Creating value through governing IT deployment in a public/private-sector inter-organisational context: a human agency perspective

Harnessing value from Information Technology (IT) has long been a focus of research, but evidence is lacking about how effective practice of Information Technology Governance (ITG) contributes to creating value for stakeholders in inter-organisational contexts. This is especially so for public/private sector partnerships. In this study we used ISO/IEC 38500:2008, the corporate governance of IT standard, to direct analysis of how ITG was practised in deployment of a large IT project in an inter-organisational public/private sector context. The findings demonstrate that ITG strategies related to human agency contribute to the realisation of value for participating stakeholders, particularly through pre-emptive stakeholder participation in evaluating IT functionality of the old system and iteratively in deployment of the new system. Further, our investigation shows that ISO/IEC 38500:2008 has merit as an analytical framework to objectively evaluate corporate governance of IT, although there is need for some enhancement.     

Integrating open government data with stratosphere for more transparency

Governments are increasingly publishing their data to enable organizations and citizens to browse and analyze the data. However, the heterogeneity of this Open Government Data hinders meaningful search, analysis, and integration and thus limits the desired transparency.In this article, we present the newly developed data integration operators of the Stratosphere parallel data analysis framework to overcome the heterogeneity. With declaratively specified queries, we demonstrate the integration of well-known government data sources and other large open data sets at technical, structural, and semantic levels. Furthermore, we publish the integrated data on the Web in a form that enables users to discover relationships between persons, government agencies, funds, and companies. The evaluation shows that linking person entities of different data sets results in a good precision of 98.3% and a recall of 95.2%. Moreover, the integration of large data sets scales well on up to eight machines.     

TWC LOGD: A portal for linked open government data ecosystems

International open government initiatives are releasing an increasing volume of raw government datasets directly to citizens via the Web. The transparency resulting from these releases not only creates new application opportunities but also imposes new burdens inherent to large-scale distributed data integration, collaborative data manipulation and transparent data consumption. The Tetherless World Constellation (TWC) at Rensselaer Polytechnic Institute (RPI) has developed the Semantic Web-based TWC LOGD portal to support the deployment of linked open government data (LOGD). The portal is both an open source infrastructure supporting linked open government data production and consumption and a vibrant community portal that educates and serves the growing international open government community of developers, data curators and end users. This paper motivates and introduces the TWC LOGD Portal and highlights innovative aspects and lessons learned.     

政府开放数据的国家安全风险评估模型研究

政府开放数据作为国家和社会发展重要战略资源,蕴含着巨大价值,但我国在政府开放数据的安全风险评估方面缺乏标准,国家数据安全面临风险。借鉴信息安全风险评估理论,以国家安全资产、开放数据脆弱性和安全威胁作为主要安全风险要素,构建政府开放数据的安全风险评估模型,利用层次分析法和模糊综合评价法对政府开放数据的安全风险进行量化评估,并通过实例验证模型的有效性。     

Exploring motivations for contributing to open source initiatives: The roles of contribution context and personal values

We explore contextual and dispositional correlates of the motivation to contribute to open source initiatives. We examine how the context of the open source project, and the personal values of contributors, are related to the types of motivations for contributing. A web-based survey was administered to 300 contributors in two prominent open source contexts: software and content. As hypothesized, software contributors placed a greater emphasis on reputation-gaining and self-development motivations, compared with content contributors, who placed a greater emphasis on altruistic motives. Furthermore, the hypothesized relationships were found between contributors’ personal values and their motivations for contributing.     

Alternative estimation of “public procurement advertised in the Official Journal as % of GDP” official indicator using open government data

This article aims to share some findings about the potential value that can be obtained from the aggregation of public procurement data at a pan-European scale. The period of calculation of the “public procurement advertised in the Official Journal as % of GDP” official indicator could be significantly shortened and the cost of production brought down by harnessing the power of open data. The value of public procurement openly advertised in six countries has been calculated for three different types of prices published in the contract award notices submitted to the OJ. The three rounds of calculations have been compared against the official data released by Eurostat. This article shows how the calculation and discussion of official economic indicators becomes possible for an individual or organization (Euroalert.net) thanks to the availability of open government data (TED), open source software and cloud tools (Google BigQuery) that empower citizens and drive innovation.     

Enhancing cultural recommendations through social and linked open data

In this article, we describe a hybrid recommender system (RS) in the artistic and cultural heritage area, which takes into account the activities on social media performed by the target user and her friends, and takes advantage of linked open data (LOD) sources. Concretely, the proposed RS (1) extracts information from Facebook by analyzing content generated by users and their friends; (2) performs disambiguation tasks through LOD tools; (3) profiles the active user as a social graph; (4) provides her with personalized suggestions of artistic and cultural resources in the surroundings of the user’s current location. The last point is performed by integrating collaborative filtering algorithms with semantic technologies in order to leverage LOD sources such as DBpedia and Europeana. Based on the recommended points of cultural interest, the proposed system is also able to suggest to the active user itineraries among them, which meet her preferences and needs and are sensitive to her physical and social contexts as well. Experimental results on real users showed the effectiveness of the different modules of the proposed recommender.

     

Cross-community context management in Cooperating Smart Spaces

Recently, social networks have become the most prevalent IT paradigm, as the vast majority of Internet users maintain one or multiple social networking accounts. These accounts, irrespectively of the underlying service, contain rich information and data for the owner’s preferences, social skills, everyday activities, beliefs and interests. Along with these services, the computation, sensing and networking capabilities of the state of the art mobile and portable devices, with their always-on mode, assist users in their everyday lives. Thus, the integration of social networking services with current pervasive computing systems could provide the users with the potential to interact with other users that have similar interests, preferences and expectations; and in general, the same or similar context, for limited or not time periods, in order to ameliorate their overall experience, communicate, socialise and improve their everyday activities with minimal effort. This paper introduces a cross-community context management framework that is suitable for Cooperating Smart Spaces, which couple the advantages of pervasive computing and social networking. This framework goes beyond the state of the art, among others, in that cross-community context from a multitude of sources is collected and processed to enhance the end user experience and increase the perceived value of the services provided.     

Electromagnetic modular Smart Surface architecture and control in a microfactory context

This paper presents an electromagnetic conveyance system called electromagnetic modular Smart Surface (emSS) permitting to move pallets on a planar surface in a microfactory context. The proposed surface concept allows flexibility in reconfiguring the system layout along with product routing. The possibilities of accurate positioning of the moving pallet and controlling multiple pallets on the surface make the emSS suitable for reconfigurable and flexible manufacturing systems. However, the emSS control needs to be robust and scalable to adapt the changes in manufacturing systems. A framework is therefore defined to monitor and control the emSS by simulation or in-line. It allows to define product routing on the emSS by satisfying numerous requirements such as reduction in energy consumption, collision avoidance, etc., and to minimize the human interventions by changing product routing when emSS component failures occur. A first experiment realized on an emSS prototype, allowed to compare two paths strategies regarding cost function linked to energy consumption and velocities. Two other studies exploit the emSS modeling in terms of pallet path generation and simulation of collision avoidance.     

Smart wheelchair control through a deictic approach

In this paper, the implementation of assistance to the driving of a smart wheelchair through a deictic approach is described. Initially, a state of the art of mobility assistance, interfaces and types of commands for smart wheelchairs is presented. The deictic concept, and more particularly, the approach used for the design of our interface is examined. Then the two functionalities carried out to implement this type of interface, as well as methodology used to control our wheelchair are illustrated. Finally, the usability of this deictic approach for the assistance to the driving of a smart wheelchair is discussed.     

Integrated machine learning with semantic web for open government data recommendation based on cloud computing

Open government data (OGD) is a type of trusted information that can be used to verify the correctness of information on social platforms. Finding interesting OGD to serve personalized needs to facilitate the development of social platforms is a challenging research topic. This study explores how to link the Taiwanese government's open data platform with Facebook and how to recommend related OGD. First, an integrated machine learning with semantic web into cloud computing framework is defined. Next, the linked data query platform (LDQP) is developed to validate its feasibility. The LDQP provides a graphical approach for personal query and links with related Facebook fan pages. LDQP automatically finds highly relevant OGD based on recent topics that users are following on Facebook when users login to Facebook via the LDQP. In this way, the LDQP query result can be dynamically adjusted and graphically displayed according to user's Facebook operations.     

Missing value estimation for microarray data through cluster analysis

Microarray datasets with missing values need to impute accurately before analyzing diseases. The proposed method first discretizes the samples and temporarily assigns a value in missing position of a gene by the mean value of all samples in the same class. The frequencies of each gene value in both types of samples for all genes are calculated separately and if the maximum frequency occurs for same expression value in both types, then the whole gene is entered into a subset; otherwise, each portion of the gene of respective sample type (i.e., normal or disease) is entered into two separate subsets. Thus, for each gene expression value, maximum three different clusters of genes are formed. Each gene subset is further partitioned into a stable number of clusters using proposed splitting and merging clustering algorithm that overcomes the weakness of Euclidian distance metric used in high-dimensional space. Finally, similarity between a gene with missing values and centroids of the clusters are measured and the missing values are estimated by corresponding expression values of a centroid having maximum similarity. The method is compared with various statistical, cluster-based and regression-based methods with respect to statistical and biological metrics using microarray datasets to measure its effectiveness.     

scenario modeling for government big data governance decision-making: Chinese experience with public safety services

In the public safety service context, government big data governance (GBDG) is a challenging decision-making problem that encompasses uncertainties in the arenas of big data and its complex links. Modeling and collaborating the key scenario information required for GBDG decision-making can minimize system uncertainties. However, existing scenario-building methods are limited by their rigidity as they are employed in various application contexts and the associated high costs of modeling. In this paper, using a design science paradigm, a model-driven scenario modeling approach is proposed to achieve flexible scenario modeling for various applications through the transfer of generic domain knowledge. The key component of the proposed approach is a scenario meta-model that is built from existing literatures and practices by integrating qualitative, quantitative, and meta-modeling analysis. An instantiation mechanism of the scenario meta-model is also proposed to generate customized scenarios under Antecedent-Behavior-Consequence (ABC) theory. Two real-world safety service cases in Wuhan, China were evaluated to find that the proposed approach reduces GBDG decision-making uncertainties significantly by providing key information for GBDG problem identification, solution design, and solution value perception. This scenario-building approach can be further used to develop other GBDG systems for public safety services with reduced uncertainties and complete decision-making functions.     

爱尔兰政府《公共服务数据战略2019-2023》的分析及启示

数据是国家的重要战略资产,实施国家数据战略对优化政府决策、完善公共服务、提升政府治理水平具有重要作用。文章对爱尔兰政府《公共服务数据战略2019-2023》进行文本分析,从愿景、原则、战略主题三个方面介绍了战略的主要内容,最后得出对我国的启示,包括倡导整体性政府理念、推动战略统筹规划、重视个人隐私保护、促进数据开放共享。     

Analysis of two-tier public service systems under a government subsidy policy

Some public service systems such as healthcare systems consist of both free public service provider with a long wait time and paid private service provider with a short wait time. Such service systems are often called a two-tier service system. In general, more customers will choose the free service provider (SP). To reduce the congestion in the free system, the government may encourage customers to use the pay system by offering them a subsidy. This paper studies whether such a subsidy can reduce the free system’s waiting time and improves the social welfare. While the objective of the free system is to maximize its own total customers’ utility, the objective of the pay system is to maximize its profit. We develop a mixed duopoly game to analyze the Nash equilibrium for the competition between the free and toll systems. Two scenarios with unregulated and regulated prices are considered. When the pay system price is unregulated (the private SP can set prices freely), we find that if customers are less sensitive to the service delay, the subsidy policy can effectively reduce the expected waiting time for the free system and increase the customer utility surplus of the entire two-tier system. However, if customers are more sensitive to the service delay, the subsidy policy may have the opposite effect. When the pay system price is regulated (the price determined by government), the subsidy policy can effectively reduce the expected waiting time for the free system and improve the social welfare of the two-tier system. And there exists an optimal regulated price to maximize the social welfare of the entire public service system.     

ICT-driven financial inclusion initiatives for urban poor in a developing economy: implications for public policy

A key agenda of policy-makers in both the developing and the developed worlds is to have an inclusive growth. Financial services have been recognised as one of the fundamental services that have the potential to achieve this objective and help move towards a more just and equitable society. This paper attempts to assess the impact of three information and communication technology-driven initiatives in the field of financial services by differentiating them on the basis of service design. This study goes beyond the stated objective of these services and uses Sen’s capability perspective to study their impact across three non-economic outcome variables viz. literacy, service-specific well-being and empowerment. The data for the study are collected from the urban poor across different locations in a large metropolitan city in South India where the three different services are being offered. The study follows a quasi-experimental design (field study) and ensures matching of the treatment and control groups through propensity score matching. The matched data are analysed using an independent sample t-test. The result of the analysis shows that service design plays a key role in increasing service literacy, improving service-specific well-being and empowering end users. The study suggests that the true challenge for providers (government and partner agencies) of these services is in designing a service that ensures a balance of structure and flexibility without constraining the choice of end users through innovative service blueprints.     

Open data and e-government – related or competing ecosystems: a paradox of open government and promise of civic engagement in Estonia*

ABSTRACT

The article analyzes an open data movement in an unusual context of highly developed digital economy and widespread popularity of e-government services in a country that is universally well-known as one of the global leaders in promoting information society and electronic democracy, but paradoxically demonstrating modest results in propagating a presumably related concept of open government data. In this regard, paying special attention to the investigation of main drivers, stakeholders and challenges of the open data movement in Estonia, the author argues that a highly centralized administrative policy that has been widely used previously by authorities in advancing various technology-driven public reforms, which partly explains a truly impressive advance of this Nordic state in e-government, e-commerce, e-banking and evoting, does not necessarily lead to same effective results in the open data domain. On the contrary, the presence of established democratic institutions and developed civil society as well as an incredibly advanced and dynamic private ICTindustry that values competition and professional curiosity along with a very strong sense of patriotism and adherence to a particular neighborhood deeply rooted in Estonian society has played a much more important role in diffusing the concept rather than just traditional government directives and strategies.