Evangelos Kalampokis

Understanding the predictive power of social media

Purpose – The purpose of this paper is to consolidate existing knowledge and provide a deeper understanding of the use of social media (SM) data for predictions in various areas, such as disease outbreaks, product sales, stock market volatility and elections outcome predictions. Design/methodology/approach – The scientific literature was systematically reviewed to identify relevant empirical studies. These studies were analysed and synthesized in the form of a proposed conceptual framework, which was thereafter applied to further analyse this literature, hence gaining new insights into the field. Findings – The proposed framework reveals that all relevant studies can be decomposed into a small number of steps, and different approaches can be followed in each step. The application of the framework resulted in interesting findings. For example, most studies support SM predictive power, however, more than one-third of these studies infer predictive power without employing predictive analytics. In addition, a...

A classification scheme for open government data: towards linking decentralised data

Open government data (OGD) refers to making public sector information freely available in open formats and ways that enable public access and facilitate exploitation. Lately, a large number of OGD initiatives launched worldwide aiming to implement one-stop portals acting as single points of access to governmental data. At the same time, the so-called linked data technologies emerged aiming at publishing structured data on the web in such a way that enables semantically enriching data, uniform access to data, and linking of data. In this paper, we first propose a classification scheme for OGD initiatives based on the relevant literature. We thereafter, review and analyse OGD initiatives based on the proposed scheme. We finally present an architecture and prototype implementation for the most advanced OGD class in our scheme, which enables linking decentralised data.

Open government data: a stage model

Public sector information constitutes a valuable primary material for added-value services and products, which however remains unexploited. Recently, Open Government Data (OGD) initiatives emerged worldwide aiming to make public data freely available to everyone, without limiting restrictions. Despite its potential however there is currently a lack of roadmaps, guidelines and benchmarking frameworks to drive and measure OGD progress. This is particularly true as proposed stage models for measuring eGovernment progress focus on services and do not sufficiently consider data. In this paper, we capitalize on literature on eGovernment stage models and OGD initiatives to propose a stage model for OGD. The proposed model has two main dimensions, namely organizational & technological complexity and added value for data consumers. We anticipate the proposed model will open up a scientific discussion on OGD stage models and will be used by practitioners for constructing roadmaps and for benchmarking just like the European Union stage model is currently used for measuring public service online sophistication.

A Domain Model for eParticipation

The introduction of information and communication technologies (ICTs) in the field of public participation led to the emergence of electronic participation (eparticipation). The area of eparticipation is currently a rapidly evolving one. Although, a few eparticipation-related frameworks have been developed they actually aimed to address specific purposes. As a result, there is no work aiming to model the whole eparticipation domain. In this paper, a first attempt to model the domain of eparticipation is presented. For this purpose, we identify and describe the most significant aspects that characterize the eparticipation domain according to the relevant literature. In addition, we define a domain model in order to formally describe these aspects and the relationships between them. This model is illustrated using a set of Unified Modeling Language (UML) package and class diagrams.

Combining social and government open data for participatory decision-making

In the last years, several research endeavors were launched aiming at involving popular social media platforms in electronic participation. These early endeavors seem to present some essential limitations related mainly to scalability and uptake. In order to avoid these limitations, we introduce a two-phased approach for supporting participatory decision-making based on the integration and analysis of social and government open data. The proposed approach is based on the literature related to the analysis of massive amounts of social data for future events prediction. In this paper we also present a Web data driven architecture for the implementation of the proposed approach. The architecture is based on the use of linked data paradigm as a layer that will enable integration of data from different sources. We anticipate that the proposed approach will (i) allow decision makers to understand and predict public opinion and reaction about specific decisions; and (ii) enable citizens to inadvertently contribute in decision-making.

A survey of e-participation research projects in the European Union

The introduction of Information and Communication Technologies in the field of public participation has led to the emergence of electronic participation (e-participation). The field of e-participation is rapidly evolving and is characterised by an increasing number of related projects and tools. In this paper we survey e-participation projects financially supported by the European Commission under relevant calls for proposals, i.e., within FP5, FP6, eTen, Interreg and the Preparatory Actions 2006. Our results reveal the total investment in e-participation, the main areas of research, as well as the primary technologies and tools in use within these projects.

Linked Open Government Data Analytics

Although the recently launched Open Government Data OGD movement promised to provide a number of benefits, recent studies have shown that its full potential has not yet realized. The difficulty in exploiting open data seems surprising if we consider the huge importance data have in modern societies. In this paper we claim that the real value of OGD will unveil from performing data analytics on top of combined statistical datasets that were previously closed in disparate sources and can now be linked to provide unexpected and unexplored insights. To support this claim, we describe the linked OGD analytics concept along with its technical requirements and demonstrate its end-user value employing a use case related to UK general elections. The use case revealed that there is a significant relationship between the probability one of the two main political parties i.e. Labour Party and Conservative Party to win in a UK constituency and the unemployment rate in the same constituency.

Fostering Enterprise Architecture Education and Training with the Enterprise Architecture Competence Framework

Enterprise architecture (EA) implementation refers to a set of activities ultimately aiming to align business objectives with information technology infrastructure in an organization. EA implementation is a multidisciplinary, complicated and endless process, hence, calls for adequate education and training programs that will build highly skilled personnel (called enterprise architects) with diverse competencies. This development of domain‐specific competencies is also supported by European policies on education and vocational training. To this end, the authors present training uses of the Enterprise Architecture Competence Framework (EA‐CF). EA‐CF is a proposed conceptual model that describes EA competencies in compliance to the European e‐Competence Framework (e‐CF). The authors argue that EA stakeholders can consult the framework regarding competencies they want to underpin and thus identify the corresponding skills, knowledge and attitudes that result as learning outcomes in EA courses and training programs.

The linked medical data access control framework

The integration of medical data coming from multiple sources is important in clinical research. Amongst others, it enables the discovery of appropriate subjects in patient-oriented research and the identification of innovative results in epidemiological studies. At the same time, the integration of medical data faces significant ethical and legal challenges that impose access constraints. Some of these issues can be addressed by making available aggregated instead of raw record-level data. In many cases however, there is still a need for controlling access even to the resulting aggregated data, e.g., due to data providers policies. In this paper we present the Linked Medical Data Access Control (LiMDAC) framework that capitalizes on Linked Data technologies to enable controlling access to medical data across distributed sources with diverse access constraints. The LiMDAC framework consists of three Linked Data models, namely the LiMDAC metadata model, the LiMDAC user profile model, and the LiMDAC access policy model. It also includes an architecture that exploits these models. Based on the framework, a proof-of-concept platform is developed and its performance and functionality are evaluated by employing two usage scenarios.

On publishing linked open government data

In the last years, a number of government led initiatives have been launched worldwide aiming at making government data freely available to everyone, without limiting restrictions. Linked Data has been employed by some of these as a paradigm that allows for the provision of structured, semantically enabled and linkable data on the Web. The objective of this article is to discuss how Linked Data has been used in government data provision so far and to describe an architecture that will enable the provision of integrated government data around real-world things in a decentralized manner. Moreover, an implementation of the specific architecture is described in detail employing a hypothetical use case scenario that involves real world public agencies and schools. This implementation includes among others the publishing of Linked Data on top of a relational database and inline the HTML code of a web page as well as the linking of data from distributed sources at the instance level.