Software systems are increasingly depending on data, particularly with the rising use of machine learning, and developers are looking for new sources of data. Open Data Ecosystems (ODE) is an emerging concept for data sharing under public licenses in software ecosystems, similar to Open Source Software (OSS). It has certain similarities to Open Government Data (OGD), where public agencies share data for innovation and transparency.

We aimed to explore open data ecosystems involving commercial actors. Thus, we organized five focus groups with 27 practitioners from 22 companies, public organizations, and research institutes. Based on the outcomes, we surveyed three cases of emerging ODE practice to further understand the concepts and to validate the initial findings. The main outcome is an initial conceptual model of ODEs’ value, intrinsics, governance, and evolution, and propositions for practice and further research.

We found that ODE must be value driven. Regarding the intrinsics of data, we found their type, meta-data, and legal frameworks influential for their openness. We also found the characteristics of ecosystem initiation, organization, data acquisition and openness be differentiating, which we advise research and practice to take into consideration.

软件系统越来越依赖于数据，特别是随着机器学习使用的增加，开发人员正在寻找新的数据来源。开放数据生态系统 (ODE) 是软件生态系统中在公共许可下共享数据的新兴概念，类似于开源软件 (OSS)。它与开放政府数据 (OGD) 有某些相似之处，在开放政府数据 (OGD) 中，公共机构共享数据以实现创新和透明度。

我们旨在探索涉及商业参与者的开放数据生态系统。因此，我们组织了五个焦点小组，有来自 22 家公司、公共组织和研究机构的 27 名从业者。根据结果​​，我们调查了三个新兴的 ODE 实践案例，以进一步了解这些概念并验证初步发现。主要成果是 ODE 的价值、内在、治理和演变的初始概念模型，以及用于实践和进一步研究的命题。

我们发现 ODE 必须是价值驱动的。关于数据的内在特性，我们发现它们的类型、元数据和法律框架对其开放性有影响。我们还发现生态系统启动、组织、数据获取和开放性的特征是差异化的，我们建议研究和实践考虑到这些特征。