With the explosion of “big data” in the past decade, exploring and mining the value hidden in the data has already generated a lot of innovative applications, especially the recent advances of AI applications. The data governance, including activities of data creation, sharing, exchange, management, analytics, tracing, and accounting, has drawn a lot of attentions. Services computing establishes the foundation of current data governance, typically in a centralized fashion, e.g., the cloud-based storage services and analytic services. However, the potential values of big data distributed on the Internet are far away from being adequately explored. Considering the infrastructure revolution made by the blockchain, in this position article, we try to rethink a new data governance fashion that is built upon the blockchain-based decentralized services computing paradigm. The core principle is that data owners are able to publish their data as a set of services that can be deployed independently from the application systems where the data were born. Meanwhile, data owners can define service rules/policies where their data should be stored and how the data can be shared, and keep governing the whole lifecycle record of how their data are actually used. Similar to existing services computing paradigm, data users can search, discover, integrate, and analyze the data in a decentralized fashion. With this perspective, we try to discuss some key insights and enumerate several related new technologies and open challenges, in terms of programmability, interoperability, and intelligence.

中文翻译：

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大数据治理的新兴去中心化服务计算范式：立场文件

随着过去十年“大数据”的爆发，探索和挖掘隐藏在数据中的价值已经产生了很多创新应用，尤其是人工智能应用的最新进展。数据治理，包括数据的创建、共享、交换、管理、分析、追溯和核算等活动，引起了广泛关注。服务计算建立了当前数据治理的基础，通常以集中的方式，例如，基于云的存储服务和分析服务。然而，分布在互联网上的大数据的潜在价值还远未得到充分挖掘。考虑到区块链带来的基础设施革命，在这篇立场文章中，我们试图重新思考一种建立在基于区块链的去中心化服务计算范式之上的新数据治理方式。核心原则是数据所有者能够将他们的数据作为一组服务发布，这些服务可以独立于数据诞生的应用系统进行部署。同时，数据所有者可以定义他们的数据应该存储在哪里以及如何共享数据的服务规则/策略，并继续管理他们的数据实际如何使用的整个生命周期记录。类似于现有的服务计算范式，数据用户可以以去中心化的方式搜索、发现、集成和分析数据。从这个角度出发，我们尝试讨论一些关键的见解，并在可编程性、互操作性和智能方面列举几个相关的新技术和开放挑战。