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spatial@linkedscience - Exploring the Research Field of GIScience with Linked Data

机译:Spatial @ LinkedScience - 通过链接数据探索GISCING的研究领域

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Metadata for scientific publications contain various explicit and implicit spatio-temporal references. Data on conference locations as well as author and editor affiliations - both changing over time – enable insights into the geographic distribution of scientific fields and particular specializations. At the same time, these byproducts of scientific bibliographies offer a great opportunity to integrate data across different bibliographies to get a more complete picture of a domain. In this paper, we demonstrate how the Linked Data paradigm can assist in enriching and integrating such collections. Starting from the bibliographies of the GIScience, COSIT, ACM GIS, and AGILE conference series, we show how to convert the data to Linked Data and integrate the previously separate datasets. We focus on the spatio-temporal aspects and discuss how they help in matching and disambiguating entities such as authors or universities. We introduce a novel user interface to explore the integrated dataset, demonstrating the potential of Linked Data for innovative applications using spatio-temporal information, and discuss how more complex queries can be addressed. While we focus on bibliographies, the presented work is part of the broader vision of a Linked Science infrastructure for e-Science.
机译:科学出版物的元数据包含各种显式和隐含的时空参考。关于会议地点以及作者和编辑附属机构的数据 - 两者都改变​​了时间 - 使能科学领域的地理分布和特殊专业化的见解。与此同时,这些科学教训的这些副产品提供了一个很好的机会,可以将数据整合到不同的书目上,以获得更完整的域图片。在本文中,我们展示了联系数据范例如何协助丰富和整合这些系列。从GISCICE,COST,ACM GIS和Agile会议系列的书目开始,我们展示了如何将数据转换为链接数据并集成先前单独的数据集。我们专注于时空方面,并讨论他们如何帮助匹配和消除作者或大学的歧义实体。我们介绍了一种新颖的用户界面来探索集成的数据集,展示使用时空信息的创新应用程序的链接数据的潜力,并讨论如何解决更复杂的查询。虽然我们专注于书目,但所呈现的工作是E-Science联系科学基础设施更广泛愿景的一部分。

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