结构的力量

Erin Canning, Susan Brown, Sarah Roger, Kim Martin
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引用次数: 0

摘要

信息系统是由有意图的人开发的——它们被设计用来帮助创造者和用户用数据讲述特定的故事。在信息系统中,通常不可见的元数据结构深刻地影响了可以从该数据中获得的含义。网络文化奖学金项目的链接基础设施(LINCS)通过使用链接的开放数据将人文学科数据集转换为有组织的、相互连接的、机器可处理的资源,帮助人文学科研究人员讲述故事。LINCS为在线文化材料提供上下文,将它们相互连接,并将它们置于资源中,以改进研究的网络资源。本文描述了LINCS团队如何使用链接数据的共享标准,特别是本体(通常看不见但功能强大),通过结构为元数据带来意义。LINCS元数据——由有关文化文物、人员和流程的链接开放数据组成——以及支持它的结构必须代表多种不同的认识方式。它需要采用各种方法来整合上下文数据,并通过细微差别和上下文来讲述故事,这些方法由反映特殊性和复杂性并为其腾出空间的数据结构所定位和支持。由于它解决了每个研究数据集的特殊性,LINCS同时努力平衡互操作性,通过一定程度的泛化实现,具有上下文和领域特定的需求。LINCS团队采用和使用本体的方法以交叉性、多样性和差异性为中心。所使用的结构将给数据带来什么意义的问题与将数据连接在一起所引入的意义同样重要,该项目已将这一前提纳入其决策和实施过程。为了传达对类别和分类的理解,将其作为上下文嵌入-文化产生,交叉和话语- LINCS团队将它们不是固定的,而是作为调查的基础和理解的起点。元数据结构与词汇表一样重要,可以产生这种含义。
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The Power to Structure
Information systems are developed by people with intent—they are designed to help creators and users tell specific stories with data. Within information systems, the often invisible structures of metadata profoundly impact the meaning that can be derived from that data. The Linked Infrastructure for Networked Cultural Scholarship project (LINCS) helps humanities researchers tell stories by using linked open data to convert humanities datasets into organized, interconnected, machine-processable resources. LINCS provides context for online cultural materials, interlinks them, andgrounds them in sources to improve web resources for research. This article describes how the LINCS team is using the shared standards of linked data and especially ontologies—typically unseen yet powerful—to bring meaning mindfully to metadata through structure. The LINCS metadata—comprised of linked open data about cultural artifacts, people, and processes—and the structures that support it must represent multiple, diverse ways of knowing. It needs to enable various means of incorporating contextual data and of telling stories with nuance and context, situated and supported by data structures that reflect and make space for specificities and complexities. As it addresses specificity in each research dataset, LINCS is simultaneously working to balance interoperability, as achieved through a level of generalization, with contextual and domain-specific requirements. The LINCS team’s approach to ontology adoption and use centers on intersectionality, multiplicity, and difference. The question of what meaning the structures being used will bring to the data is as important as what meaning is introduced as a result of linking data together, and the project has built this premise into its decision-making and implementation processes. To convey an understanding of categories and classification as contextually embedded—culturally produced, intersecting, and discursive—the LINCS team frames them not as fixed but as grounds for investigation and starting points for understanding. Metadata structures are as important as vocabularies for producing such meaning.
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