4 research outputs found

    Open Data Diffusion for Service Innovation: An Inductive Case Study on Cultural Open Data Services

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    Information Systems research on Open Data has been primarily focused on its contribution to e-government inquiries, government transparency, and open government. Recently, Open Data has been explored as a catalyser for service innovation as a consequence of big claims around the potential of such initiatives in terms of additional value that can be injected into the worldwide economy. Subsequently, the Open Data Services academic conversation was structured (Lindman et al. 2013a). The research project presented in this paper is an interpretive case study that was carried out to explore the factors that influence the diffusion of Open Data for new service development. This paper contributes to this debate by providing an interpretive inductive case study (Walsham 1995) of a tourism company that successfully turned several city authorities’ raw open datasets into a set of valuable services. Results demonstrate that 16 factors and 68 related variables are the most relevant in the process of diffusion of open data for new service development. Furthermore, this paper demonstrates the suitability of Social Constructionism and interpretive case study research to inductively generate knowledge in this field

    Cloud Services Brokerage for Mobile Ubiquitous Computing

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    Recently, companies are adopting Mobile Cloud Computing (MCC) to efficiently deliver enterprise services to users (or consumers) on their personalized devices. MCC is the facilitation of mobile devices (e.g., smartphones, tablets, notebooks, and smart watches) to access virtualized services such as software applications, servers, storage, and network services over the Internet. With the advancement and diversity of the mobile landscape, there has been a growing trend in consumer attitude where a single user owns multiple mobile devices. This paradigm of supporting a single user or consumer to access multiple services from n-devices is referred to as the Ubiquitous Cloud Computing (UCC) or the Personal Cloud Computing. In the UCC era, consumers expect to have application and data consistency across their multiple devices and in real time. However, this expectation can be hindered by the intermittent loss of connectivity in wireless networks, user mobility, and peak load demands. Hence, this dissertation presents an architectural framework called, Cloud Services Brokerage for Mobile Ubiquitous Cloud Computing (CSB-UCC), which ensures soft real-time and reliable services consumption on multiple devices of users. The CSB-UCC acts as an application middleware broker that connects the n-devices of users to the multi-cloud services. The designed system determines the multi-cloud services based on the user's subscriptions and the n-devices are determined through device registration on the broker. The preliminary evaluations of the designed system shows that the following are achieved: 1) high scalability through the adoption of a distributed architecture of the brokerage service, 2) providing soft real-time application synchronization for consistent user experience through an enhanced mobile-to-cloud proximity-based access technique, 3) reliable error recovery from system failure through transactional services re-assignment to active nodes, and 4) transparent audit trail through access-level and context-centric provenance

    An infrastructure for context-dependent RDF data replication on mobile devices

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    Der im Rahmen dieser Arbeit vorgestellte Ansatz beschreibt die Erstellung einer technischen Infrastruktur, die selektiv RDF-Daten in Abhängigkeit der Informationsbedürfnisse und den unterschiedlichen Kontexten mobiler Nutzer auf ein mobiles Endgerät repliziert und diese somit in intelligenter Art und Weise unterstützt. Eine Zusammenführung kontextspezifischer Konzepte und semantischer Technologien stellt einen wesentlichen Bestandteil zur Verbesserung der mobilen Informationssuche dar und erhöht gleichzeitig die Präzision mobiler Informationsgewinnungsprozesse. Trotz des vorhandenen Potentials einer proaktiven, kontextabhängigen Replizierung von RDF-Daten, gestaltet sich die Verarbeitung auf mobilen Endgeräten schwierig. Die Gründe dafür liegen in den technischen und netzwerkspezifischen Beschränkungen, in der fehlenden Verarbeitungs- und Verwaltungsfunktionalität von ontologiebasierten Beschreibungsverfahren sowie in der Unzulänglichkeit bestehender Replikationsansätze, sich an verändernde Informationsbedürfnisse sowie an unterschiedliche technische, umgebungsspezifische und infrastrukturbezogene Eigenheiten anzupassen. Verstärkt wird diese Problematik durch das Fehlen ausdrucksstarker Beschreibungsverfahren zur Repräsentation kontextspezifischer Daten. Existierende Ansätze leiden dementsprechend unter der Verwendung proprietärer Datenformate, dem Einsatz serverabhängiger Applikationsinfrastrukturen sowie dem Unvermögen, kontextspezifische Daten auszutauschen. Dies äußert sich in Studien, welche die Berücksichtigung der Informationsbedürfnisse mobiler Nutzer als unzureichend einstuft und einen Großteil der benötigten Informationen als kontextrelevant auszeichnet. Obgleich Fortschritte bei der Adaption von semantischen Technologien und Beschreibungsverfahren zur kontextabhängigen Verarbeitung zu erkennen sind, bleibt eine auf semantische Technologien basierende, proaktive Replizierung von RDF-Daten auf mobile Endgeräte ein offenes Forschungsfeld. Die vorliegende Arbeit diskutiert Möglichkeiten zur Erweiterung der mobilen, kontextspezifischen Datenverarbeitung durch semantische Technologien und beinhaltet eine vergleichende Studie zur Leistungsfähigkeit aktueller mobiler RDF-Frameworks. Kernpunkt ist die formale Beschreibung eines abstrakten Modells zur effizienten Akquise, Repräsentation, Verwaltung und Verarbeitung von Kontextinformationen unter Berücksichtigung der technischen Gegebenheiten mobiler Informationssysteme. Ergänzt wird es durch die formale Spezifikation eines nebenläufigen, transaktionsbasierten Verarbeitungsmodells, welches Vollständigkeits- und Konsistenzbedingungen auf Daten- und Prozessebene berücksichtigt. Der praktische Nutzen des vorliegenden Ansatzes wird anhand typischer Informationsbedürfnisse eines Wissensarbeiters demonstriert. Der Ansatz reduziert Abhängigkeiten zu externen Systemen und ermöglicht Nutzern, unabhängig von zeitlichen, örtlichen und netzwerkspezifischen Gegebenheiten, auf die für sie relevanten Daten zuzugreifen und diese zu verarbeiten. Durch die lokale Verarbeitung kontextbezogener Daten wird sowohl die Privatssphäre des Nutzers gewahrt als auch sicherheitsrelevanten Aspekten Rechnung getragen.This work describes an infrastructure for the selective RDF data replication to mobile devices while considering current and future information needs of mobile users and the different contexts they are operating in. It presents a novel approach in synthesizing context-aware computing concepts with semantic technologies and distributed transaction management concepts for intelligently assisting mobile users while enhancing mobile information seeking behavior and increasing the precision of mobile information retrieval processes. Despite the huge potential of a proactive, context-dependent replication of RDF data, such data can not be efficiently processed on mobile devices due to (i) technical limitations and network-related constraints, (ii) missing processing and management capabilities of ontology-based description frameworks, (iii) the inability of traditional data replication strategies to adapt to changing user information needs and to consider technical, environmental, and infrastructural restrictions of mobile operating systems, and (iv) the dynamic and emergent nature of context, which requires flexible and extensible description frameworks that allow for elaborating on the semantics of contextual constellations as well as on the relationships that exist between them. As a consequence, existing approaches suffer from the deployment of proprietary data formats, server-dependent application infrastructures, and the inability to share and exchange contextual information across system borders. Moreover, results of recently conducted studies reveal that mobile users find their information needs inadequately addressed, where a large share can be attributed as context or context-relevant. Although progress has been made in applying semantic technologies, concepts, and languages to the domain of context-aware computing, a synthesis of those fields for the proactive provision of RDF data replicas on mobile devices remains an open research issue. This work discusses possible fields where context-aware computing can be enhanced using technologies, languages, and concepts from the Semantic Web and contains a comparative study about the performance of current mobile RDF frameworks in replication-specific tasks. The main contribution of this thesis is a formal description of an abstract model that allows for an efficient acquisition, representation, management, and processing of contextual information while taking into account the peculiarities and operating environments of mobile information systems. It is complemented by a formal specification of a concurrently operating transaction-based processing model that considers completeness and consistency requirements on data and process level. We demonstrate the practicability of the presented approach trough a prototypical implementation of context and data providers that satisfy typical information needs of a mobile knowledge worker. As a consequence, dependencies to external systems are reduced and users are equipped with relevant information that adheres to their information needs anywhere and at any time, independent of any network-related constraints. Since context-relevant data are processed directly on a mobile device, security and privacy issues are preserved
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