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Data management

About: Data management is a research topic. Over the lifetime, 31574 publications have been published within this topic receiving 424326 citations.


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Journal ArticleDOI
TL;DR: Analysis and evaluations manifest that the proposed BlockTDM scheme provides a general, flexible, and configurable blockchain-based paradigm for trusted data management with tamper-resistance, which is suitable for edge computing with high-level security and creditability.
Abstract: With rapid development of computing technologies, large amount of data are gathered from edge terminals or Internet of Things (IoT) devices, however data trust and security in edge computing environment are very important issues to be considered, especially when the gathered data are fraud or dishonest, or the data are misused or spread without any authorization, which may lead to serious problems. In this article, a blockchain-based trusted data management scheme (called BlockTDM) in edge computing is proposed to solve the above problems, in which we proposed a flexible and configurable blockchain architecture that includes mutual authentication protocol, flexible consensus, smart contract, block and transaction data management, blockchain nodes management, and deployment. The BlockTDM scheme can support matrix-based multichannel data segment and isolation for sensitive or privacy data protection, and moreover, we have designed user-defined sensitive data encryption before the transaction payload stores in blockchain system, and have implemented conditional access and decryption query of the protected blockchain data and transactions through smart contract. Finally, we have evaluated the proposed BlockTDM scheme security, availability, and efficiency with large amount of experiments. Analysis and evaluations manifest that the proposed BlockTDM scheme provides a general, flexible, and configurable blockchain-based paradigm for trusted data management with tamper-resistance, which is suitable for edge computing with high-level security and creditability.

131 citations

Journal ArticleDOI
04 Nov 2013-PLOS ONE
TL;DR: The re3data.org project as mentioned in this paper provides an overview of the heterogeneous research data repositories (RDRs) and provides a typology of institutional, disciplinary, multidisciplinary and project-specific RDRs.
Abstract: Researchers require infrastructures that ensure a maximum of accessibility, stability and reliability to facilitate working with and sharing of research data. Such infrastructures are being increasingly summarized under the term Research Data Repositories (RDR). The project re3data.org–Registry of Research Data Repositories–has begun to index research data repositories in 2012 and offers researchers, funding organizations, libraries and publishers an overview of the heterogeneous research data repository landscape. In July 2013 re3data.org lists 400 research data repositories and counting. 288 of these are described in detail using the re3data.org vocabulary. Information icons help researchers to easily identify an adequate repository for the storage and reuse of their data. This article describes the heterogeneous RDR landscape and presents a typology of institutional, disciplinary, multidisciplinary and project-specific RDR. Further the article outlines the features of re3data.org, and shows how this registry helps to identify appropriate repositories for storage and search of research data.

131 citations

Patent
17 Jun 1997
TL;DR: In this paper, an attribute design database system provides for inventory management, order process management and design management in a telecommunications management network provisioning environment, which operates in a physical network management system that includes various telecommunications network management tools.
Abstract: An attribute design database system provides for inventory management, order process management and design management. The system operates in a telecommunications management network provisioning environment. It provides a physical network management system that includes various telecommunications network management tools. Graphical user interface facilitates the user's navigation of the database system to enable the same person to have access to and the ability to modify information in regards to inventory management, design management and order management for the network.

130 citations

Journal ArticleDOI
TL;DR: This paper presents the first Big Data based architecture for construction waste analytics, validated for exploratory analytics of 200,000 waste disposal records from 900 completed projects and revealed that existing waste management software classify the bulk of construction waste as mixed waste, which exposes poor waste data management.
Abstract: In recent times, construction industry is enduring pressure to take drastic steps to minimise waste. Waste intelligence advocates retrospective measures to manage waste after it is produced. Existing waste intelligence based waste management software are fundamentally limited and cannot facilitate stakeholders in controlling wasteful activities. Paradoxically, despite a great amount of effort, the waste being produced by the construction industry is escalating. This undesirable situation motivates a radical change from waste intelligence to waste analytics (in which waste is propose to be tackle proactively right at design through sophisticated big data technologies). This paper highlight that waste minimisation at design (a.k.a. designing-out waste) is data-driven and computationally intensive challenge. The aim of this paper is to propose a Big Data architecture for construction waste analytics. To this end, existing literature on big data technologies is reviewed to identify the critical components of the proposed Big Data based waste analytics architecture. At the crux, graph-based components are used: in particular, a graph database (Neo4J) is adopted to store highly voluminous and diverse datasets. To complement, Spark, a highly resilient graph processing system, is employed. Provision for extensions through Building Information Modelling (BIM) are also considered for synergy and greater adoption. This symbiotic integration of technologies enables a vibrant environment for design exploration and optimisation to tackle construction waste. The main contribution of this paper is that it presents, to the best of our knowledge, the first Big Data based architecture for construction waste analytics. The architecture is validated for exploratory analytics of 200,000 waste disposal records from 900 completed projects. It is revealed that existing waste management software classify the bulk of construction waste as mixed waste, which exposes poor waste data management. The findings of this paper will be of interest, more generally to researchers, who are seeking to develop big data based simulation tools in similar non-trivial applications.

130 citations

BookDOI
01 Jan 2016
TL;DR: Management of Information Technology in Health presents a very special challenge because it is an area that can be highly controversial and very costly, often with considerable dissatisfaction and with significant levels of failure.
Abstract: Management of Information Technology (IT) in Health presents a very special challenge. The IT industry itself is a very dynamic, rapidly evolving field, with a continuous stream of new technologies bringing new possibilities and challenges. However IT is not merely a technological issue, as it is generally found that many of the most difficult problems are about the way the technology relates to the organization. If technology is going to be effective in most cases, then substantial changes in the way the organization operates is necessary (Coombs et al 1992). These changes involve many conflicting factors which can be political, managerial, industrial, cultural, and may require substantial changes in skills, and roles. Implementation is much more than a technical process, and involves skills of politicians, salesmen, project management and organizational change agents (Keen 1991). It is an area that can be highly controversial and very costly, often with considerable dissatisfaction and with significant levels of failure (Sauer 1993). In addition to these problems, health is possibly one of the most complex of environments, which makes the management of information in the health industry extremely demanding.

130 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023218
2022485
2021959
20201,435
20191,745
20181,719