Open semantic annotation of scientific publications using DOMEO.
Open semantic annotation of scientific publications using DOMEO.
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DOI：
10.1186/2041-1480-3-s1-s1
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发表时间：
2012-04-24
影响因子：
1.9
通讯作者：
Clark T
中科院分区：
文献类型：
--
作者：
Ciccarese P;Ocana M;Clark T
我们的小组开发了一个有用的共享软件框架，用于使用开放表示模型执行、版本控制、共享和查看多种 Web 注释。 Domeo 注释工具是与这种开放模型注释本体 (AO) 一起开发的。注释框架和开放模型的开发是由几种不同类型的 alpha 用户的需求驱动的，包括来自大学研究实验室、在线科学社区、出版和制药公司的基础科学家和生物医学管理者。该工具包逐步实现了多个用例。生物医学通信中的这些用例包括个人笔记、小组文档注释、语义标记、主张证据上下文提取、试剂标记以及实体提取算法的文本挖掘结果的管理。我们在此报告 Domeo 用户界面。 Domeo 已作为 NIH 神经科学信息框架（NIF，http://www.neuinfo.org）的一部分部署在测试版中，并计划在 NIF 的下一个完整版本中进行生产部署。未来的论文将详细描述这项工作的其他方面，包括注释框架服务和用于与外部文本挖掘服务（例如 NCBO Annotator Web 服务）以及使用 Apache UIMA 框架的其他文本挖掘应用程序集成的组件。
Our group has developed a useful shared software framework for performing, versioning, sharing and viewing Web annotations of a number of kinds, using an open representation model. The Domeo Annotation Tool was developed in tandem with this open model, the Annotation Ontology (AO). Development of both the Annotation Framework and the open model was driven by requirements of several different types of alpha users, including bench scientists and biomedical curators from university research labs, online scientific communities, publishing and pharmaceutical companies. Several use cases were incrementally implemented by the toolkit. These use cases in biomedical communications include personal note-taking, group document annotation, semantic tagging, claim-evidence-context extraction, reagent tagging, and curation of textmining results from entity extraction algorithms. We report on the Domeo user interface here. Domeo has been deployed in beta release as part of the NIH Neuroscience Information Framework (NIF, http://www.neuinfo.org) and is scheduled for production deployment in the NIF’s next full release. Future papers will describe other aspects of this work in detail, including Annotation Framework Services and components for integrating with external textmining services, such as the NCBO Annotator web service, and with other textmining applications using the Apache UIMA framework.