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Governments are one of the largest producers and collectors of data in many different domains. As one major aim of open government data initiatives is the release of social and commercial value, we here explore existing processes of value creation on government data. We identify the dimensions that impact, or are impacted by value creation, and distinguish between the different value creating roles and participating stakeholders. We propose the use of Linked Data as an approach to enhance the value creation process, and provide a Value Creation Assessment Framework to analyse the resulting impact

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A worldwide movement towards the publication of Open Government Data is taking place, and budget data is one of the key elements pushing this trend. Its importance is mostly related to transparency, but publishing budget data, combined with other actions, can also improve democratic participation, allow comparative analysis of governments and boost data-driven business. However, the lack of standards and common evaluation criteria still hinders the development of appropriate tools and the materialization of the appointed benefits. In this paper, we present a model to analyse government initiatives to publish budget data. We identify the main features of these initiatives with a double objective: (i) to drive a structured analysis, relating some dimensions to their possible impacts, and (ii) to derive characterization attributes to compare initiatives based on each dimension. We define use perspectives and analyse some initiatives using this model. We conclude that, in order to favour use perspectives, special attention must be given to user feedback, semantics standards and linking possibilities.

Data is quite popularly considered to be the new oil since it has become a valuable commodity. This has resulted in many entities and businesses that hoard data with the aim of exploiting it. Yet, the 'simple' exploitation of data results in entities who are not obtaining the highest benefits from the data, which as yet is not considered to be a fully-fledged enterprise asset. Such data can exist in a duplicated, fragmented, and isolated form, and the sheer volume of available data further complicates the situation. Issues such as the latter highlight the need for value-based data governance, where the management of data assets is based on the quantification of the data value. This quantification will provide an opportunity for evidence-based approaches to data governance. This paper has the purpose of creating awareness and further understanding of challenges that result in untapped data value. We identify niches in related work, and through our experience with businesses who use data assets, we here analyse four main context-independent challenges that hinder entities from achieving the full benefits of using their data. This will aid in the advancement of the field of value-driven data governance and therefore directly affect data asset exploitation.

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