Phase I IUCRC University of Maryland Baltimore County: Center for Accelerated Real Time Analytics (CARTA)

第一阶段 IUCRC 马里兰大学巴尔的摩县：加速实时分析中心 (CARTA)

• 批准号: 1747724
• 负责人: Karuna Joshi
• 金额: $ 75万
• 依托单位: University of Maryland Baltimore County
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1747724&HistoricalAwards=false
• 关键词: Phase; IUCRC; University; Maryland; Baltimore

Nearly every research field and industry sector is struggling with extracting useful information from massive and dynamic data in a timely way. Developing tools and technologies in this realm of real-time and accelerated analytics contributes to promoting the progress of science and to advancing the national prosperity and welfare. Success in this realm hinges on balancing fundamental research, technological know-how, and commercial market intelligence. To address this challenge, this project joins industry members with academic centers to conduct multidisciplinary science and research towards extracting value from massive and moving data and enabling better decision making of complex, dynamic data.The Center of Accelerated Real Time Analytics (CARTA) project explores the ways in which relatively high-risk fundamental developments can be leveraged to help organizations that have longer-term, more complex analytic needs. The focus of CARTA is on horizontal foundational technologies that would create an infrastructure capable of powering applications of national significance. In this context, at University of Maryland, Baltimore County (UMBC), the CARTA/UMBC site will focus on developing next generation cognitive/self-learning systems that will leverage high performance computing and quantum computing platforms, to facilitate real-time critical decision making. Having these technologies and systems will be key in achieving the goals of the overall CARTA center.The broader impact of the work of the CARTA center will be in addressing the future advanced, real-time analytics needs of the industry and society. The techniques developed by CARTA can be applied across industry sectors, including national security, healthcare, manufacturing, energy, and business intelligence. The fundamental research done at CARTA will be translated into technology developments, delivering practical solutions to hard problems. The ultimate success of this paradigm shift by the analytics industry will rest on the ability of CARTA universities to prepare experts to take advantage of the science and technologies to solve a variety of real-life applications.CARTA research may involve sensitive academic and industrial data along with public domain data. This data and resulting research outputs will be maintained using appropriate best practices for each type of data for a period of three years after the closing of CARTA. A central repository, suitably tagged for appropriate referencing and documentation, will be set up at https://carta.umbc.edu for maintaining the acquired and generated data from Center projects. Project results will be made available in response to approved user requests.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.

几乎每个研究领域和行业部门都在努力从大量动态数据中及时提取有用的信息。在实时和加速分析领域开发工具和技术有助于促进科学的进步，促进国家的繁荣和福利。这一领域的成功取决于平衡基础研究、技术知识和商业市场情报。为了应对这一挑战，该项目将行业成员与学术中心联合起来，开展多学科科学研究，从大量移动数据中提取价值，并对复杂、动态的数据做出更好的决策。加速实时分析中心（CARTA）项目探索了利用相对高风险的基础开发来帮助具有更长期、更复杂分析需求的组织的方法。CARTA的重点是横向基础技术，这些技术将创建能够为具有国家意义的应用提供动力的基础设施。在此背景下，马里兰大学巴尔的摩分校（UMBC）的CARTA/UMBC站点将专注于开发下一代认知/自我学习系统，该系统将利用高性能计算和量子计算平台，促进实时关键决策。拥有这些技术和系统将是实现整个CARTA中心目标的关键。CARTA中心工作的更广泛影响将是解决行业和社会未来先进的实时分析需求。CARTA开发的技术可以应用于各个行业，包括国家安全、医疗保健、制造业、能源和商业智能。CARTA所做的基础研究将转化为技术发展，为困难问题提供切实可行的解决方案。分析行业这种模式转变的最终成功将取决于CARTA大学培养专家利用科学技术解决各种现实应用的能力。CARTA研究可能涉及敏感的学术和工业数据以及公共领域数据。这些数据和由此产生的研究成果将在CARTA结束后的三年内对每一类数据采用适当的最佳做法加以保存。将在https://carta.umbc.edu建立一个中央储存库，为适当的参考和文档作适当标记，以维护从中心项目获得和生成的数据。项目结果将应核准的用户要求提供。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Automating Privacy Compliance Using Policy Integrated Blockchain

使用策略集成区块链自动化隐私合规

• DOI: 10.3390/cryptography3010007
• 发表时间: 2019
• 期刊: Cryptography
• 影响因子: 1.6
• 作者: Joshi, Karuna Pande;Banerjee, Agniva
• 通讯作者: Banerjee, Agniva

ViCLOUD: Measuring Vagueness in Cloud Service Privacy Policies and Terms of Services

ViCLOUD：衡量云服务隐私政策和服务条款的模糊性

• DOI: 10.1109/cloud49709.2020.00023
• 发表时间: 2020
• 期刊: 2020 IEEE 13th International Conference on Cloud Computing (CLOUD
• 作者: Kotal, Anantaa;Joshi, Karuna Pande;Joshi, Anupam
• 通讯作者: Joshi, Anupam

An Integrated Knowledge Graph to Automate Cloud Data Compliance

用于自动化云数据合规性的集成知识图

• DOI: 10.1109/access.2020.3008964
• 发表时间: 2020
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Joshi, Karuna Pande;Elluri, Lavanya;Nagar, Ankur
• 通讯作者: Nagar, Ankur

A Semantic Approach for Automating Knowledge in Policies of Cyber Insurance Services

网络保险服务政策知识自动化的语义方法

• DOI: 10.1109/icws.2019.00018
• 发表时间: 2019
• 期刊: 2019 IEEE International Conference on Web Services (ICWS
• 作者: Joshi, Ketki;Pande Joshi, Karuna;Mittal, Sudip
• 通讯作者: Mittal, Sudip