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A digital library framework for biodiversity information systems

机译:生物多样性信息系统的数字图书馆框架

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Biodiversity Information Systems (BISs) involve all kinds of heterogeneous data, which include ecological and geographical features. However, available information systems offer very limited support for managing these kinds of data in an integrated fashion. Furthermore, such systems do not fully support image content (e.g., photos of landscapes or living organisms) management, a requirement of many BIS end-users. In order to meet their needs, these users—e.g., biologists, environmental experts猳ften have to alternate between separate biodiversity and image information systems to combine information extracted from them. This hampers the addition of new data sources, as well as cooperation among scientists. The approach provided in this paper to meet these issues is based on taking advantage of advances in digital library innovations to integrate networked collections of heterogeneous data. It focuses on creating the basis for a next-generation BIS, combining new techniques of content-based image retrieval and database query processing mechanisms. This paper shows the use of this component-based architecture to support the creation of two tailored BIS systems dealing with fish specimen identification using search techniques. Experimental results suggest that this new approach improves the effectiveness of the fish identification process, when compared to the traditional key-based method.
机译:生物多样性信息系统(BIS)涉及各种异构数据,包括生态和地理特征。但是,可用的信息系统为以集成方式管理此类数据提供的支持非常有限。此外,这样的系统不能完全支持图像内容(例如,风景或活生物的照片)管理,这是许多BIS最终用户的要求。为了满足他们的需求,这些用户(例如生物学家,环境专家)必须在单独的生物多样性和图像信息系统之间进行切换,以结合从中提取的信息。这阻碍了新数据源的增加以及科学家之间的合作。本文提供的解决这些问题的方法是基于利用数字图书馆创新的优势来集成异构数据的网络集合。它着重于创建下一代BIS的基础,结合了基于内容的图像检索和数据库查询处理机制的新技术。本文展示了使用这种基于组件的体系结构来支持创建两个定制的BIS系统,这些系统使用搜索技术来处理鱼标本识别。实验结果表明,与传统的基于密钥的方法相比,这种新方法提高了鱼识别过程的有效性。

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