BD Spokes: SPOKE: NORTHEAST: Collaborative: A Licensing Model and Ecosystem for Data Sharing

BD Spokes：SPOKE：NORTHEAST：协作：数据共享的许可模型和生态系统

• 批准号: 1947440
• 负责人: Tim Kraska
• 金额: $ 27.09万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1947440&HistoricalAwards=false
• 关键词: BD; Spokes; SPOKE; NORTHEAST; Collaborative

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 (requiring e.g., 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, which are both disconnected from what the actual stakeholders aim to do and fraught as both sides struggle with the implications and possibilities of modern security, privacy, and data sharing techniques. Worse, fear of missing a loophole in how the data might be (mis)used often prevents many data sharing efforts from even getting off the ground. 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 and (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 of 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.

共享数据集可以为行业、研究人员和非营利组织带来巨大的互惠互利。例如，公司可以从大学研究人员探索其数据集并做出发现的事实中获利，这有助于公司改善其业务。与此同时，研究人员一直在寻找现实世界的数据集，以证明他们新开发的技术在实践中有效。不幸的是，许多在工业界和学术界不同利益相关者之间共享相关数据集的尝试都失败了，或者需要大量投资才能实现数据共享。一个主要障碍是数据的使用方式通常受到禁止性限制（例如要求执行法律条款或其他政策、处理数据隐私问题等）。如今，为了执行这些要求，律师通常会参与每份合同条款的谈判。这种创建个人数据共享合同的过程最终会陷入旷日持久的谈判，这种情况并不罕见，这种谈判既与实际利益相关者的目标脱节，又因双方都在与现代安全、隐私、和数据共享技术。更糟糕的是，担心错过数据可能被（滥用）使用的漏洞往往会阻碍许多数据共享工作的开展。为了应对这些挑战，我们新的数据共享辐条将使数据提供商能够轻松共享数据，同时对数据的使用施加限制。这项工作有两个关键组成部分：(1) 创建数据许可模型，以促进在不同组织之间共享不一定开放或免费的数据；(2) 开发原型数据共享软件平台 ShareDB，该平台强制执行条款和限制已开发的许可证。我们相信这些努力将对数据共享的方式产生变革性影响。通过将数据从个人和单一组织的孤岛转移到更广泛的社会手中，我们可以解决许多具有社会重大意义的问题。这种新的数据共享辐条将使数据提供者能够轻松共享数据，同时对数据的使用施加限制。如今已经存在许多提供数据集访问的服务和平台。然而，这些平台通常提倡完全开放的访问，并且没有解决处理专有数据时出现的上述问题。因此，这项工作包含三个关键组成部分：(1) 创建数据许可模型，以促进不同组织之间不一定开放或免费的数据共享；(2) 开发原型数据共享软件平台 ShareDB，该平台强制执行条款和所开发许可证的限制，以及（3）开发和集成相关元数据，这些元数据将伴随在不同许可证下共享的数据集，使它们易于搜索和解释。为了确保开发的工具和许可证有用，该项目将组建东北数据共享小组，由许多不同的利益相关者组成，以使许可模型在许多应用领域（例如健康和金融）得到广泛接受和使用。该提案的智力价值在于设计一个许可模型和一个被广泛接受并可在许多不同领域用作模板的数据共享平台。虽然还有其他努力来实现数据共享（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强制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），并且还提供工具来确保敏感信息的数据共享安全。我们建议研究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、访问可撤销以及维护访问控制和审核日志的能力。

项目成果

Towards instance-optimized data systems

• DOI: 10.14778/3476311.3476392
• 发表时间: 2021-07
• 期刊: Proc. VLDB Endow.
• 作者: Tim Kraska

Poly'19 Workshop Summary: GDPR

Poly19 研讨会摘要：GDPR

• DOI: 10.1145/3444831.3444842
• 发表时间: 2020
• 期刊: ACM SIGMOD Record
• 作者: Stonebraker, Michael;Mattson, Timothy;Kraska, Tim;Gadepally, Vijay
• 通讯作者: Gadepally, Vijay