BD Spokes: SPOKE: NORTHEAST: Collaborative: A Licensing Model and Ecosystem for Data Sharing
BD Spokes: SPOKE: NORTHEAST: Collaborative: A Licensing Model and Ecosystem for Data Sharing
批准号:
1636766
负责人:
Samuel Madden
金额:
$44.4万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2021-12-31
中文摘要
数据集的共享可以为行业、研究人员和非营利组织提供巨大的互惠利益。例如,公司可以从大学研究人员探索他们的数据集和发现中获利,这有助于公司改善业务。与此同时,研究人员一直在寻找真实世界的数据集,以证明他们新开发的技术在实践中是有效的。不幸的是,在工业界和学术界的不同利益相关者之间共享相关数据集的许多尝试都失败了,或者需要大量投资才能使数据共享成为可能。一个主要的障碍是,数据的使用方式往往受到禁止性的限制(例如,要求执行法律条款或其他政策,处理数据隐私问题等)。今天,为了执行这些要求,律师通常会参与每项合同条款的谈判。这种为数据共享创建个人合同的过程最终以旷日持久的谈判告终,因为双方都在为现代安全、隐私和数据共享技术的影响和可能性而斗争,这并不罕见。更糟糕的是,由于担心错过数据可能被(错误)使用的漏洞,许多数据共享工作甚至无法开始。为了应对这些挑战,我们的新数据共享协议将使数据提供商能够轻松地共享数据,同时对数据的使用施加约束。这项工作有两个关键组成部分:(1)为数据创建一个许可模型,以促进在不同组织之间共享不一定是开放或免费的数据;(2)开发一个原型数据共享软件平台ShareDB,该平台执行已开发的许可的条款和限制。我们相信这些努力将对数据共享的方式产生变革性的影响。通过将数据从个人和单个组织的孤岛转移到更广泛的社会手中,我们可以解决许多重大的社会问题。这个新的数据共享辐条将使数据提供者能够轻松地共享数据,同时对数据的使用施加约束。目前已经存在许多提供访问数据集的服务和平台。然而,这些平台通常促进完全开放的访问,并没有解决在处理专有数据时出现的上述问题。因此,这项工作有三个关键组成部分:(1)为数据创建一个许可模型,以促进不同组织之间不一定开放或免费的数据共享;(2)开发一个原型数据共享软件平台ShareDB,该平台执行已开发许可的条款和限制;(3)开发和集成在不同许可下共享数据集的相关元数据,使其易于搜索和解释。为确保开发的工具和许可证有用,该项目将组建由许多不同利益攸关方组成的东北数据共享小组,以使许可模式在许多应用领域(例如,卫生和金融)得到广泛接受和使用。这个建议的智力价值在于设计了一个许可模型和一个数据共享平台,它被广泛接受,并在许多不同的领域中作为模板可用。虽然也存在其他实现数据共享的努力(例如,知识共享),但它们关注的是数据所有者愿意在互联网上公开共享数据的情况。这种许可模式和生态系统是不同的,因为它允许数据所有者执行数据共享协议中规定的某些要求(例如,允许谁访问数据),并且还提供了使敏感信息的数据共享安全的工具。我们建议调查的许可证和软件将使组织更容易向适当的组织开放其数据,同时保持确保数据受到保护、访问是可撤销的、访问控制和审计日志得到维护的能力。
英文摘要
Sharing of data sets can provide tremendous mutual benefits for industry, researchers and nonprofit organizations. For example, companies can profit from the fact that university researchers explore their data sets and make discoveries, which help the company to improve their business. At the same time, researchers are always on the search for real world data sets to show that their newly developed techniques work in practice. Unfortunately, many attempts to share relevant data sets between different stakeholders in industry and academia fail or require a large investment to make data sharing possible. A major obstacle is that data often comes with prohibitive restrictions on how it can be used (e.g., requiring the enforcement of legal terms or other policies, handling data privacy issues, etc.). In order to enforce these requirements today, lawyers are usually involved in negotiation the terms of each contract. It is not atypical that this process of creating an individual contract for data sharing ends up in protracted negotiations, as both sides struggle with the implications and possibilities of modern security, privacy, and data sharing techniques. Worse, fears of missing a loophole in how the data might be (mis)used often prevents many data sharing efforts from even getting started. To address these challenges, our new data sharing spoke will enable data providers to easily share data while enforcing constraints on the use of the data. This effort has two key components:(1) Creating a licensing model for data that facilitates sharing data that is not necessarily open or free between different organizations and (2) Developing a prototype data sharing software platform, ShareDB, which enforces the terms and restrictions of the developed licenses. We believe these efforts will have a transformative impact on how data sharing takes place. By moving data out of the silos of individuals and single organizations and into the hands of broader society, we can tackle many societally significant problems.This new data sharing spoke will enable data providers to easily share data while enforcing constraints on the use of the data. Many services and platforms that provide access to data sets exist already today. However, these platforms generally promote completely open access and do not address the aforementioned issues that arise when dealing with proprietary data. Thus, the effort has three key components: (1) Creating a licensing model for data that facilitates sharing data that is not necessarily open or free between different organizations, (2) developing a prototype data sharing software platform, ShareDB, which enforces the terms and restrictions of the developed licenses, and (3) developing and integrating relevant metadata that will accompany the datasets shared under the different licenses, making them easily searchable and interpretable. To ensure that the developed tools and licenses are useful, the project will form the Northeast Data Sharing Group, comprising many different stakeholders to make the licensing model widely accepted and usable in many application domains (e.g., health and finance). The intellectual merit of this proposal is to design a licensing model and a data sharing platform that is widely accepted and usable as a template in many different domains. While there exist other efforts to enable data sharing (e.g., Creative Commons), they focus on the case where the data owner is willing to openly share the data on the Internet. This licensing model and the ecosystem is different since it allows data owners to enforce certain requirements stated in a data sharing agreement (e.g., on who is allowed to access the data) and also provides tools to make data sharing of sensitive information safe. The licenses and software we propose to investigate will make it easier for organizations to open up their data to the appropriate organizations, while maintaining the ability to ensure it is protected, that access is revocable, and that access controls and audit logs are maintained.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
ATLANTIC: Making Database Differentially Private and Faster with Accuracy Guarantee
ATLANTIC:使数据库具有差分隐私性且速度更快且保证准确性
DOI:
10.14778/3476311.3476337
发表时间:
2021
期刊:
Proceedings of the International Conference on Very Large Data Bases
影响因子:
--
作者:
[Cao, Lei, Xiao, Dongqing, Yan, Yizhou, Madden, Samuel, Li, Guoliang]
通讯作者:
Li, Guoliang
DOI:
10.1145/3329859.3329877
发表时间:
2019-03
期刊:
Proceedings of the Second International Workshop on Exploiting Artificial Intelligence Techniques for Data Management
影响因子:
--
作者:
[R. Fernandez;S. Madden]
通讯作者:
R. Fernandez;S. Madden
DOI:
--
发表时间:
2020
期刊:
影响因子:
--
作者:
[E. Rezig;Lei Cao;Giovanni Simonini;Maxime Schoemans;S. Madden;N. Tang;M. Ouzzani;M. Stonebraker]
通讯作者:
E. Rezig;Lei Cao;Giovanni Simonini;Maxime Schoemans;S. Madden;N. Tang;M. Ouzzani;M. Stonebraker
Collaborative Research: Elements: A Self-tuning Anomaly Detection Service
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批准号:2103799
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项目类别:Standard Grant
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资助金额:$34.0万
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财政年份:2021
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负责人:Samuel Madden
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依托单位:
III: Medium: Massively Parallel Data Analytics on Heterogeneous Architectures
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批准号:1763434
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项目类别:Continuing Grant
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资助金额:$120.0万
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财政年份:2018
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负责人:Samuel Madden
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依托单位:
III: Medium: Collaborative Research: DataHub - A Collaborative Dataset Management Platform for Data Science
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批准号:1513443
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项目类别:Continuing Grant
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资助金额:$33.33万
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负责人:Samuel Madden
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依托单位:
ACM SIGMOD 2012 Student Programming Contest: A Multidimensional Indexing System
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批准号:1235666
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项目类别:Standard Grant
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资助金额:$2.5万
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财政年份:2012
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负责人:Samuel Madden
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依托单位:
III: Medium: Scalable and Secure Database as a Service
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批准号:1065219
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项目类别:Continuing Grant
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资助金额:$120.0万
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财政年份:2011
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负责人:Samuel Madden
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依托单位:
SIGMOD 2011 Programming Contest
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批准号:1129526
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项目类别:Standard Grant
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资助金额:$3.0万
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财政年份:2011
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负责人:Samuel Madden
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依托单位:
III: Large: Collaborative Research: SciDB - An Array Oriented Data Management System for Massive Scale Scientific Data
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批准号:1111371
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项目类别:Standard Grant
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资助金额:$55.62万
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财政年份:2011
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负责人:Samuel Madden
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依托单位:
2010 SIGMOD Programming Contest
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批准号:1037986
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项目类别:Standard Grant
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资助金额:$2.3万
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财政年份:2010
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负责人:Samuel Madden
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依托单位:
Collaborative Research: A Comparative Study of Approaches to Cluster-Based Large Scale Data Analysis
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批准号:0844013
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项目类别:Standard Grant
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资助金额:$15.12万
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财政年份:2009
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负责人:Samuel Madden
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依托单位:
2009 SIGMOD Programming Contest
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批准号:0848727
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项目类别:Standard Grant
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资助金额:$4.5万
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财政年份:2008
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负责人:Samuel Madden
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依托单位:
Collaborative Research: IDBR: VoxNet- A Deployable Bioacoustic Sensor Network
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批准号:0754662
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项目类别:Continuing Grant
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资助金额:$13.5万
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财政年份:2008
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负责人:Samuel Madden
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依托单位:
III-COR - ChunkyStore: Physical Database Design for Next-Generation Databases
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批准号:0704424
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项目类别:Standard Grant
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资助金额:$81.9万
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负责人:Samuel Madden
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依托单位:
CSR-CSI: XStream, a Distributed Stream Processor for Heterogeneous Sensor Systems
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批准号:0720079
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项目类别:Continuing Grant
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资助金额:$35.0万
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财政年份:2007
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负责人:Samuel Madden
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依托单位:
CAREER: MACAQUE - Managing Ambiguity and Complexity in Acquisitional QUery Environments
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批准号:0448124
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项目类别:Continuing Grant
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资助金额:$0.0万
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财政年份:2005
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负责人:Samuel Madden
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依托单位:
CSR-EHS: Collaborative Research: A General, Efficient and Robust Platform for Enabling Control Applications in Sensor Networks
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批准号:0509261
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项目类别:Standard Grant
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资助金额:$20.0万
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财政年份:2005
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负责人:Samuel Madden
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依托单位:
海外基金