Dacura平台——历史研究的数据收集和知识提取新途径

Dacura:A New Solution to Data Harvesting and Knowledge Extraction for the Historical Sciences

随着计算机科技的进步,我们可以解决历史学家在收集和评估基于互联网的海量数据时遭遇到的各类问题。作为范例,本文介绍Dacura数据维护平台。它被用来协助历史研究者从互联网或者其他数据源收集、分析、维护高质量数据。Dacura使用语义知识图谱技术将数据表示为复杂的、相互关联的知识,在不需要查询表的情况下,允许快速搜索和检索特定数据。Dacura使各种工具的生产自动化,以帮助非专业人士逐步构建高质量的知识库,并从大量数据源里将数据整合进它的知识综合维护模型中。Dacura平台所具有的这些特性,为用户快捷地收集和自动分析来自互联网的资源提供了新的途径。本文将为读者提供一个Dacura平台实际操作的范例:这一平台如何应用于填充和管理Seshat数据库。

New advances in computer science address problems historical scientists face in gathering and evaluating the now vast data sources available through the Internet.As an example we introduce Dacura,a dataset curation platform designed to assist historical researchers in harvesting,evaluating,and curating high-quality information sets from the Internet and other sources.Dacura uses semantic knowledge graph technology to represent data as complex,inter-related knowledge allowing rapid search and retrieval of highly specific data without the need of a lookup table.Dacura automates the generation of tools to help non-experts curate high quality knowledge bases over time and to integrate data from multiple sources into its curated knowledge model.Together these features allow rapid harvesting and automated evaluation of Internet resources.We provide an example of Dacura in practice as the software employed to populate and manage the Seshat databank.