Cliopatria -一个从公元前3400年到公元2024年的全球政治实体的地理空间数据库。

IF 7.2 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-12 DOI:10.1038/s41597-025-04516-9
James S Bennett, Erin Mutch, Andrew Tollefson, Ed Chalstrey, Majid Benam, Enrico Cioni, Jenny Reddish, Jakob Zsambok, Jill Levine, C Justin Cook, Pieter Francois, Daniel Hoyer, Peter Turchin
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引用次数: 0

摘要

对全球历史复杂动态的科学理解——从国家的兴起和扩张到它们的衰落和衰落,从它们与经济或外交交流的和平互动到暴力对抗——其核心要求是对历史政治实体、它们的位置、范围和持续时间进行一致和明确的编码。人们曾多次尝试以不同的时间深度和分辨率制作政治的数字地理概要。大多数地理空间数据集的范围有限,许多更全面的地理空间数据集要么必须获得许可,要么必须以专有格式存储,这使得学术分析难以访问。为了解决这些问题,我们开发了Cliopatria,这是一个全面的开源地理空间数据集,涵盖了从公元前3400年到公元2024年的世界各国。目前,它包括按不同时间步长和空间尺度采样的1600多个政治实体。在这里,我们将讨论它的结构、范围和当前的局限性。
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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Cliopatria - A geospatial database of world-wide political entities from 3400BCE to 2024CE.

The scientific understanding of the complex dynamics of global history - from the rise and spread of states to their declines and falls, from their peaceful interactions with economic or diplomatic exchanges to violent confrontations - requires, at its core, a consistent and explicit encoding of historical political entities, their locations, extents and durations. Numerous attempts have been made to produce digital geographical compendia of polities with different time depths and resolutions. Most have been limited in scope and many of the more comprehensive geospatial datasets must either be licensed or are stored in proprietary formats, making access for scholarly analysis difficult. To address these issues we have developed Cliopatria, a comprehensive open-source geospatial dataset of worldwide states from 3400BCE to 2024CE. Presently it comprises over 1600 political entities sampled at varying timesteps and spatial scales. Here, we discuss its construction, its scope, and its current limitations.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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