Development of an integrated data system for regional tourism analysis in Italy: A microdata perspective

IF 3.5 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Big Data Research Pub Date : 2025-06-07 DOI:10.1016/j.bdr.2025.100550

Samuele Cesarini, Fabrizio Antolini, Ivan Terraglia

引用次数: 0

Abstract

This paper presents the development of an integrated data system tailored for the Italian regions, combining microdata from the Bank of Italy's and ISTAT's surveys. These datasets offer an in-depth analysis of both domestic and international aspects of tourism, framed within the theoretical context of the tourism determinants. By merging this integrated dataset with additional data from other statistical sources, this study offers a queryable relational database enabling granular regional analysis. Currently, tourism statistics in Italy are fragmented and do not provide a unified picture of tourism in its many aspects. The relational model's interoperability addresses Italy's fragmented tourism data landscape, and its data definition language represents an important step towards the creation of a unified tourism archive. Micro-data allows for different statistical analyses than those usually carried out with aggregated data, increasing knowledge of the dynamics of the sector.

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意大利区域旅游分析综合数据系统的开发：微数据视角

本文介绍了为意大利地区量身定制的综合数据系统的开发，结合了意大利银行和ISTAT调查的微观数据。这些数据集在旅游决定因素的理论背景下，对国内和国际旅游方面进行了深入分析。通过将这个集成数据集与其他统计来源的其他数据合并，本研究提供了一个可查询的关系数据库，可以进行粒度区域分析。目前，意大利的旅游统计数据是支离破碎的，不能提供一个统一的旅游业的许多方面的画面。关系模型的互操作性解决了意大利支离破碎的旅游数据格局，其数据定义语言代表了创建统一旅游档案的重要一步。与通常使用汇总数据进行的统计分析相比，微观数据允许进行不同的统计分析，从而增加了对该部门动态的了解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data Research Computer Science-Computer Science Applications

CiteScore

8.40

自引率

3.00%

发文量

期刊介绍： The journal aims to promote and communicate advances in big data research by providing a fast and high quality forum for researchers, practitioners and policy makers from the very many different communities working on, and with, this topic. The journal will accept papers on foundational aspects in dealing with big data, as well as papers on specific Platforms and Technologies used to deal with big data. To promote Data Science and interdisciplinary collaboration between fields, and to showcase the benefits of data driven research, papers demonstrating applications of big data in domains as diverse as Geoscience, Social Web, Finance, e-Commerce, Health Care, Environment and Climate, Physics and Astronomy, Chemistry, life sciences and drug discovery, digital libraries and scientific publications, security and government will also be considered. Occasionally the journal may publish whitepapers on policies, standards and best practices.