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<p>Data sharing is central to various applications such as fraud detection, ad matching, and improving patient care. However, each solution to data sharing is bespoke and cost-intensive, hampering value generation. We identify the lack of abstractions to control data release as the culprit of the problem. For example, it is common to have constraints on whether to share data that depend on the result of sharing, and evaluating these constraints requires sharing in the first place, leading to a standstill. To help people build solutions to a wide variety of data sharing applications, we propose <i>programmable dataflows</i>, which consist of two components. The first component is an abstraction, the <i>contract</i>, which agents use to communicate the intent of a data sharing action and evaluate its consequences before the dataflow takes place. This helps agents control the release of their data. The second component is a <i>contract programming model</i> (CPM), which allows agents to program data sharing applications catered to each problem’s needs with the contract abstraction. We describe how to deploy those applications on a data escrow to ensure data remains protected from unintended data releases. Our evaluation shows 1) the contract abstraction permits representing a wide range of sharing problems, 2) CPM permits writing programs for complex data sharing problems and 3) quantitatively, our improvements to CPM make sharing programs run efficiently.</p>

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Programmable Dataflows: Abstraction and Programming Model for Data Sharing

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月3日

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  • Siyuan Xia,
  • Chris Zhu,
  • Tapan Srivastava,
  • Bridget Fahey,
  • Raul Castro Fernandez

摘要

Data sharing is central to various applications such as fraud detection, ad matching, and improving patient care. However, each solution to data sharing is bespoke and cost-intensive, hampering value generation. We identify the lack of abstractions to control data release as the culprit of the problem. For example, it is common to have constraints on whether to share data that depend on the result of sharing, and evaluating these constraints requires sharing in the first place, leading to a standstill. To help people build solutions to a wide variety of data sharing applications, we propose programmable dataflows, which consist of two components. The first component is an abstraction, the contract, which agents use to communicate the intent of a data sharing action and evaluate its consequences before the dataflow takes place. This helps agents control the release of their data. The second component is a contract programming model (CPM), which allows agents to program data sharing applications catered to each problem’s needs with the contract abstraction. We describe how to deploy those applications on a data escrow to ensure data remains protected from unintended data releases. Our evaluation shows 1) the contract abstraction permits representing a wide range of sharing problems, 2) CPM permits writing programs for complex data sharing problems and 3) quantitatively, our improvements to CPM make sharing programs run efficiently.