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

Abstract

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.