The value of data: an analysis of closed-urban-data-based and open-data-based business models (original) (raw)
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Proceedings of the 15th Annual International Conference on Digital Government Research - dg.o '14, 2014
Business models for open data have emerged in response to the economic opportunities presented by the increasing availability of open data. However, scholarly efforts providing elaborations, rigorous analysis and comparison of open data models are very limited. This could be partly attributed to the fact that most discussions on open data business models are predominantly in the practice community. This shortcoming has resulted in a growing list of open data business models which, on closer examination, are not clearly delineated and lack clear value orientation. We address this problem by 1) consolidating reported open data business models in both academic and practice literature, 2) describe the models based on a business model framework, and 3) determine open data business models patterns. In addition, we identified the emerging core value disciplines for open data businesses. Our results help to streamline existing useful models, and link them to the overall business strategy through value disciplines.
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Business models for open government data
Proceedings of the 8th International Conference on Theory and Practice of Electronic Governance, 2014
The commercial re-use of open government data is broadly expected to generate economic value. However, the practice and study of this trend is still in its infancy. In particular, the issue of value creation in the commercial re-use open government data remains largely unknown. This study aims to further understand how open government data is used to develop commercial products and services. Grounded in the comprehensive data obtained from a sample of 500 U.S. firms that use open government data as part of their business model, we propose a taxonomy that encompasses three business model archetypes (enablers, facilitators, and integrators). Furthermore, we discuss the value proposition of each business model archetype, and subsequently present a framework that describes the value created in the context of the open government data ecosystem. Our framework can be used by both scholars and practitioners in the field of open government data to effectively frame the debate of the value created by the commercial re-use of open government data. Simultaneously, our work can be of benefit to entrepreneurs as it provides a systematic overview, as well as practical insights, of the growing use of open government data in the private sector.
Open Innovation, Open Data and new Business Models
Open government data are the result of as well as the preconditions for open government. Data made publically accessible are an important basis for creating added value for society as a whole. Open data business models support entrepreneurs in reusing and combining available open data sources to provide value-added services. Three cases show how open data business models can be realized.
This section offers a series of joint reflections on (open) data platform from a variety of cases, from cycling, traffic and mapping to activism, environment and data brokering. Data platforms play a key role in contemporary urban governance. Linked to open data initiatives, such platforms are often proposed as both mechanisms for enhancing the accountability of administrations and performing as sites for 'bottom-up' digital invention. Such promises of smooth flows of data, however, rarely materialise unproblematically. The development of data platforms is always situated in legal and administrative cultures, databases are often built according to the standards of existing digital ecologies, access always involves processes of social negotiation, and interfaces (such as sensors) may become objects of public contestation. The following contributions explore the contested and mutable character of open data platforms as part of heterogeneous publics and trace the pathways of data through different knowledge, skills, public and private configurations. They also reflect on the value of STS approaches to highlight issues and tensions as well as to shape design and governance.
Data Ownership and Open Data: The Potential for Data-Driven Policy Making
SpringerBriefs in applied sciences and technology, 2021
As part of the rhetoric surrounding the Smart City concept, cities are increasingly facing challenges related to data (management, governance, processing, storage, publishing etc.). The growing power acquired by the data market and the great relevance assigned to data ownership rather than to data-exploitation knowhow is affecting the development of a data culture and is slowing down the embedding of data-related expertise inside public administrations. Concurrently, policies call for more open data to foster service innovation and government transparency. What are the consequences of these phenomena when imagining the potential for policy making consequent to the growing data quantity and availability? Which strategic challenges and decisions do public authorities face in this regard? What are valuable approaches to arm public administrations in this "war on data"? The Smart Flanders program was initiated by the Flemish Government (Belgium) in 2017 to research and support cities with defining and implementing a common open data policy. As part of the program, a "maturity check" was performed, evaluating the cities on several quantitative and qualitative parameters. This exercise laid to bare some challenges in the field of open data and led to a checklist that cities can employ to begin tackling them, as well as a set of model clauses to be used in the procurement of new technologies.
AO 05 Business models adopted by intermediaries in the use of open government data
2016
After the adoption of open data policies by governments around the world, new business models began to explore the databases opened and create new products and services that may or not generate revenue for its providers. From this scenario, this study aimed to understand the business models adopted by service providers that use open government databases or databases built from public data and data captured by tools resulting from these new products and services. Therefore, we analyzed seven cases of businesses awarded in prizes that had evaluation criteria such as innovation, technology and services to the population. This qualitative study aimed to identify evidences of phenomena relating to the use of open government databases, the participation of these service providers in the open government data value chain and features present in their business models that could be replicated in new cases. The main findings revealed that business models need to create databases that standardi...
The Open Data Canvas–Analyzing Value Creation from Open Data
Digital Government: Research and Practice
Expectations to derive value from open data are high. However, how value is created from open data is still largely unknown. Open data value is usually generated in constellation of actors in which each player has different capabilities and roles. To understand the open data value creation process, the business model canvas is introduced in this article. The typical components of the business model canvas and open data value creation are derived from the literature. By combining these two research streams, the open data value model canvas is created. The case of Coronavirus disease 2019 (COVID-19) worldwide dashboard developed by the Johns Hopkins University is used to evaluate the model's utility. Key components of the open data value model are creating an overview of various data sources from public and private organizations, having capabilities to combine heterogeneous data, and connecting data and needs. In this way, the open data canvas helps to grasp the value creation logic.
Exploring the economic value of open government data
Government Information Quarterly, 2016
Business models for open data have emerged in response to the economic opportunities presented by the increasing availability of open data. However, scholarly efforts providing elaborations, rigorous analysis and comparison of open data models are very limited. This could be partly attributed to the fact that most discussions on Open Data Business Models (ODBMs) are predominantly in the practice community. This shortcoming has resulted in a growing list of ODBMs which, on closer examination, are not clearly delineated and lack clear value orientation. This has made the understanding of value creation and exploitation mechanisms in existing open data businesses difficult and challenging to transfer. Following the Design Science Research (DSR) tradition, we developed a 6-Value (6-V) business model framework as a design artifact to facilitate the explication and detailed analysis of existing ODBMs in practice. Based on the results from the analysis, we identify business model patterns and emerging core value disciplines for open data businesses. Our results not only help streamline existing ODBMs and help in linking them to the overall business strategy, but could also guide governments in developing the required capabilities to support and sustain the business models.
Data Ecosystem Business Models
Journal of Business Models
Purpose: Organizations evolve from using and governing data internally towards the exchange of data in multi-organizational data ecosystems. The purpose of this research is to determine a business model framework for actors operating in and/or entering a data ecosystem. Methodology: To determine a business model framework in data ecosystems. an analysis was made based on how the research fields of “business models”, “data governance”, “data ecosystems”, “data sharing”, “business ecosystem” complement each other. A business model framework was created, which was applied to three use case studies in the field of Smart Cities and Urban Digital Twins: The Helsinki Digital Twin, the Rotterdam Digital Twin, and the Smart Retail Dashboard in Flanders. Findings: The business model of actors in a data ecosystem is determined by value and control factors. Value is determined by the capability to create value through the exchange of data in the ecosystem, and to capture value through revenue (...