Proto-OKN Theme 1: BioBricks-OKG An Open Knowledge Graph For Cheminformatics And Chemical Safety

NSF Proto-Open Knowledge Network Theme 1项目旨在增强开源BioBricks系统，将其转变为有效的知识图谱后端，以促进访问关键的化学品健康和安全数据，使人工智能能够用于开发新的化学品测试和监管方法。目前，横跨健康信息学、毒理学和化学信息学的数据生态系统由许多相互脱节的数据库组成，可用性不一致。访问、处理和集成来自不同来源的数据以构建健壮的模型是具有挑战性的。BioBricks Open Knowledge Graph(BioBricks-OKG)旨在通过半自动将表格数据协调成统一的知识图来解决这一问题。这将通过本体对齐方法加强数据库之间的数据共享。此外，BioBricks-OKG的目标是将这些技术扩展到60多个公共卫生和化学信息学数据库，显著改善数据一致性和可访问性。BioBricks-OKG将通过促进数据科学和机器学习的整合，极大地造福于公共卫生、医疗和生命科学领域。一旦投入使用，诊所、制药公司、监管机构和生物信息学合同研究组织(CRO)就可以利用BioBricks-OKG知识图谱进行智能数据查询，而不需要复杂的数据存储库导航或冗余的数据提取管道。该项目利用了BioBricks-AI框架和项目团队在构建以毒理学为重点的知识图谱方面的经验。BioBricks-AI框架提供了开放源码的存储库，可以将健康信息数据库转换为可分发的、可扩展的数据分析的序列化格式。这项工作包括将BioBricks-AI存储库和公共卫生数据库简化为一个巨大的图形数据库。这个数据库将把化学品、它们的遗传、分子和细胞破坏、健康危害、不良后果途径、测试方法和其他与化学品安全和监管有关的实体联系起来。国家毒理学计划的替代毒理学方法评估机构间中心(NICEATM)将使用由此产生的BioBricks-OKG来设计、收集信息和评估“新方法方法学”(NAM)测试指南。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This NSF Proto-Open Knowledge Network Theme 1 project aims to enhance the open-source BioBricks system, transforming it into an effective knowledge graph backend to facilitate access to crucial chemical health and safety data, enabling the use of AI in developing new chemical testing and regulation approaches. Currently, the data ecosystem that spans health informatics, toxicology, and cheminformatics comprises numerous disjointed databases with inconsistent availability. It is challenging to access, process, and integrate data from various sources for robust model construction. The BioBricks Open Knowledge Graph (BioBricks-OKG) is designed to address this issue by semi-automating the harmonization of tabular data into a unified knowledge graph. This will enhance data sharing between databases through ontology alignment methodologies. Furthermore, BioBricks-OKG aims to scale these techniques to over 60 public health and cheminformatics databases, significantly improving data harmonization and accessibility. The BioBricks-OKG will greatly benefit the public health, medical, and life science fields by fostering the integration of data science and machine learning. Once operational, clinics, pharmaceutical companies, regulatory agencies, and bioinformatics Contract Research Organizations (CROs) can utilize the BioBricks-OKG knowledge graph for intelligent data queries, obviating the need for complex data repository navigation or redundant data extraction pipelines. The project leverages the BioBricks-AI framework and the project team's experience in building toxicology-focused knowledge graphs. The BioBricks-AI framework offers open-source repositories that transform health informatics databases into a distributable, serialized format for scalable data analysis. The work involves streamlining BioBricks-AI repositories and public health databases into a vast graph database. This database will link chemicals, their genetic, molecular, and cellular disruptions, health hazards, adverse outcome pathways, testing methods, and other entities relevant to chemical safety and regulation. The National Toxicology Program's Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM) will use the resulting BioBricks-OKG for designing, collecting information, and evaluating "New Approach Methodology" (NAM) test guidelines.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.