Automated assessment of data quality in biological knowledge resources

该项目旨在开发识别生物数据库中质量差数据的方法。生物医学研究的基础是庞大的生物数据数据库。数据质量主要是通过人工管理来管理的，但是评估质量的自动化方法是非常需要的。该项目期望开发一套用于评估生物数据质量的计算工具，利用基于数据库记录连接的网络分析的创新方法。这些工具将能够大规模地量化数据质量。研究人员、基于证据的生物医学决策者以及使用这些数据的分析或预测工具将做出更可靠的推断和决策。

This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approach based on network analysis of database record connectivity. These tools will enable quantifying data quality at scale. Researchers, evidence-based decision-makers in biomedicine, and the analytical or predictive tools that use this data will make more reliable inferences and decisions.