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OWLing Clinical Data Repositories With the Ontology Web Language

机译:使用本体网络语言OWLing临床数据存储库

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Background The health sciences are based upon information. Clinical information is usually stored and managed by physicians with precarious tools, such as spreadsheets. The biomedical domain is more complex than other domains that have adopted information and communication technologies as pervasive business tools. Moreover, medicine continuously changes its corpus of knowledge because of new discoveries and the rearrangements in the relationships among concepts. This scenario makes it especially difficult to offer good tools to answer the professional needs of researchers and constitutes a barrier that needs innovation to discover useful solutions. Objective The objective was to design and implement a framework for the development of clinical data repositories, capable of facing the continuous change in the biomedicine domain and minimizing the technical knowledge required from final users. Methods We combined knowledge management tools and methodologies with relational technology. We present an ontology-based approach that is flexible and efficient for dealing with complexity and change, integrated with a solid relational storage and a Web graphical user interface. Results Onto Clinical Research Forms (OntoCRF) is a framework for the definition, modeling, and instantiation of data repositories. It does not need any database design or programming. All required information to define a new project is explicitly stated in ontologies. Moreover, the user interface is built automatically on the fly as Web pages, whereas data are stored in a generic repository. This allows for immediate deployment and population of the database as well as instant online availability of any modification. Conclusions OntoCRF is a complete framework to build data repositories with a solid relational storage. Driven by ontologies, OntoCRF is more flexible and efficient to deal with complexity and change than traditional systems and does not require very skilled technical people facilitating the engineering of clinical software systems.
机译:背景健康科学是基于信息的。临床信息通常由医师使用不稳定的工具(例如电子表格)进行存储和管理。生物医学领域比采用信息和通信技术作为普遍商业工具的其他领域更为复杂。而且,由于新发现和概念之间关系的重新安排,医学不断地改变其知识主体。这种情况特别难以提供好的工具来满足研究人员的专业需求,并且成为需要创新才能发现有用解决方案的障碍。目的目的是设计和实施用于开发临床数据存储库的框架,该框架能够应对生物医学领域的不断变化,并最大限度地减少最终用户所需的技术知识。方法我们将知识管理工具和方法论与关系技术相结合。我们提出了一种基于本体的方法,该方法灵活高效地处理复杂性和变更,并与可靠的关系存储和Web图形用户界面集成在一起。结果进入临床研究表格(OntoCRF)是用于定义,建模和实例化数据存储库的框架。它不需要任何数据库设计或编程。定义新项目所需的所有信息均在本体中明确说明。而且,用户界面是作为网页自动动态构建的,而数据则存储在通用存储库中。这允许立即部署和填充数据库,以及任何修改的即时在线可用性。结论OntoCRF是构建具有可靠关系存储的数据存储库的完整框架。在本体论的驱动下,OntoCRF比传统系统更灵活,更有效地处理复杂性和变更,并且不需要技术娴熟的技术人员来促进临床软件系统的工程设计。

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