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Using a domain-specific modeling language for analyzing harmonizing and interfering public and private sector goals: A scenario in the context of open data for weather forecasting

机译:使用特定领域的建模语言来分析协调和干扰公共和私营部门的目标:开放数据用于天气预报的场景

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The opening of data by public organizations can result in innovations and new business models in the private sector. Yet, the public and private sectors may have different and sometimes interfering objectives. In this paper, we analyze the goals of an open data business model for weather forecasting using the multi-perspective goal modelling language GoalML. The public and private sectors partly share similar goals, but creating public value was found to be interfering (to some extent) with the private sector objective of making profit. One of the values of GoalML is that it clearly shows harmonizing and interfering goals. The interfering goals are one of the explanations for a slow adoption of open data. Mechanisms need to be developed to deal with them.
机译:公共组织开放数据可以在私营部门带来创新和新的商业模式。但是,公共和私营部门可能有不同的目标,有时甚至是相互干扰的目标。在本文中,我们使用多角度目标建模语言GoalML分析了用于天气预报的开放数据业务模型的目标。公共部门和私营部门部分地具有相同的目标,但发现创造公共价值在一定程度上干扰了私营部门的盈利目标。 GoalML的价值之一是,它清楚地表明了协调和干扰目标。干扰的目标是缓慢采用开放数据的原因之一。需要开发处理这些问题的机制。

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