基于开放数据和api的数据科学服务的挑战和治理解决方案

Juha-Pekka Joutsenlahti, Timo Lehtonen, M. Raatikainen, Elina Kettunen, T. Mikkonen
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引用次数: 4

摘要

越来越普遍的开放数据和开放应用程序编程接口(api),以及数据科学(如人工智能(AI),特别是机器学习(ML))的进步,创造了通过组合来自不同来源的数据来构建新服务的机会。在这份经验报告中,我们描述了我们在芬兰和瑞典海上交通领域的开放数据的第一手经验,并确定了新服务的技术机会。我们列举了我们在开放数据应用中遇到的五个挑战:相关数据、历史数据、许可、运行时质量和API发展。这些挑战影响业务模型和技术实现。我们将讨论如何通过对提供的开放api和数据进行更好的治理实践来缓解这些挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges and Governance Solutions for Data Science Services based on Open Data and APIs
Increasingly common open data and open application programming interfaces (APIs) together with the progress of data science – such as artificial intelligence (AI) and especially machine learning (ML) – create opportunities to build novel services by combining data from different sources. In this experience report, we describe our firsthand experiences on open data and in the domain of marine traffic in Finland and Sweden and identified technological opportunities for novel services. We enumerate five challenges that we have encountered with the application of open data: relevant data, historical data, licensing, runtime quality, and API evolution. These challenges affect both business model and technical implementation. We discuss how these challenges could be alleviated by better governance practices for provided open APIs and data.
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