Semantic data management in Smart Cities

2017 ◽  
Author(s):  
Mohamed Kettouch ◽  
Cristina Luca ◽  
Ouissem Khorief ◽  
Rui Wu ◽  
Sergiu Dascalu
Keyword(s):  
Data Management ◽  
Smart Cities ◽  
Semantic Data

M-SMDM: A model of security measures using Green Internet of Things with Cloud Integrated Data Management for Smart Cities

2021 ◽  
pp. 101802
Author(s):  
Amjad Rehman ◽  
Khalid Haseeb ◽  
Tanzila Saba ◽  
Hoshang Kolivand
Keyword(s):  
Internet Of Things ◽  
Data Management ◽  
Smart Cities ◽  
Security Measures

scholarly journals Stakeholders’ Viewpoints toward Blockchain Integration within IoT-Based Smart Cities

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Nada Alasbali ◽  
Saaidal Razalli Bin Azzuhri ◽  
Rosli Salleh
Keyword(s):  
Data Management ◽  
Smart City ◽  
Urban Landscape ◽  
Smart Cities ◽  
Pearson Correlation ◽  
Future Evolution ◽  
Mixed Method Design ◽  
Cross Tabulation ◽  
The Relationship ◽  
Structured Questionnaire

This study intends to assess the development of IoT-based smart cities industry and the possibilities of blockchain integration from the perspective of industry stakeholders as the vision for a modern, integrated smart city future is predicated upon intelligence and the relationship between data-rich connections and human activities. Although this ideal of an interconnected urban landscape is currently being tested and actively used by consumers spanning a range of connected nodes and service solutions, the scalability, interoperability, and security of this emergent cyber-physical ideal has yet to be adequately resolved. This study used an exploratory study design following a mixed method design approach. A structured questionnaire survey (quantitative) and interviews (qualitative) were conducted for collecting data. IBM SPSS was used for the analysis of the data, which computed descriptive statistics, cross-tabulation, Pearson correlation, and ANOVA for quantitative data and thematic analysis for qualitative data. Through an empirical assessment of the perceptions and expertise of 122 stakeholders from within the worldwide IoT smart city industry, conceptual support for blockchain integration into the IoT solution was acquired, highlighting the solution-oriented, system-centered advantages of a decentralised, autonomous data management backbone that could be applied to future IoT-based smart city solutions. To meet the broad and diversified needs of the smart city and its future evolution, this study has confirmed that a commitment to decentralisation and blockchain intermediary data management is critical to scalable, secure, and autonomous negotiations of the IoT-enabled smart city networks.

Features and Limitations of Ontologies for Coronavirus Data Management in Libraries

2021 ◽  
pp. 18-40
Author(s):  
Enrique Wulff
Keyword(s):  
Semantic Web ◽  
Data Management ◽  
Quality Criteria ◽  
Emerging Technology ◽  
Data Sources ◽  
Semantic Data ◽  
Important Quality ◽  
Selection For ◽  
Over Time ◽  
Or Applications

The purpose of this chapter is to follow the evolution of what has occurred over time in the ontologies published in response to the COVID-19 pandemic. Correctness and completeness of ontologies on the schema and instance level are important quality criteria in their selection for an application. To help both the librarians and the users, there is a need of a framework for the comparison of different semantic data sources in the COVID-19 pandemic. Meanwhile, online services and/or applications based on ontologies or SKOS-based COVID-19 thesauri are still rare. As an emerging technology in libraries, an all-integrating ontology for coronavirus disease knowledge and data refers to the continuing development of an existing technology. In spite of using ontologies in the Semantic Web, meanings of concepts and relationships are still largely unrealized in terms of obtaining accurate and timely information about COVID-19. But the nature of causal relationships on this disease is made accessible through ontologies as the material in which its main concepts are supported.

scholarly journals Expressing the Tacit Knowledge of a Digital Library System as Linked Data

Computers ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 49 ◽  
Author(s):  
Angela Di Iorio ◽  
Marco Schaerf
Keyword(s):  
Data Management ◽  
Tacit Knowledge ◽  
Digital Library ◽  
Linked Data ◽  
Data Publishing ◽  
Library System ◽  
Semantic Data ◽  
Digital Library System ◽  
Interpretation Process ◽  
Data Source

Library organizations have enthusiastically undertaken semantic web initiatives and in particular the data publishing as linked data. Nevertheless, different surveys report the experimental nature of initiatives and the consumer difficulty in re-using data. These barriers are a hindrance for using linked datasets, as an infrastructure that enhances the library and related information services. This paper presents an approach for encoding, as a Linked Vocabulary, the “tacit” knowledge of the information system that manages the data source. The objective is the improvement of the interpretation process of the linked data meaning of published datasets. We analyzed a digital library system, as a case study, for prototyping the “semantic data management” method, where data and its knowledge are natively managed, taking into account the linked data pillars. The ultimate objective of the semantic data management is to curate the correct consumers’ interpretation of data, and to facilitate the proper re-use. The prototype defines the ontological entities representing the knowledge, of the digital library system, that is not stored in the data source, nor in the existing ontologies related to the system’s semantics. Thus we present the local ontology and its matching with existing ontologies, Preservation Metadata Implementation Strategies (PREMIS) and Metadata Objects Description Schema (MODS), and we discuss linked data triples prototyped from the legacy relational database, by using the local ontology. We show how the semantic data management, can deal with the inconsistency of system data, and we conclude that a specific change in the system developer mindset, it is necessary for extracting and “codifying” the tacit knowledge, which is necessary to improve the data interpretation process.

Cloud-Based Semantic Data Management for the VPH-Share Medical Research Community

2014 ◽  
Author(s):  
Siegfried Benkner ◽  
Chris Borckholder ◽  
Yuriy Kaniovskyi Alfredo Saglimbeni ◽  
Tomas Pariente Lobo ◽  
Piotr Nowakowski ◽  
...  
Keyword(s):  
Data Management ◽  
Medical Research ◽  
Research Community ◽  
Semantic Data

Smart Cities: A Survey on Data Management, Security, and Enabling Technologies

2017 ◽  
Vol 19 (4) ◽  
pp. 2456-2501 ◽  
Author(s):  
Ammar Gharaibeh ◽  
Mohammad A. Salahuddin ◽  
Sayed Jahed Hussini ◽  
Abdallah Khreishah ◽  
Issa Khalil ◽  
...  
Keyword(s):  
Data Management ◽  
Smart Cities ◽  
Enabling Technologies

scholarly journals Privacy Protection in Smart Cities by a Personal Data Management Protocol in Blockchain

2020 ◽  
Vol 12 (3) ◽  
pp. 44-52
Author(s):  
Hossein Mohammadinejad ◽  
◽  
Fateme Mohammadhoseini
Keyword(s):  
Data Management ◽  
Privacy Protection ◽  
Smart Cities ◽  
Personal Data ◽  
Management Protocol

scholarly journals PREFACE

2018 ◽  
Vol IV-4/W7 ◽  
pp. 1-2
Author(s):  
C. Ellul ◽  
V. Coors ◽  
S. Zlatanova ◽  
R. Laurini ◽  
M. Rumor
Keyword(s):  
Decision Making ◽  
Data Management ◽  
Smart City ◽  
Spatial Information ◽  
Smart Cities ◽  
Citizen Engagement ◽  
Smart Data ◽  
The City ◽  
Urban Data

<p><strong>Abstract.</strong> Simply defined, a Smart City is a city overlaid by a digital layer, which is used for the governance of the city. A Smart City uses intelligent technology to enhance our quality of life in urban environments, bringing together people and data from disparate sources such as sensors, demographics, topographic and 3D mapping, Building Information Models and many more. Increasingly, Smart Cities use this data in a variety of ways, to address key challenges related to transportation, communications, air quality, noise, well-being of the citizens, decision making relating to education and health and urban planning, as well as in relation to initiatives such as startups and fostering economic growth and employment within the city. As more data becomes available, the challenges of storing, managing and integrating such data are also multiplied.</p><p> This increasing interest in Smart Cities world-wide, along with a growing understanding of the importance of integrating “Smart” data with other data and wider applications for the benefit of citizens, made the choice of hosting the third Smart Data, Smart Cities conference in Delft – in conjunction with three other conferences – a very natural one. Together the four conferences were held during the week of 1st–5th October 2018, and alongside SDSC participants were invited to attend the ISPRS Technical Commission IV Symposium, the 13th 3D GeoInfo Conference and the 6th International FIG Workshop on 3D Cadastres. Participant interaction – and the ability to attend sessions across the four events – was particularly encouraged. SDSC 2018 itself was organised by the Urban Data Management Society (UDMS www.udms.net), ISPRS and TU Delft (the Delft University of Technology), and Professor Volker Coors Chaired the SDSC committee.</p><p> As in previous years, three key conference themes were proposed to represent the Smart Cities: <b>Smart Data</b> (sensor network databases, on-the-fly data mining, geographic and urban knowledge modeling and engineering, green computing, urban data analytics and big data, big databases and data management), <b>Smart People</b> (volunteered information, systems for public participation) and <b>Smart Cities</b> (systems of territorial intelligence, systems for city intelligence management,3D modeling of cities, internet of things, social networks, monitoring systems, mobility and transportation, smart-city-wide telecommunications infrastructure, urban knowledge engineering, urban dashboard design and implementation, new style of urban decision-making systems, geovisualization devoted to urban problems, disaster management systems).</p><p> This volume consists of 18 papers, which were selected from 34 submissions on the basis of double blind review, with each paper being reviewed by a minimum of three reviewers. These papers present novel research concerning the use of spatial information and communication technologies in Smart Cities, addressing different aspects of Smart Data and Smart Citizens. The selected papers tackle different aspects of Smart Cities: 3D; Citizen Engagement; transport, sustainable mobility; dashboards and web GIS; citizen engagement and participation; sensors; urban decision making.</p><p> The editors are grateful to the members of the Scientific Committee for their time and valuable comments, which contributed to the high quality of the papers. Reviews were contributed by: Giorgio Agugiaro, Maria Antoniabrovelli, Ken Arroyoohori, Martina Baucic, Michela Bertolotto, Pawel Boguslawski, Azedine Boulmakoul, Caesar Cardenas, Ofelia Cervantes, Volker Coors, Isabel Cruz, Vincenzo Delfatto, Claire Ellul, Tarun Ghawana, Gesquiere Gilles, Gerhard Groeger, Eberhard Gulch, Jan-Henrik Haunert, Stephen Hirtle, Umit Isikdag, Martin Kada, Snjezana Knezic, Robert Laurini, Liu Liu, Ed Manley, Viviana Mascardi, Marco Minghini, Raul Monroy, Regina Motz, Beniamino Murgante, Marco Painho, Dev Paudyal, Alenka Poplin, Ivana Racetin, Ismail Rakip Karas, Preston Rodrigues, David Sol, Wei Tu, Wei Tu, Genoveva Vargas, Kavita Vemuri, Edward Verbree, Mingshu Wang, Maribel Yasminasantos, Sisi Zlatanova. We are also grateful to the work of the local organising committee at TU Delft, without whom this conference would not have been possible. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-4/W7, 2018 3rd International Conference on Smart Data and Smart Cities, 4–5 October 2018, Delft, The Netherlands</p>

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