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Part 1: Semantic Concepts and Open Data ; International audience ; Open Data is a current trend in sharing data on the Web. Public sector bodies maintain large amounts of data that, if re-used, could be a source of significant benefits. Therefore Open Government Data initiatives have been launched in many countries in order to increase availability of openly licensed and machine-readable government data. Because Open Data publishers face various challenges, methods for publication of Open Data are emerging. However these methods differ in focus, scope and structure which might complicate selection of a method that would suit specific needs of an organization. In this paper we discuss the possible benefits of constructing Open Data publication methods from a meta-model and we use the Software and Systems Process Engineering Meta-Model version 2.0 to analyze similarities and differences in structure of three Open Data publication methods.

There is a lack of research concerning the factors influencing the success or failure of open data initiatives. Based on the results of two workshops, we provide a list of 47 success factors for open data publication and 18 success factors for open data use. We further use three case studies (ENGAGE, Open NY, and Open Vienna) to examine how the criticality of factors varies depending on the geographical level and other characteristics of the open data initiative. The cases, representing open data initiatives at city, regional and transnational levels, point at different categories of critical success factors. Our key conclusions are that 1) the criticality of the factors depends considerably on the context of the open data initiative; 2) a number of success factors appear to be more universally applicable than others; 3) the factors that are critical to all three cases are derived from many different success factor categories, which suggests that open data initiatives should adopt an interdisciplinary approach, and 4) further work is needed to detail the success factors for open data publication and use in other contexts.

Open Government Data (OGD) is a movement that has spread worldwide, enabling the publication of thousands of datasets on the Web, aiming to concretize transparency and citizen participatory governance. This initiative can create value by linking data describing the same phenomenon from different perspectives using the traditional Web and semantic web technologies. A framework of these technologies is linked data movement that guides the publication of data and their interconnection in a machine-readable means enabling automatic interpretation and exploitation. Nevertheless, Open Government Data publication as Linked Open Data (LOD) is not a trivial task due to several obstacles, such as data heterogeneity issues. Many works dealing with this transformation process have been published that need to be investigated thoroughly to deduce the general trends and the issues related to this field. The current work proposes a classification of existing methods dealing with OGD-LOD transformation and a synthesis study to highlight their main trends and challenges.

A large number of open government data concerns official and unofficial statistics. These data can be represented as multidimensional data. In this paper, we commence by presenting data fragmentation, an important challenge when exploiting open data. We thereafter introduce multidimensional data as a possible solution to overcome data fragmentation. More specifically, we outline the data cube model and linked open data technologies. In addition, we present a process for multidimensional linked open data publication and reuse. We also present a number of software tools that have been developed to manage multidimensional linked open data. We finally summarize the benefits and some of the main barriers.

A large number of open government data concerns official and unofficial statistics. These data can be represented as multidimensional data. In this paper, we commence by presenting data fragmentation, an important challenge when exploiting open data. We thereafter introduce multidimensional data as a possible solution to overcome data fragmentation. More specifically, we outline the data cube model and linked open data technologies. In addition, we present a process for multidimensional linked open data publication and reuse. We also present a number of software tools that have been developed to manage multidimensional linked open data. We finally summarize the benefits and some of the main barriers.

This document provides the Swiss Linked Data community with a shared vision of the state of linked open data publication in the public and heritage sectors in Switzerland and gives people who are new to the community a first overview of previous and ongoing activities in the area of data publication, data use, and know-how exchange. The document contains a short introduction to linked (open) data, gives a detailed account of what linked data publication is about, provides an overview of the present state of linked data publication by Swiss public and heritage sector organizations, and presents a series of exemplary use cases that serve as test and study cases to tackle current challenges and demonstrate the usefulness of linked (open) data in practice.

The provision and dissemination of Open Data is a flourishing concept, which is highly recognized and established in the government and public administrations domains. Typically, the actual data is served as static file downloads, such as CSV or PDF, and the established software solutions for Open Data are mostly designed to manage this kind of data. However, the rising popularity of the Internet of things and smart devices in the public and private domain leads to an increase of available real-time data, like public transportation schedules, weather forecasts, or power grid data. Such timely and extensive data cannot be used to its full potential when published in a static, file-based fashion. Therefore, we designed and developed Ronda - an open source platform for gathering, processing and publishing real-time Open Data based on industry-proven and established big data and data processing tools. Our solution easily enables Open Data publishers to provide real-time interfaces for heterogeneous data sources, fostering more sophisticated and advanced Open Data use cases. We have evaluated our work through a practical application in a production environment.

Part 2: Open Government ; International audience ; Innovation based on open data lags behind the high expectations of policy makers. Hence, open data researchers have investigated the barriers of open data publication and adoption. This paper contributes to this literature by taking a capabilities perspective on how successful open data re-users create value out of the available data sources. First, a framework of IT, organization and skills capabilities required to innovate with data is derived from literature. Second, a case study including a survey and interview with managers from 12 frontrunners in the Netherlands was conducted. The analysis reveals that skills are valued the highest closely followed by organizational capabilities. Setting up a multi-disciplinary team with motivated employees and giving this team the mandate to experiment with data, is essential when innovating with open data. Theoretically, this study contributes to open data research by offering a new capabilities perspective on the organizational level. Our results highlight the importance of entrepreneurship theories to explain value creation with open data. Practically, our study suggests that digital skills and start-ups are important to the open government data policies.

Little is known about the factors which influence the success or failure of open data initiatives. Based on the results of a workshop, we provide a list of success factors for open data publication and use (64 in total) and discuss their criticality in a particular setting using a case study (the ENGAGE project). The most critical success factors for open data publication and use, in the context of this case study, related to legislation, regulation and licenses. However,the criticality of factors depends considerably on the context of the open data initiative. Our key conclusions are that further work is needed to detail the success factors for open data publication and use in particular contexts, and that a number of success factors, such as those related to sustainability of publication process and user feedback, appear to be more universally applicable than others.

The timely, traceable and provenance-aware publication of Linked Open Data (LOD) is crucial for its success and to fulfill the vision of a global, decentralized, and machine-readable database of knowledge. Yet, the access to LOD is still fragmented and mainly centralized aggregations are being used, relying on complex harvesting mechanisms. As a remedy, we propose a blockchain-based approach enabling an integrated, traceable, and timely view on LOD. We use a blockchain to meet the organizational requirements of publishing LOD in a decentralized fashion while still supporting the sovereignty of the data providers and supporting provenance and proper integration into a harmonized knowledge graph. We present an approach and an implemented system that fulfills the requirements regarding volume and throughput and can be used as the foundation for practical deployments. We use Linked Open Government Data (LOGD) as our case study to demonstrate the feasibility of our approach. We developed a prototype to address the specific requirements of LOGD publication and apply the Practical Byzantine Fault Tolerance algorithm at its core to enable a robust state replication.

AURORAL is part of the EC's Open Research Data Pilot programme; therefore, the goal of this deliverable is to specify the terms for the project participation in that programme. As such, this deliverable presents the AURORAL Open Research Data Strategy and explains how AURORAL aims to provide open access to the publications and data generated by the project. The AURORAL open research data strategy is in line with the H2020 guidelines. Furthermore, the AURORAL Zenodo community will be the entry point for all the AURORAL open publications and data. ; This report is part of the AURORAL project that has received funding by the European Union's Horizon 2020 Programme under Grant Agreement number 101016854. The results of these deliverables reflect only the author's view and the Commission is not responsible for any use that may be made of the information it contains. These deliverables may be subject to final acceptance by the European Commission.

This article explores the opening and the free usage of stored public sector data, supplied by state. In the age of Open Government and Open Data it's not enough just to put data online. It should be rather weighed out whether, how and which supplied public sector data can be published. Open Data are defined as stored data which could be made accessible in a public interest without any restrictions for usage and distribution. These Open Data can possibly be statistics, geo data, maps, plans, environmental data and weather data in addition to materials of the parliaments, ministries and authorities. The preparation and the free access to existing data permit varied approaches to the reuse of data, discussed in the article. In addition, impulses can be given for Open Government – the opening of state and administration, to more transparency, participation and collaboration as well as to innovation and business development. The Open Data movement tries to get to the bottom of current publication processes in the public sector which could be formed even more friendly to citizens and enterprises.