Linked Data and Time - Modeling Researcher Life Lines by Events
Linked Data and Time - Modeling Researcher Life Lines by Events
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关联数据和时间 - 按事件对研究人员生命线进行建模
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
W. Kuhn
中科院分区：
文献类型：
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作者：
Johannes Trame;C. Kessler;W. Kuhn
链接数据网络上的大多数数据集对所表示的实体及其之间的关系强加了静态视图，而忽略了它们所表示的现实的时间方面。在本文中，我们讨论了资源在空间、时间和主题背景下的表示。我们回顾了有关在关联数据网络上表示时间相关关系的有争议的提议。我们认为，表示和使用这种关系是由于对不充分的概念化的直接编码而变得困难的，而不是由于表示语言 RDF 的固有限制。使用从简历中提取的研究人员生命线的示例，我们展示了如何根据事件对活动序列进行建模。我们以 DOLCE Ultralite+DnS 本体论的事件参与模式为基础，展示人们在职业生涯中扮演的地点和社会角色与事件的关系。此外，我们还展示了如何通过时间推理将科学成就与职业轨迹中的事件联系起来。
Most datasets on the Linked Data Web impose a static view on the represented entities and relations between them, neglecting temporal aspects of the reality they represent. In this paper, we address the representation of resources in their spatial, temporal and thematic context. We review the controversial proposals for the representation of time-dependent relations on the Linked Data Web. We argue that representing and using such relations is made hard through the direct encoding of inadequate conceptualizations, rather than through inherent limitations of the representation language RDF. Using the example of researcher life lines extracted from curricula vitae, we show how to model sequences of activities in terms of events. We build upon the event participation pattern from the DOLCE Ultralite+DnS Ontology and show how places and social roles that people play during their careers relate to events. Furthermore, we demonstrate how scientific achievements can be related to events in a career trajectory by means of temporal reasoning.