基于元数据仓储与动态链接的图书馆资源整合系统的整合与实现

研究了对资源整合的方法,设计与实现了一种基于元数据仓储与动态链接的资源整合系统。采用OpenURL技术解决了网络数据库之间相互链接的问题。采用元数据仓储,通过元数据收集、整理、聚合、存储,建立了各种分类体系,构建了资源导航、高级检索、个性化服务、用户权限管理等功能,使用户能够在统一的界面上,实现对图书馆资源的统一检索、浏览和利用。     

临床数据中心建设方法探讨

针对武汉大学中南医院目前多个异构信息系统中非标准化数据无法共享、集成、且无法深层次利用的现状,提出了基于临床数据中心的解决方案。创建了扩展性强、可灵活定制数据模型的临床数据中心,提供了标准化的流程以满足医院业务需求,并通过实例介绍了应用新方法建设CDR的流程及架构。     

网络数据的信任度与统计元数据

2010年2月16日发丧在《公其科学图书馆·综合》（PLoSOne）期刊L的一份研究报告称,研究人员对4个臻因数据库GenBank、UCSC Genome Browser、DOE Joint Genome Instillzte数据库l羽1Ensembl数据库中所有非灵长类缱阕组进行了人类特异性菔复序列Alu 原件的筛硷,在搜索的2027个原始序列基因组中,党然发现有454个存九人类Alu元件序列的污染,约占总数的22．39％。由此提出网络数据的信任度问题。严格地说,米自网络的所订统计数据必须经过同行确认．州时用正确的元数据告知数据的使川人或信息系统如何正确扶墩、阅渎、处理。分析、解释和表达实际存任的统计数据。水文讨论丁医学信息中统计元数据、统计元数据标准体系及其重要忡。     

Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network experience

Background

Systematic study of clinical phenotypes is important for a better understanding of the genetic basis of human diseases and more effective gene-based disease management. A key aspect in facilitating such studies requires standardized representation of the phenotype data using common data elements (CDEs) and controlled biomedical vocabularies. In this study, the authors analyzed how a limited subset of phenotypic data is amenable to common definition and standardized collection, as well as how their adoption in large-scale epidemiological and genome-wide studies can significantly facilitate cross-study analysis.

Methods

The authors mapped phenotype data dictionaries from five different eMERGE (Electronic Medical Records and Genomics) Network sites studying multiple diseases such as peripheral arterial disease and type 2 diabetes. For mapping, standardized terminological and metadata repository resources, such as the caDSR (Cancer Data Standards Registry and Repository) and SNOMED CT (Systematized Nomenclature of Medicine), were used. The mapping process comprised both lexical (via searching for relevant pre-coordinated concepts and data elements) and semantic (via post-coordination) techniques. Where feasible, new data elements were curated to enhance the coverage during mapping. A web-based application was also developed to uniformly represent and query the mapped data elements from different eMERGE studies.

Results

Approximately 60% of the target data elements (95 out of 157) could be mapped using simple lexical analysis techniques on pre-coordinated terms and concepts before any additional curation of terminology and metadata resources was initiated by eMERGE investigators. After curation of 54 new caDSR CDEs and nine new NCI thesaurus concepts and using post-coordination, the authors were able to map the remaining 40% of data elements to caDSR and SNOMED CT. A web-based tool was also implemented to assist in semi-automatic mapping of data elements.

Conclusion

This study emphasizes the requirement for standardized representation of clinical research data using existing metadata and terminology resources and provides simple techniques and software for data element mapping using experiences from the eMERGE Network.     

电子病历与健康档案数据交换规范化的研究与应用

运用现代信息学理论和技术,以临床信息与病案书写规范为指南,并参照国家相关信息交换标准规范及国际标准化组织信息规范。针对电子病历与健康档案数据交换,采用可扩展标记语言（XML）技术,制定了《健康档案与病案的电子数据交换规范化应用指南》。并依据指南定义了电子病历与健康档案数据元素信息的XML结构文档,对提高医药卫生行业管理水平、信息安全传输和交换共享利用具有良好的应用价值。     

本体支持的生物医学领域元数据异质性与可兼容性研究

利用本体支持数据元素的表示,是提升元数据机器可理解性的重要手段。采用生物医学通用数据元素数据库caDSR中的数据,评价相关的数据元素之间的语义异质性,并利用机器学习对元数据可兼容性进行判别。首先,从caDSR 中选取60对通用数据元素,涉及人口学、生活方式、既往病史和实验室测量等方面。依据ISO/IEC 111179标准抽提数据元素的必要组分,利用NCIT的本体支持,就每对关联数据元素的相似度进行评价。依据数据元素内部各组分的语义相似度,利用支持向量机,对数据元素间的可兼容性做出预测,其准确度超过80%。研究结果显示,目前在caDSR数据库中,对于元数据的定义存在较大的异质性,这些异质性在数据元素的概念域尤其集中。虽然如此,通过机器学习的方法,还是能够依据现有的数据元素的定义实现数据可兼容性的自动判断。研究所建立的方法,对于优化数据元素构建流程、丰富数据标准化工具具有一定的应用价值。     

The extensible neuroimaging archive toolkit

The Extensible Neuroimaging Archive Toolkit (XNAT) is a software platform designed to facilitate common management and productivity tasks for neuroimaging and associated data. In particular, XNAT enables qualitycontrol procedures and provides secure access to and storage of data. XNAT follows a threetiered architecture that includes a data archive, user interface, and middleware engine. Data can be entered into the archive as XML or through data entry forms. Newly added data are stored in a virtual quarantine until an authorized user has validated it. XNAT subsequently maintains a history profile to track all changes made to the managed data. User access to the archive is provided by a secure web application. The web application provides a number of quality control and productivity features, including data entry forms, data-type-specific searches, searches that combine across data types, detailed reports, and listings of experimental data, upload/download tools, access to standard laboratory workflows, and administration and security tools. XNAT also includes an online image viewer that supports a number of common neuroimaging formats, including DICOM and Analyze. The viewer can be extended to support additional formats and to generate custom displays. By managing data with XNAT, laboratories are prepared to better maintain the long-term integrity of their data, to explore emergent relations across data types, and to share their data with the broader neuroimaging community.     

基于多维元数据模型的军队卫生统计信息系统架构研究

目的 :提出一种多维元数据模型,并设计基于该模型的军队卫生统计信息系统架构,用于促进统计信息共享并提高统计工作效率。方法:基于统计元数据构建多维元数据模型,采用面向服务的多层架构对军队卫生统计信息系统架构进行设计。结果:该系统能够自动将统计报表按指标分类,将不同类别统计指标推送给统计相关单位,待数据填报后汇总生成所需报表。结论:该系统解决了统计过程中数据重复填报和数据不一致的问题,提高了军队卫生统计信息的共享性和复用性。     

Linking a Consortium-Wide Data Quality Assessment Tool with the MIRACUM Metadata Repository

Background  Many research initiatives aim at using data from electronic health records (EHRs) in observational studies. Participating sites of the German Medical Informatics Initiative (MII) established data integration centers to integrate EHR data within research data repositories to support local and federated analyses. To address concerns regarding possible data quality (DQ) issues of hospital routine data compared with data specifically collected for scientific purposes, we have previously presented a data quality assessment (DQA) tool providing a standardized approach to assess DQ of the research data repositories at the MIRACUM consortium''s partner sites. Objectives  Major limitations of the former approach included manual interpretation of the results and hard coding of analyses, making their expansion to new data elements and databases time-consuming and error prone. We here present an enhanced version of the DQA tool by linking it to common data element definitions stored in a metadata repository (MDR), adopting the harmonized DQA framework from Kahn et al and its application within the MIRACUM consortium. Methods  Data quality checks were consequently aligned to a harmonized DQA terminology. Database-specific information were systematically identified and represented in an MDR. Furthermore, a structured representation of logical relations between data elements was developed to model plausibility-statements in the MDR. Results  The MIRACUM DQA tool was linked to data element definitions stored in a consortium-wide MDR. Additional databases used within MIRACUM were linked to the DQ checks by extending the respective data elements in the MDR with the required information. The evaluation of DQ checks was automated. An adaptable software implementation is provided with the R package DQAstats . Conclusion  The enhancements of the DQA tool facilitate the future integration of new data elements and make the tool scalable to other databases and data models. It has been provided to all ten MIRACUM partners and was successfully deployed and integrated into their respective data integration center infrastructure.     

基于元数据的异构蛋白质-蛋白质相互作用数据库整合

研究蛋白质-蛋白质相互作用是理解生命活动的基础。在蛋白质-蛋白质相互作用的研究过程中,产生了大量来源于实验和预测的数据。这些数据存储于彼此异构的数据库中。对上述异构数据库进行数据整合是实现共享和最大限度利用已有蛋白质-蛋白质相互作用数据必须解决的关键问题。据此问题提出了基于元数据理论和查询转换方法的异构数据库整合方案,并构建了一个基于网络的蛋白质-蛋白质相互作用相关异构数据库的整合平台,成功实现了对9个蛋白质-蛋白质相互作用数据库的整合。