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The aim of this paper is to describe a local government effort to realise an open government agenda. This is done using a storytelling approach.

The empirical data are based on a case study. The authors participated in, as well as followed, the process of realising an open government agenda on a local level, where citizens were invited to use open public data as the basis for developing apps and external Web solutions. Based on an interpretative tradition, they chose storytelling as a way to scrutinise the competition process. In this paper, they present a story about the competition process using the story elements put forward by Kendall and Kendall (2012).

The research builds on existing research by proposing the myth that the “public” wants to make use of open data. The authors provide empirical insights into the challenge of gaining benefits from open public data. In particular, they illustrate the difficulties in getting citizens interested in using open public data. Their case shows that people seem to like the idea of open public data, but do not necessarily participate actively in the data reuse process.

The results are based on one empirical study. Further research is, therefore, needed. The authors would especially welcome more studies that focus on citizens’ interest and willingness to reuse open public data.

This study illustrates the difficulties of promoting the reuse of open public data. Public organisations that want to pursue an open government agenda can use these findings as empirical insights.

This paper answers the call for more empirical studies on public open data. Furthermore, it problematises the “myth” of public interest in the reuse of open public data.

The aim of this study was to understand how public relations leaders view and use social media analytics (SMA) and the impact of SMA on the public relations function.

The research involved in-depth interviews with chief communication officers (CCOs) from leading multinational corporate brands.

The findings revealed that although CCOs perceive social media analytics as strategically important to the advancement of public relations, the use of social media data is slowed by challenges associated with building SMA capacity.

The research extends public relations theory on public relations as a strategic management function and provides practical insights for building SMA capabilities.

The study is among the first to provide empirical evidence of how companies are using social media analytics to enhance public relations efforts.

This paper aims to address the recent trends and developments relating to the re‐use of public sector information (PSI) and open government data.

It starts from the European Commission's Digital Agenda, which stressed the importance of opening up access to content to promote the single market. While the 2003 PSI directive has contributed to this, barriers to the re‐use of PSI still remain, often based on a lack of awareness with public sector data holders and users. Some of these barriers are currently being challenged by the open government data (OGD) movement. While this movement has comparable objectives to the PSI directive, it is based on different arguments. This raises the question of how the two approaches relate.

The paper argues that the proponents of the re‐use of PSI and OGD should join forces to promote the availability of public sector data.

In this way, the public sector can be encouraged to rethink its information policy and move to a more coherent view on how data can be used to increase the benefits for the information society and the market for digital content.

Blighted and vacant properties represent a persistent and costly problem for cities and local governments throughout the USA. The purpose of this paper is to identify data needs and requirements for value creation in the context of urban blight. The main assumption is that sharing and opening data through a robust and effective code enforcement program will facilitate more informed management, mitigation and remediation of blighted and vacant properties. Code enforcement programs must be grounded on organizational and technical infrastructures that enable data sharing and value creation for the city and the communities that share its space.

In this paper, the information needs and realities of a city’s code enforcement environment are described, based on data gathered through a series of workshops and focus groups with a range of stakeholders, which included city government departments, police, fire, bank representatives, realtors and community groups.

The analysis reveals key data elements that could potentially help to build a code enforcement program to better manage the cycles and costs of urban blight. Although some of these data elements already exist, and are public, they are not easily accessible to key stakeholders. The paper ends with sets of short-term and long-term recommendations for establishing an information-sharing infrastructure, which would serve as the main conduit for exchanging code enforcement data among a number of city government departments and the public that may play a role in managing urban blight and its consequences.

In this paper, the authors are connecting extant literature on sharing and opening data with literature on the creation of public value. They argue that sharing and opening government data constitute effective ways of managing the costs and cycles of urban blight while creating value. As a result of an initial assessment of data and information requirements, the authors also point to specific data and its potential value from stakeholder perspective.

The purpose of this paper is to explore the roles of public libraries in the context of Big Data.

A mixed method approach was used and had two main data collection phases. A survey of public libraries was used to generate an overview of which professional roles connect public libraries with Big Data. Eight roles were identified, namely, educator, marketer, data organiser, data container, advocator, advisor, developer and organisation server. Semi-structured interviews with library directors and managers were then conducted to gain a deeper understanding of these roles and how they connect to the library’s overall functions.

Results of the survey indicated that librarians lack a proper comprehension of and a pragmatic application of Big Data. Their opinions on the eight roles are slightly stronger than neutral. However, they do not demonstrate any strong agreement on these eight roles. In the interviews, the eight roles attained more clear support and are classified into two groups: service-oriented and system-oriented roles.

As an emerging research field, Big Data is not widely discussed in the library context, especially in public libraries. Therefore, this study fills a research gap between public libraries and Big Data. In addition, Big Data in public libraries could be well managed and readily approached by citizens in undertaking such roles, which entails that public libraries will eventually benefit from the Big Data era.

The revitalization of big data has gained attention in the public sector. However, such open government data (OGD) is facing major challenges with respect to data quality and limited use. To solve this problem, this study analyzes the factors driving the use of OGD from the perspective of data providers in the public sector.

Using the analytic hierarchy process and analytic network process methodologies, the importance of the factors driving the use of big data in the public sector was ranked. In addition, the different characteristics of tasks among the departments in a public agency were compared based on expert interviews.

The factors driving OGD use are not only political environment or the technological environment. The importance of the institutional culture within the organization increases with the motivation of the data provider. The priorities of the OGD factors also depend on the objectives of the department involved.

This study provides implications for improving the publication of open data by analyzing the priorities of the factors driving its use from the perspective of big data providers. It focuses on different perceptions of the factors valued by public officials in charge of data in institutions. The results suggest the need to explore officials' perceptions of value creation in big data fields.

With the worldwide open government data (OGD) movement and frequent public health emergencies in recent years, academic research on OGD for public health emergencies has been growing. However, it is not fully understood how to promote OGD on public health emergencies. Therefore, this paper aims to explore the factors that influence OGD on public health emergencies.

The technology–organization–environment framework is applied to explore factors that influence OGD during COVID-19. It is argued that the effects of four key factors – technical capacity, organizational readiness, social attention and top-down pressure – are contingent on the severity of the pandemic. A unique data set was created by combining multiple data sources which include archival government data, a survey of 1,034 Chinese respondents during the COVID-19 outbreak and official COVID-19 reports.

The data analysis indicates that the four factors positively affect OGD, and pandemic severity strengthens the effects of technical capacity, organizational readiness and social attention on OGD.

This study provides theoretical insights regarding how to improve OGD during public health emergencies, which can guide government efforts in sharing data with the public when dealing with outbreak in the future.

Despite several big data maturity models developed for businesses, assessment of big data maturity in the public sector is an under-explored yet important area. Accordingly, the purpose of this study is to identify the big data maturity models developed specifically for the public sector and evaluate two major big data maturity models in that respect: one at the state level and the other at the organizational level.

A literature search is conducted using Web of Science and Google Scholar to determine big data maturity models explicitly addressing big data adoption by governments, and then two major models are identified and compared: Klievink et al.’s Big Data maturity model and Kuraeva’s Big Data maturity model.

While Klievink et al.’s model is designed to evaluate Big Data maturity at the organizational level, Kuraeva’s model is appropriate for assessments at the state level. The first model sheds light on the micro-level factors considering the specific data collection routines and requirements of the public organizations, whereas the second one provides a general framework in terms of the conditions necessary for government’s big data maturity such as legislative framework and national policy dimensions (strategic plans and actions).

This study contributes to the literature by identifying and evaluating the models specifically designed to assess big data maturity in the public sector. Based on the review, it provides insights about the development of integrated models to evaluate big data maturity in the public sector.