ABI Development: An ontology of evidence types to support biological data management

研究人员通过从实验室实验到基于计算机的分析等多种不同的方法生成生物数据。这些数据是研究人员用来进行推断和得出科学结论的证据。生物固化的过程旨在以标准化的方式捕捉这些结论和导致这些结论的证据，以便整个科学界都能很容易地获得这些信息。实现这一目标的最有效方法是使用本体来描述证据类型。本体是一种受控制的术语词汇表，其中每个术语都经过仔细定义，并通过精确的关系链接到其他术语。证据本体（EO）是描述用于支持生物学研究中科学结论的研究证据类型的社区标准。EO被世界上的一些人使用？S最突出的蛋白质数据库和基因组资源获取证据信息。这个项目的目标是改进EO并在更大的研究人员社区中推广它的使用。将通过外联、培训和教育工作，包括讲习班和实习，来促进《就业政策》。更广泛的影响将包括向巴尔的摩市公立学校的学生推广，重点是教授以受控方式构建信息的重要性。暑期实习生将参与EO开发和生物信息学活动。大量从事广泛生物学研究的科学家将从持续发展和扩大使用环境信息系统中受益。由于多种原因，以一致和可计算的方式描述证据和断言方法（即，是人类还是机器发表陈述）的能力是必不可少的。方法捕获是科学方法的核心，可以影响结果的评估，将结构化证据与存储的数据相关联，允许从甚至最大的数据库中进行选择性数据查询和检索，结构化证据系统使自动化质量控制成为可能，这对于大规模数据管理至关重要。目前，包括蛋白质数据库、模式生物数据库、表型资源和基因表达数据库在内的近30种生物资源正在使用证据本体（Evidence Ontology， EO）来获取证据信息、支持结构化数据查询、对相关数据进行分组或建立质量控制机制。我们将进一步发展行政分析，以解决结构性问题、厘清主轴、增加逻辑约束，并将行政分析与相关资源相关联。新的证据类型将根据研究界的需要不断添加到本体论中。将创建一个网络资源，其中包括改进的可视化工具，用于与EO术语相关的证据和数据、完整的用户文档和可下载的内容。EO还将开发质量评估方法，使研究人员能够更好地评估证据。将开展外联、培训和教育，以扩大EO的用户基础，并教育研究人员和学生了解获取证据的价值和方法。EO开发人员将出席科学会议、发表论文、接待实习生、举办研讨会和科学推广活动。通过改进EO和提高用户意识，研究人员将能够更好地利用证据和相关数据。欲了解更多信息，请访问：http://evidenceontology.org

Researchers generate biological data from many diverse methods that range from laboratory experiments to computer-based analyses. These data serve as the evidence that researchers use to make inferences and draw scientific conclusions. The process of biocuration seeks to capture these conclusions and the evidence that led to them in a standardized way so that the information is readily accessible to the entire scientific community. The most efficient way to accomplish this is to use an ontology to describe the evidence types. An ontology is a controlled vocabulary of terms where each term is carefully defined and linked to other terms by precise relationships. The Evidence Ontology (EO) is a community standard for describing types of research evidence used to support scientific conclusions in biological research. The EO is used by some of the world?s most prominent protein databases and genomic resources to capture evidence information. The goal of this project is to improve EO and promote its use by a larger community of researchers. The EO will be promoted through outreach, training, and education efforts, including workshops and internships. Broader impacts will include outreach efforts to Baltimore City Public Schools students focusing on teaching the importance of structuring information in a controlled way. Summer interns will engage in EO development and bioinformatics activities. A vast number of scientists researching a wide range of biological topics will benefit from the continued development and expanded use of the EO.The ability to describe both evidence and assertion method (i.e. whether a human or a machine makes a statement) in a consistent and computable fashion is essential for multiple reasons. Capture of methodology is central to the scientific method and can impact evaluation of results, associating structured evidence with stored data allows for selective data queries and retrieval from even the largest databases, and structured evidence systems make automated quality control possible, which is essential for large-scale data management. Nearly 30 biological resources including protein databases, model organism databases, phenotype resources, and gene expression databases currently are using the Evidence Ontology (EO) to capture evidence information, support structured data queries, group related data, or establish quality control mechanisms. EO will be developed further to address structural issues, clarify the main axis, add logical constraints, and map EO to related resources. New evidence types will be continually added to the ontology based on the needs of the research community. A web resource will be created that includes improved visualization tools for evidence and data associated with EO terms, complete user documentation, and downloadable content. EO will also develop quality assessment methodologies to enable researchers to better evaluate evidence. Outreach, training, and education will be conducted to grow the EO user base and educate researchers and students about the value and means of capturing evidence. EO developers will present at scientific conferences, publish papers, host interns, and conduct workshops and science outreach activities. By improving EO and increasing user awareness, researchers will be better able to make the most of evidence and associated data. For more information, please visit: http://evidenceontology.org.