SGER: Exploratory Investigation of Modular Ontology Languages
SGER:模块化本体语言的探索性研究
基本信息
- 批准号:0639230
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2006
- 资助国家:美国
- 起止时间:2006-09-01 至 2009-02-28
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Many distributed data and knowledge base applications call for a structured approach to collaborative construction of large ontologies (conceptualizations of objects, properties, and relationships between objects of interest in specific domains). This high risk, potentially high impact research is aimed at addressing the need of such applications for ontology languages, distributed reasoning algorithms, and software tools that support rapid collaborative assembly and use of complex ontologies through partial and selective reuse of independently created ontology modules. A family of description logics (DL) based modular ontology languages, namely Package-Based Description logics (P-DL) being developed by the researchers to explore the language features, syntax, and semantics of package-based partial order ontologies (PPO). The resulting tools will be evaluated in the context of collaborative construction of animal trait (phenotype) ontologies needed for comparative genomics. Anticipated results of the research include open source software for rapid, collaborative construction of PPO (and eventually, P-DL ontologies). The resulting tools can potentially transform distributed data and knowledge base applications in the same way in which the World-Wide Web transformed the construction, sharing and use of hyperlinked documents and Wiki has transformed encyclopedia construction. Broader impacts of this research include enhanced opportunities for research-based training of graduate and undergraduate students, enhanced interdisciplinary collaborations, increased participation of under-represented groups, and engagement of the broader scientific community in developing and using increasingly sophisticated collaborative ontology development tools. The project Web site (http://www.cs.iastate.edu/~honavar/ailab/projects/modularontologies.html) provides access to the information on the project, publications and prototype software tools.
许多分布式数据和知识库应用程序需要一个结构化的方法来协作构建大型本体(概念化的对象,属性和对象之间的关系,在特定的领域)。 这种高风险,潜在的高影响力的研究,旨在解决这样的本体语言,分布式推理算法和软件工具,支持快速协作组装和使用复杂的本体,通过部分和选择性重用独立创建的本体模块的应用程序的需要。一个基于描述逻辑(DL)的模块化本体语言,即基于包的描述逻辑(P-DL)正在开发的研究人员探索的语言功能,语法和语义的基于包的偏序本体(PPO)。所产生的工具将在合作的背景下进行评估, 构建比较基因组学所需的动物性状(表型)本体。该研究的预期成果包括用于PPO(以及最终的P-DL本体)的快速协作构建的开源软件。由此产生的工具可以潜在地改变分布式数据和知识库应用程序,就像万维网改变了超链接文档的构建、共享和使用,维基改变了百科全书的构建一样。这项研究的更广泛的影响包括增强研究生和本科生的研究培训机会,加强跨学科合作,增加代表性不足的群体的参与,以及更广泛的科学界参与开发和使用日益复杂的协作本体开发工具。该项目的网址(http://www.cs.iastate.edu/modulhonavar/ailab/projects/modularontologies.html)提供关于该项目的信息、出版物和原型软件工具。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Vasant Honavar其他文献
Neural network design and the complexity of learning, by J. Stephen Judd. Cambridge, MA: MIT Press, 1990
- DOI:
10.1007/bf00993255 - 发表时间:
1992-06-01 - 期刊:
- 影响因子:2.900
- 作者:
Vasant Honavar - 通讯作者:
Vasant Honavar
Machine-learning guided biophysical model development: application to ribosome catalysis
- DOI:
10.1016/j.bpj.2021.11.2053 - 发表时间:
2022-02-11 - 期刊:
- 影响因子:
- 作者:
Yang Jiang;Justin Petucci;Nishant Soni;Vasant Honavar;Edward O'Brien - 通讯作者:
Edward O'Brien
Book Review:Neural Network Design and the Complexity of Learning, by J. Stephen Judd. Cambridge, MA: MIT Press, 1990
- DOI:
10.1023/a:1022680813848 - 发表时间:
1992-06-01 - 期刊:
- 影响因子:2.900
- 作者:
Vasant Honavar - 通讯作者:
Vasant Honavar
Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach
- DOI:
10.1186/1471-2105-8-284 - 发表时间:
2007-08-03 - 期刊:
- 影响因子:3.300
- 作者:
Carson Andorf;Drena Dobbs;Vasant Honavar - 通讯作者:
Vasant Honavar
A practical guide to machine learning interatomic potentials – Status and future
机器学习原子间势的实用指南——现状与未来
- DOI:
10.1016/j.cossms.2025.101214 - 发表时间:
2025-03-01 - 期刊:
- 影响因子:13.400
- 作者:
Ryan Jacobs;Dane Morgan;Siamak Attarian;Jun Meng;Chen Shen;Zhenghao Wu;Clare Yijia Xie;Julia H. Yang;Nongnuch Artrith;Ben Blaiszik;Gerbrand Ceder;Kamal Choudhary;Gabor Csanyi;Ekin Dogus Cubuk;Bowen Deng;Ralf Drautz;Xiang Fu;Jonathan Godwin;Vasant Honavar;Olexandr Isayev;Brandon M. Wood - 通讯作者:
Brandon M. Wood
Vasant Honavar的其他文献
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{{ truncateString('Vasant Honavar', 18)}}的其他基金
Collaborative Research: RI: III: SHF: Small: Multi-Stakeholder Decision Making: Qualitative Preference Languages, Interactive Reasoning, and Explanation
协作研究:RI:III:SHF:小型:多利益相关者决策:定性偏好语言、交互式推理和解释
- 批准号:
2225824 - 财政年份:2022
- 资助金额:
-- - 项目类别:
Standard Grant
III: Small: Predictive Modeling from High-Dimensional, Sparsely and Irregularly Sampled, Longitudinal Data
III:小:根据高维、稀疏和不规则采样的纵向数据进行预测建模
- 批准号:
2226025 - 财政年份:2022
- 资助金额:
-- - 项目类别:
Standard Grant
AI Institute: Planning: Institute for AI-Enabled Materials Discovery, Design, and Synthesis
人工智能研究所:规划:人工智能材料发现、设计和合成研究所
- 批准号:
2020243 - 财政年份:2020
- 资助金额:
-- - 项目类别:
Standard Grant
EAGER: Interpreting Black-Box Predictive Models Through Causal Attribution
EAGER:通过因果归因解释黑盒预测模型
- 批准号:
2041759 - 财政年份:2020
- 资助金额:
-- - 项目类别:
Standard Grant
BD Spokes: SPOKE: NORTHEAST: Collaborative Research: Integration of Environmental Factors and Causal Reasoning Approaches for Large-Scale Observational Health Research
BD 发言:发言:东北:合作研究:大规模观察健康研究的环境因素和因果推理方法的整合
- 批准号:
1636795 - 财政年份:2017
- 资助金额:
-- - 项目类别:
Standard Grant
EAGER: Towards a Computational Infrastructure for Analysis of Sensitive Data
EAGER:建立用于分析敏感数据的计算基础设施
- 批准号:
1551843 - 财政年份:2015
- 资助金额:
-- - 项目类别:
Standard Grant
SHF:Large:Collaborative Research: Inferring Software Specifications from Open Source Repositories by Leveraging Data and Collective Community Expertise
SHF:大型:协作研究:利用数据和集体社区专业知识从开源存储库推断软件规范
- 批准号:
1518732 - 财政年份:2015
- 资助金额:
-- - 项目类别:
Standard Grant
ITR: Algorithms and Software for Knowledge Acquisition from Heterogeneous Distributed Data
ITR:从异构分布式数据获取知识的算法和软件
- 批准号:
0219699 - 财政年份:2002
- 资助金额:
-- - 项目类别:
Continuing Grant
RIA: Constructive Neural Network Learning Algorithms for Pattern Classification
RIA:用于模式分类的构造性神经网络学习算法
- 批准号:
9409580 - 财政年份:1994
- 资助金额:
-- - 项目类别:
Continuing Grant
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