Open-Source Toolkit for Knowledge-Based Querying of Time-Oriented Data

描述(由申请人提供)： 在涉及生物途径、疾病进展和治疗结果的研究中，研究人员在确定他们收集的时间信息之间的重要关系方面面临着特别困难。目前，研究人员在大量观测和实验数据中发现相关时间模式的能力有限，因为缺乏广泛可用的、即用即用的工具，这些工具结合了时间和领域知识。为了应对这些挑战，我们提出了一种新的方法来查询和抽象时态模式，该方法集成了数据、本体、规则和形式时态语义。我们的方法被称为语义查询增强的Web规则语言(SQWRL)，是语义Web的W3C标准和Protigi环境的扩展-Protigi环境是用于指定本体和知识库的最广泛使用的、免费提供的开源软件。拟议的查询工具包称为SQWRL-TK，将为调查人员提供一个集成的、可扩展的框架，用于领域驱动的时间现象调查。我们努力的目标是开发一套开放源码工具，该工具可以灵活地集成基于知识的方法来转换、检索和抽象时态数据。我们的具体目标是(1)实现一个可扩展的、可重用的软件体系结构，用于使用本体和规则来查询和抽象时态模式；(2)开发一个数据映射工具，该工具可以将存储在现有关系数据库中的面向时间的数据映射到适合于基于知识的查询的时态本体；以及(3)创建一个查询启发工具，它可以允许研究人员制定与领域相关的时态模式来进行数据提取和检查这些查询的结果。我们将在与调查小组的持续合作中开发和评估这些工具的使用，这些调查小组在艾滋病毒耐药性研究和免疫紊乱试验管理领域拥有完善的数据库。我们计划进行反复的软件测试和优化过程，以确保准确性和性能。我们将创建一个网站来传播这些工具(作为protigi的开源插件)。在研究人员中广泛使用这种一般方法，可以极大地发现隐藏在生物医学数据库中以时间为导向的数据之间的科学关联和模式。

DESCRIPTION (provided by applicant): In research involving biological pathways, disease progression, and treatment outcomes, investigators face particular difficulties in identifying important relationships among the temporal information they collect. Currently, investigators have limited abilities to discover relevant temporal patterns among volumes of observational and experimental data based, because of the lack of widely available, ready-to-use tools that incorporate temporal and domain knowledge. To address these challenges, we propose a novel method for querying and abstracting temporal patterns that integrates data, ontologies, rules, and formal temporal semantics. Our approach, called Semantic Query-enhanced Web Rule Language (SQWRL), is an extension to W3C standards for the Semantic Web and to the Protigi environment-the mostly widely used, freely available, open-source software for specifying ontologies and knowledge bases. The proposed querying toolkit, called SQWRL-TK, will provide investigators an integrated, scalable framework for domain-driven investigation of temporal phenomena. The goal of our efforts is to develop a set of open-source tools that flexibly integrates knowledge-based methods for the transformation, retrieval, and abstraction of temporal data. Our specific aims are (1) to implement a scalable, reusable software architecture for the querying and abstraction of temporal patterns using ontologies and rules; (2) to develop a data-mapping tool that can map time-oriented data stored in existing relational databases into a temporal ontology suitable for knowledge- based querying; and (3) to create a query-elicitation tool that can allow investigators to formulate domain- relevant temporal patterns for data extraction and inspect the results of those queries. We will develop and evaluate the use of these tools in ongoing collaborations with investigative teams who have well-developed data repositories in the areas of HIV drug resistance research and immune disorder trial management. We plan to undertake a reiterative process of software testing and optimization to ensure accuracy and performance. We will create a website to disseminate these tools (as open-source plug ins to Protigi). The widespread use of such general methods among investigators may greatly enable the discovery of scientifically relevant associations and patterns hidden among time-oriented data within biomedical databases.