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Authors: Erika Mináriková 1 ; Galena Pisoni 2 ; Bálint Molnár 3 and Hanna Skaftadottir 4

Affiliations: 1 Faculty of Economic Informatics, University of Economics in Bratislava, Bratislava, Slovakia ; 2 York Business School, York St. John University, Lord Mayor’s Walk, YO31 7EX, York, U.K. ; 3 Eötvös Loránd University, ELTE, IK Pázmány Péter 1/C, 1117, Budapest, Hungary ; 4 Department of Business, Bifrost University, Iceland

Keyword(s): Linguistic Summaries, Smart Cities, Enterprise Architectures, Business Intelligence Reporting, Drill-Down and Roll-up Summaries.

Abstract: An increasing number of intelligent urban services rely on the use of Information and Communication Technologies (ICT). Data-driven approach is often considered for supporting sustainable cities, provided the pervasive nature of the Internet of Things (IoT) like sensors, and their capabilities to collect data for elaborating to the cities. This paper focuses on an intelligent business reporting approach explaining the bicycle sharing patterns by linguistic summaries in order to provide relevant insights for decision makers and citizens. We explored the developments in bicycle sharing stations in different periods of the day for months and seasons. The business intelligence query operations of drill-down and roll-up are often used in data reporting and analysis. In this work, these operations are realized by linguistic summaries. The main aim is to propose an approach for analysis and visualization in an understandable and interpretable way for diverse user categories. Experiments wer e conducted on the Dublin bicycle sharing data set. Finally, a way how cities can set in place the collection of data coming from different sources, as well as relevant enterprise infrastructures and data analytic pipelines for such service are discussed. (More)

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Paper citation in several formats:
Mináriková, E.; Pisoni, G.; Molnár, B. and Skaftadottir, H. (2024). Business Intelligence Reporting by Linguistic Summaries for Smart Cities: A Case on Explaining Bicycle Sharing Patterns. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: SEC-SCIS; ISBN 978-989-758-692-7; ISSN 2184-4992, SciTePress, pages 762-768. DOI: 10.5220/0012748200003690

@conference{sec-scis24,
author={Erika Mináriková. and Galena Pisoni. and Bálint Molnár. and Hanna Skaftadottir.},
title={Business Intelligence Reporting by Linguistic Summaries for Smart Cities: A Case on Explaining Bicycle Sharing Patterns},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: SEC-SCIS},
year={2024},
pages={762-768},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012748200003690},
isbn={978-989-758-692-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: SEC-SCIS
TI - Business Intelligence Reporting by Linguistic Summaries for Smart Cities: A Case on Explaining Bicycle Sharing Patterns
SN - 978-989-758-692-7
IS - 2184-4992
AU - Mináriková, E.
AU - Pisoni, G.
AU - Molnár, B.
AU - Skaftadottir, H.
PY - 2024
SP - 762
EP - 768
DO - 10.5220/0012748200003690
PB - SciTePress