Although the open Government data (OGD) movement is flourishing globally, the large-scale utilization and value creation of OGD has not really opened yet, which is far from the goal and expectation of dataopenness. G...
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Although the open Government data (OGD) movement is flourishing globally, the large-scale utilization and value creation of OGD has not really opened yet, which is far from the goal and expectation of dataopenness. Guiding the practice of OGD with the concept of "ecosystem" can help promote the efficient utilization and value realization of data. From the perspective of the whole process of OGD utilization, ecosystems have various types of ecological characteristics such as data flow, information expression and value realization. To this end, this paper proposes a new perspective of viewing OGD ecosystems across data, information and business based on the theories of supernetworks, data value chains, information ecosystems and business ecosystems, and further explores the ecosystems through a case study in Guizhou, China. We conclude that the hierarchical division of OGD ecosystems as a whole is clearer, and the focus of each layer is more focused;the cross-level dynamics mechanism of the ecosystem, and the information transmission mechanism assumed by the information ecosystem make the three layers interact with each other;and the different actors play different roles in the three layers and occupy different ecological position. This study provides useful reference for OGD practice and also expands new ideas and space for theoretical research and application practice of the ecosystem approach.
open government data (OGD) can enable outbound open innovation (OI) that is beneficial to society. However, innovation barriers hinder OGD users from generating value. While previous studies have detailed a large numb...
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open government data (OGD) can enable outbound open innovation (OI) that is beneficial to society. However, innovation barriers hinder OGD users from generating value. While previous studies have detailed a large number of such barriers, little is known of how different types of OGD users are affected, and when the barriers appear in their innovation processes. To this end, this paper describes a case study of distributed service development in the Swedish public transport sector. The contribution to extant research is twofold. Firstly, based on an inductive analysis, three OGD user archetypes are proposed: employees, entrepreneurs and hobbyists. Secondly, the study finds that the significance of distinct innovation barriers varies across phases of the services' lifecycles and depending on the OGD users' motivation, objective, pre-conditions and approach. Drawing on these insights, we propose that OGD initiatives aimed at facilitating outbound OI to a greater extent should address the barriers that appear during diffusion of innovations, the barriers that are not directly related to the OGD provision, and the barriers that are experienced by non-obvious OGD user groups.
The opendata trend is considered to be a robust driver for innovation. The expectation is that opendatasets will stimulate benefits across a variety of sectors (public, private, academia etc.), such as greater trans...
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ISBN:
(纸本)9781910810996
The opendata trend is considered to be a robust driver for innovation. The expectation is that opendatasets will stimulate benefits across a variety of sectors (public, private, academia etc.), such as greater transparency, innovation and the rise of new business models (European Commission, 2011;Davies, 2010). Although they are one of the primary users of governmental opendatasets, private sector companies themselves are not very active yet in opening the massive amount of data they produce (Bonina, 2013;Herzberg 2014). A variety of barriers hold back this potential, such as privacy issues, data security, proprietary interests and data protectionism (Verhulst 2014, Ponte 2015). Therefore our objective was to develop a decision support framework that offers an overview of the various steps required for such an action, taking the barriers and the benefits into account. We followed a design science approach in which we conducted a literature review on the concept of business opendata, performed an in-depth analysis of seven empirical case studies of well-known examples such as Nike, Syngenta and IBM, and we conducted expert interviews. We thus developed a prototype of the decision support framework, based on the concept of open data ecosystems (Heimstadt et al, 2014;Ponte, 2015). The framework was evaluated by high-level experts in the field. We not only identified the main business drivers for private sector companies to open up datasets, such as community building, promotion, business innovation, and new revenue streams. We also addressed the key challenges encountered by the private organizations, which are: characteristics of the data itself, the process for opening-up the data and obstacles in using business opendata (ie. the risks of misinterpretation). Our framework addresses the drivers as well as the barriers for private organizations to decide which datasets are eligible to be opened up, and supports them to consider all aspects that need to be taken in
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