Adegboyega Ojo

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.

An ontology for next generation e-Participation initiatives

Abstract Despite over a decade-long experience of implementing e-Participation initiatives, there have been limited efforts so far to develop a detailed, comprehensive conceptualization for e-Participation considered from three distinct perspectives: as democratic process, a project and a deliberation platform. Current e-Participation literature is replete with fragmented models, which only partially describe aspects of e-Participation with main focus on structuring the “e-Participation” concept as a domain. This has made consistent descriptions and comparative analysis of e-Participation initiatives difficult, thus hindering the overall evolution of e-Participation. Consequently, no comprehensive, formal, executable e-Participation Ontology exists, that could be directly leveraged to facilitate operations of e-Participation initiatives or improving communication and knowledge exchange between similar e-Participation initiatives. In addition, current generation of e-Participation models does not explicitly support the emerging phenomenon of spontaneous, citizen-led e-Participation, in particular hosted on the social media platforms. This work bridges this gap by providing a practical, yet sufficiently detailed, conceptualization along with corresponding formal and executable ontology for next generation e-Participation. These semantic models cover the core facets of e-Participation — as a democratic process, an initiative and a sociotechnical system. The developed models also explicitly support the integrated citizen- and government-led model of e-Participation. For demonstration and validation, we employed the developed e-Participation Formal Ontology as a “design artefact” to describe two e-Participation initiatives at Local Government and European levels.

Driving public sector innovation using big and open linked data (BOLD)

Innovation in government is about finding new ways to improve society, the government itself and the relationship between the government and the public. Many of such innovations are driven by the availability of Big and Open Linked Data (BOLD) (Janssen and Kuk 2016), the Internet of Things (IoT) and the resulting datafication of our society. Data-driven innovation can result in a dramatic transformation of public sector systems and can create societal benefits like less pollution, fewer traffic jams, improved tracking of disease outbreaks, greater energy efficiency, new agriculture services, novel applications to transform citizen experience interacting online with government, and lower costs. Big and open data play a pivotal role in this transformation and collecting, combining and sharing data from various sources has become an important means for public-sector innovation. BOLD is a global phenomenon driven by the need to boost innovation, create transparency and improve accountability (Bertot et al. 2010; Lourenço 2015). Adoption proves to be challenging (Zuiderwijk et al. 2015). Achieving the BOLD objectives might require tradeoffs such as transparency versus privacy as a competing value (Janssen and Van den Hoven 2015) and a data protection act might prevent sharing (van Loenen et al. 2016). Linking and analyzing data originating from a variety of sources can be applied in various domains, like providing real-time weather, pollution and traffic information, but also for enforcement and fraud detection, creating transparency,making cities smarter, improving a country’s competitiveness, improving decisionand policy-making and responding better in crisis management. At the local level this is often denoted as smart cities, in which all kinds of apps can assist in monitoring, analyzing and visualizing social, economic and environmental phenomena (Jaakola et al. 2015). Nevertheless there is no consensus about what smartness is (Gil-Garcia et al. 2016). Smartness encompasses various aspects including data, technology, processes and people. Data should be used to empower persons resulting in ‘smart citizens’. Instead of reinforcing current processes, big and open data should result in open government (Luna-Reyes et al. 2014). Not only should data be published, but it should be actively sought for feedback to improve the government. The publishing of government data could have far-reaching effects on the public sector. Furthermore the availability of a vast amount of data can have a profound influence on policy-making. Data can be used by governments and the public for modelling, understanding policy implications, and supporting policy decisions. For example, Data.gov is the U. S. federal government’s open data site, which aims to make government more open and accountable, thereby increasing citizen participation in government, creating opportunities for economic development, and informing decision making in * Marijn Janssen M.F.W.H.A.Janssen@tudelft.nl

Exploring the Nature of the Smart Cities Research Landscape

As a research domain, Smart Cities is only emerging. This is evident from the number of publications, books, and other scholarly articles on smart cities indexed in Google scholar and Elsevier’s Scopus—an abstract and citation database. However, significant literature is available on related topics like intelligent city, digital city, and intelligent community based on search results research repositories such as Elsevier’s Scopus, ACM Digital Library, and Google Scholar. This chapter maps the research work in the smart cities’ domain, based on the available scholarly publications. The aim is to synthesize an emerging understanding of the smart city concept, determine major research themes, types, and gaps in the current research landscape.

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.

On the Duality of E-Participation --- Towards a Foundation for Citizen-Led Participation

What remains unclear after a decade of e-Participation research and practice is the extent to which the social web and informal channels have empowered citizens in government-citizen interactions where government determines what, where and how to discuss. Lately, attention has shifted to how these informal channels could be better harnessed as part of a holistic e-Participation solution. However, this implicit notion of duality of e-Participation is yet to be explored or conceptualized. This paper provides a first step towards understanding the duality of Government-led and Citizen-led e-Participation based on structuration and dynamic capabilities theories. We employ structuration theory to understand how dynamics of power between government and citizen in deciding what is important for the society and the solutions to adopt could tilt towards the side of citizens through citizen-led deliberations. Through the dynamic capabilities theory, we determine additional capabilities required by governments to meaningfully exploit and sustain citizen-led e-participation as a part or a holistic e-participation framework. We show through a case study how our resulting analytical tool could be employed in identifying salient technical, organisational and political issues in an on-going Irish e-Participation initiative planning to adopt citizen-led deliberation.

Towards a Linked Geospatial Data Infrastructure

The pressure of opening access to public sector geospatial information traditionally managed within disparate spatial data infrastructures SDI is driven by a combination of factors. These factors include the adoption of open data programs and the need to integrate spatial data across sectors and levels of government for specific applications. Informed by the success of the Linked Open Data community, efforts to leverage Linked Data in enabling global access to spatial data currently managed within national and regional SDIs are emerging. However, these early efforts do not provide guidelines for implementing such Linked SDI nor articulate the socio-technical requirements for a successful Linked Geospatial Data strategy. By analyzing existing SDI architectures and emerging Linked SDI requirements, we develop Reference Architecture for building interoperable Linked SDIs.

A Comparative Analysis of Tools and Technologies for Policy Making

Latest advancements in information and communication technologies offer great opportunities for modernising policy making, i.e. increasing its efficiency, bringing it closer to all relevant actors, and enhancing its transparency and acceptance levels. In this context, this chapter aims to present, analyse, and discuss emerging information and communication technologies (ICT) tools and technologies presenting the potential to enhance policy making. The methodological approach includes the searching and identification of relevant tools and technologies, their systematic analysis and categorisation, and finally a discussion of potential usage and recommendations for enhancing policy making.