Fatemeh Ahmadi Zeleti

Exploring the economic value of open government data

Abstract 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.

A Tale of Open Data Innovations in Five Smart Cities

Open Data initiatives are increasingly considered as defining elements of emerging smart cities. However, few studies have attempted to provide a better understanding of the nature of this convergence and the impact on both domains. This paper presents findings from a detailed study of 18 open data initiatives across five smart cities -- Barcelona, Chicago, Manchester, Amsterdam, and Helsinki. Specifically, the study sought to understand how open data initiatives are shaped by the different smart cities contexts and concomitantly what kinds of innovations are enabled by open data in these cities. The findings highlight the specific impacts of open data innovation on the different smart cities domains, governance of the cities, and the nature of datasets available in the open data ecosystem.

Emerging business models for the open data industry: characterization and analysis

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.

Capability Matrix for Open Data

With the rapid growth of data on the web, a significant number of businesses have embraced the idea of open data to enable innovation, generate revenue and develop new data products and services. However, many businesses are still reluctant due to paucity of information on requisite capabilities to successfully publish and reuse open data to support their business goals. However, scholarly efforts articulating the nature and types of capabilities required for open data processes and innovation are very limited. This could be partly attributed to the fact that most of the discussions on open data capabilities are predominantly in the practice community. We bridge this knowledge gap by mapping Open Data (OD) capabilities described in extant literature, organizing these capabilities into major capability areas and deconstructing these areas to build a capability matrix. The resulting capability matrix provides OD program managers in particular with a framework (or tool) to develop their detailed OD capability requirements. We also believe that the developed framework provides researchers with a foundation for further analysis of OD capabilities.

Open data value capability architecture

To gain insight into customer’s needs and stay competitive, open data-driven organizations must acquire capabilities to generate different kinds of values from open data. With respect to open data capabilities, scholarly efforts articulating the nature and types of open data capabilities are very limited. To bridge this knowledge gap, we construct a theoretically-grounded open data value capability architecture that explains how open data-driven organizations can identify, map, develop and plan open data value capabilities. To demonstrate and validate the capability architecture, we implemented the architecture in two open data-driven organizations in Ireland. The application of the architecture revealed eight new open data value capabilities: Knowledge of data standards and Data on the Web Best Practices, Knowledge of data value, Data Strategy, Aggregation process (GPS), Database architecture, Knowledge of graph data models, Verifying data integrity, and Web-based front-end. We conclude that the Open data capability domain is yet to mature. Thus, more scholarly and empirical research is necessary in this area.

Realizing the Innovation Potentials from Open Data: Stakeholders’ Perspectives on the Desired Affordances of Open Data Environment

Despite the increasing number of datasets available on open data platforms, there has been limited adoption and use of open data by the public. This has consequently limited the innovation and transparency impact of open data on respective economies and governments. While literature is replete with articles on barriers to open data exploitation and use; these studies are yet to examine how affordances of open data platforms could help to overcome these barriers. This perspective is important since the platform directly mediates access to open data resources and their use. We describe a study carried out as part the Route-To-PA (Route-To-PA Project, Raising Open and User-friendly Transparency Enhancing Technologies for Public Administrations, H2020 Project, http://routetopa.eu/.) project to establish stakeholder’s perspectives on barriers to effective use of open data and the desired open data platform affordances to address these problems. Our results provide details on what kinds of data are needed by stakeholders, the features required to support their interactions and collaboration around open data and features that could enhance the understandability of datasets available on open data platform.

Critical Factors for Dynamic Capabilities in Open Government Data Enabled Organizations

Open data (OD) is increasingly considered as a core resource for many organizations in the emerging data economy. Open data-driven organizations (ODDOs) like any other organizations must develop capabilities for competitiveness and agility in addition to processes for creating value from OD to survive. While questions about the extent to which OD could be used for competitive advantage has been raised in past studies, no previous study has investigated the salient factors for agility in a dynamic data ecosystem. This paper bridges the knowledge gap by developing an operationalization of the Dynamic Capability Theory for ODDOs. As a first step towards determining the critical factors for developing dynamic capabilities (DCs) in these organizations, we analyzed the information gathered from an expert interview on the saliency of the different aspects and stages of dynamic capability in developing the agility of an up-stream organization or OD supplier in the data ecosystem. Our findings suggest that critical factors for DCs differ for organizations in the upstream and downstream sectors, albeit some core elements are shared across sectors in data ecosystem.

Business models for open data businesses

Despite the increasing volume of publications and research in open data, many aspects of open data are yet to be studied. To this extent, extensive literature review on business models in the context of open data was performed. Interestingly, scholarly efforts providing practical elaborations and rigorous analysis of open data business models are omitted. 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. Therefore, this thesis will address issues related to open data business models. This paper focuses on the background and results of my research to date. This paper also outlines the potential research questions and future work.

Competitive Capability Framework for Open Government Data Organizations

Open data-driven organizations compete in a complex and uncertain environment with growing global competition, changing and emerging demand and market, and increasing levels of analytical tools and technology. For these organizations to exploit open data for competitive advantage, they need to develop the requisite competitive capabilities. This article presents an open data competitive capability framework grounded in theory and practice of open data. Based on extant literature and insights from domain experts, we identify and describe four dimensions of competitive capabilities required for open data driven organizations. We argue that by implementing the proposed framework, organizations can increase their chances to favorably compete in their respective markets. We further argue that by understanding open government data as a strategic resource for enterprises, government as producers or suppliers of this resource become key partners to data-driven organizations.

Capability Model for Open Data: An Empirical Analysis

Creating superior competitiveness is central to open data organizations survivability in the fast changing and competitive open data market. In their quest to develop and increase competitiveness and survivability, many of these organizations are moving towards developing open data capabilities. Research-based knowledge on open data capabilities and how they relate to each other remains sparse, however, with most of the open data literature focusing on social and economic value of open data, not capabilities required. By exploring the related literature on business and organizational capabilities and linking the findings to the empirical evidence collected through the survey of 49 open data organizations around the world, this study develops an open data capability model. The model emerged from our deductive research process improves both theoretical and practical understanding of open data capabilities and their relationships required to help increase competitiveness and survivability of these types of organizations.