);  Evaluating object detection models;  Facial recognition;  Recurrent neural networks;  Transformer networks;  Siamese networks;  Reinforcement Learning. The language of Modern Data Science Technologies Workshop is English. The Modern Data Science Technologies Workshop took the form of oral presentation by peer-reviewed individual papers. The papers were distributed among 32 external reviewers from The Netherlands, Finland, Germany, France, United Kingdom, China, Austria, Czech Republic, Portugal, India, Poland, Ukraine and Ukraine. The Modern Data Science Technologies Workshop gathered participants from different countries including Germany, Algeria, The Netherlands, Finland, Poland, and Ukraine. This year Organizing Committee received 55 submissions, out of which 27 were accepted for presentation as a regular paper. These papers and extended abstracts were published in this Volume II of the 6th International Workshop on Modern Data Science Technologies (MoDaST 2024) proceedings. 2. Acknowledgments The Modern Data Science Technologies Workshop would not have been possible without the support of many people. First of all, we would like to thank all the authors who submitted papers to Modern Data Science Technologies Workshop and thus demonstrated their interest in the research problems within our scope. We are very grateful to the members of our Program Committee for providing timely and thorough reviews and, also, for being cooperative in doing additional review work. We would like to thank the Organizing Committee of the workshop whose devotion and efficiency made this instance of Modern Data Science Technologies Workshop a very interesting and effective scientific forum. We would like to thank Modern Data Science Technologies Workshop Chairs, as well as Program Committee and all Reviewers, for their diligence in selecting the papers and ensuring their high scientific quality. References [1] M. Emmerich, V. Vysotska, V. Lytvynenko, Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2023), Lviv, Ukraine, June 3, 2023, CEUR Workshop Proceedings 3426, CEUR-WS.org 2023. URL: https://dblp.uni-trier.de/db/conf/momlet/momlet2023.html, https://ceur- ws.org/Vol-3426/. [2] M. Emmerich, V. Vysotska, Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2022), Leiden-Lviv, The Netherlands-Ukraine, November 25-26, 2022, CEUR Workshop Proceedings 3312, CEUR-WS.org 2023. URL: https://dblp.uni- trier.de/db/conf/momlet/momlet2022.html, https://ceur-ws.org/Vol-3312/. [3] M. Emmerich, V. Lytvyn, V. Vysotska, V. Lytvynenko, V. Basto-Fernandes, Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2021), Lviv-Shatsk, Ukraine, June 5-6, 2021, CEUR Workshop Proceedings 2917, CEUR-WS.org 2021. URL: https://dblp.uni- trier.de/db/conf/momlet/momlet2021.html, https://ceur-ws.org/Vol-2917/. [4] M. Emmerich, V. Lytvyn, V. Vysotska, V. Basto-Fernandes, V. Lytvynenko, Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2020), Lviv-Shatsk, Ukraine, June 2-3, 2020, CEUR Workshop Proceedings 2631, CEUR-WS.org 2020. URL: https://dblp.uni- trier.de/db/conf/momlet/momlet2020.html, https://ceur-ws.org/Vol-2631/. [5] M. Emmerich, V. Lytvyn, I. Yevseyeva, V. Basto-Fernandes, D. Dosyn, V. Basto- Fernandes, V. Vysotska, Proceedings of the Modern Machine Learning Technologies and Data Science Workshop (MoMLeT&DS 2019), Lviv-Shatsk, Ukraine, June 2-4, 2019, CEUR Workshop Proceedings 2386, CEUR-WS.org 2019. URL: https://dblp.uni-trier.de/db/conf/momlet/momlet2019.html, https://ceur- ws.org/Vol-2386/.