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Use of Subimages in Fish Species Identification: A Qualitative Study

机译:亚图像在鱼类物种鉴定中的应用:定性研究

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Many scholarly tasks involve working with subdocuments, or contextualized fine-grain information, i.e., with information that is part of some larger unit. A digital library (DL) facilitates management, access, retrieval, and use of collections of data and metadata through services. However, most DLs do not. provide infrastructure or services to support working with subdocuments. Superimposed information (SI) refers to new information that is created to reference subdocuments in existing information resources. We combine this idea of SI with traditional DL services, to define and develop a DL with SI (SI-DL). We explored the use of subimages and evaluated the use of SuperlDR, a prototype SI-DL, in fish species identification, a scholarly task that involves working with subimages. The contexts and strategies of working with subimages in SuperlDR suggest new and enhanced support (SI-DL services) for scholarly tasks that involve working with subimages, including new ways of querying and searching for subimages and associated information. The main conceptual contributions of our work are the insights gained from these findings of the use of subimages and of SuperlDR, which lead to recommendations for the design of digital libraries with superimposed information.
机译:许多学术任务涉及处理子文档或上下文相关的细粒度信息,即处理某些较大单元中的信息。数字图书馆(DL)有助于通过服务管理,访问,检索和使用数据和元数据的集合。但是,大多数DL不会。提供基础结构或服务以支持处理子文档。叠加信息(SI)是指创建用来引用现有信息资源中的子文档的新信息。我们将SI与传统DL服务的思想相结合,以定义和开发具有SI的DL(SI-DL)。我们探索了子图像的使用,并评估了SuperlDR(SI-DL原型)在鱼类物种识别中的用途,这是一项涉及处理子图像的学术任务。在SuperlDR中使用子图像的上下文和策略建议为涉及子图像的学术任务提供新的增强支持(SI-DL服务),包括查询和搜索子图像及相关信息的新方法。我们工作的主要概念性贡献是从使用亚图像和SuperlDR的这些发现中获得的见解,这些见解为设计具有叠加信息的数字图书馆提供了建议。

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