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ACM SIGMOD International Conference on Management of data (SIGMOD)

作者： Chatziantoniou, Damianos Kantere, Verena Athens Univ Econ & Business Athens Greece Natl Tech Univ Athens Athens Greece

ISBN: (纸本)9781450383431

A data Virtual Machine (DVM) is a novel graph-based conceptual model, similar to the entity-relationship model, representing existing data (persistent, transient, derived) of an organization. A DVM can be built quickly, agilely, offering schematic flexibility to data engineers. data scientists can visually define complex dataframe queries in an intuitive and simple manner, which are evaluated within an algebraic framework. A DVM can be easily materialized in any logical data model and can be "reoriented" around any node, offering a "single view of any entity". In this paper we demonstrate dataMingler, a tool implementing DVMs . We argue that DVMs can have a significant practical impact in analytics environments.

关键词： data virtualization data virtual machines

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Evolving Principles of Big data virtualization 20th

Evolving Principles of Big Data Virtualization

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20th International Conference on Computational Science and Its Applications (ICCSA)

作者： Bogadanov, Alexander Degtyarev, Alexander Shchegoleva, Nadezhda Khvatov, Valery Korkhov, Vladimir St Petersburg State Univ St Petersburg Russia DGT Technol AG Enschede Netherlands Plekhanov Russian Univ Econ 36 Stremyanny Per Moscow 117997 Russia

ISBN: (纸本)9783030588175;9783030588168

The fact that over 2000 programs exist for working with various types of data, including Big data, makes the issue of flexible storage a quintessential one. Storage can be of various types, including portals, archives, showcases, data bases of different varieties, data clouds and networks. They can have synchronous or asynchronous computer connections. Because the type of data is frequently unknown a priori, there is a necessity for a highly flexible storage system, which would allow to easily switch between various sources and systems. Combining the concept of virtual personal supercomputer with the classification of Big data that accounts for different storage schemes would solve this issue.

关键词： Big data data virtualization Virtual personal supercomputer data network data marketplaces

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Combating Dirty data using data virtualization 5

Combating Dirty Data using Data Virtualization

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IEEE 5th International Conference for Convergence in Technology (I2CT)

作者： Sawant, Omkar Vilas TIBCO SOFTWARE INC Global Prod Serv Mumbai Maharashtra India

ISBN: (纸本)9781538680759

data is the new Gold of the modern age. Organizational decisions, artificial intelligence, machine learning, time critical processes, analytics, etc. are driven by highly profiled data. data gives an organization the ability to act in a corresponding situation and hence, keep up with the market. Financial returns are directly associated with the quality of data being used. Today's world has experienced a data explosion with the advent of data sources like Hadoop, data lakes, clusters and many more. Even more, the day to day devices that we use collect data to present meaningful statistics to us. There is an exponential increase in data volumes which are characterized by heterogeneous data formats and disparate data sources which in turn is complicating the task of providing uniform and profiled data to the business users for analysis. Warehousing is also not able to cope up with the on-demand real-time data access. Holistic view of the entire data is extremely difficult to achieve and takes a considerable amount of time which is slowing down an organization's decision making capabilities. The complexity of the current systems has increased due to the interconnected nature of widely distributed systems which share data. Dirty data i.e. data which is inaccurate, inconsistent, unclean or incomplete is spread all across. As all the data is unrequired garbage data, there is no point in developing your business intelligence over this data. data Clarity used along with data virtualization provides an exceptional solution to these problems by handling the complex data workloads with respect to heterogeneous data and disparate data sources and provides a holistic view of the data to the business organization.

关键词： data virtualization data Intelligence Federated Query Engine data Clarity Active clusters data life-cycle management metadata management Extensible Style sheet Language Transformations disparate data sources Extraction Transformation and Loading

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A New ETL Approach Based on data virtualization

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Journal of Computer Science & Technology 2015年第2期30卷 311-323页

作者：郭树盛袁子牧孙傲冰岳强 State Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100190 China Cloud Computing Center Chinese Academy of Sciences Dongguan 523808 China

ETL （Extract-Transform-Load） usually includes three phases： extraction, transformation, and loading. In building data warehouse, it plays the role of data injection and is the most time-consuming activity. Thus it is necessary to improve the performance of ETL. In this paper, a new ETL approach, TEL （Transform-Extract-Load） is proposed. The TEL approach applies virtual tables to realize the transformation stage before extraction stage and loading stage, without data staging area or staging database which stores raw data extracted from each of the disparate source data systems. The TEL approach reduces the data transmission load, and improves the performance of query from access layers. Experimental results based on our proposed benchmarks show that the TEL approach is feasible and practical.

关键词： cloud computing big data ETL heterogeneous database data virtualization

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data virtualization for Coupling Command and Control (C2) and Combat Simulation Systems

Data Virtualization for Coupling Command and Control (C2) an...

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10th Chinese Conference on Image and Graphics Technologies and Applications (IGTA)

作者： Xu, Xiangzhong Yang, Jiandong Tang, Zaijiang Acad Armored Force Engn Simulat Ctr Beijing 100072 Peoples R China China Satellite Maritime Tracking & Control Ctr Nanjing 214431 Jiangsu Peoples R China

ISBN: (纸本)9783662477915;9783662477908

Nowadays, coupling Command and Control (C2) Systems with combat simulation systems becomes very important and data virtualization has not gained enough attention. The C2/M&S Interoperability Technical Reference Model (TRM) is briefly discussed, which divides data into three categories, viz. persistent data, non-persistent data and exercise control data. The heterogeneity of these data categories is analyzed and the component-based comprehensive data visualization approach for coupling C2 and combat simulation systems is proposed. The XTrain Federation is built to support commanders and staffs training which consists of the Army Tactical Command and Control System (ATCCS) and the Army Tactical Simulation System (ATSS). In this federation, ATSS generates dynamic track data that are exported to and displayed on the ATCCS as a common operational picture (COP);accordingly, train audiences inject actions/orders back into ATSS. Research results show data visualization plays a great role in the domain of coupling C2 with combat simulation systems.

关键词： Interoperability data virtualization Combat simulation Command and control (C2)

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virtualization of data to Improve Pedagogical Approaches the Case of Higher Education in Morocco in the Face of the COVID-19 Pandemic 14

Virtualization of Data to Improve Pedagogical Approaches the...

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14th International Conference on Computer Supported Education (CSEDU)

作者： Nanou, Ismail Akhasbi, Hassna Riyami, Bouchaib Labriji, El Houssine Univ Hassan 2 Fac Sci Lab Technol Informat & Modelisat LTIM Casablanca Morocco Inst Super Genie Appl IGA Casablanca Casablanca Morocco

ISBN: (纸本)9789897585623

The world in general and the educational community in particular will remember well the COVID-19 pandemic, which forced schools and educational institutions to close their doors and switch abruptly to distance teaching and learning where the success of the pedagogical continuity of the 2019/2020 academic year became a challenge of high importance. Students and teachers, mostly unprepared for the pedagogy supported by digital technology, have experienced great difficulties in assuming a quality pedagogical continuity. To this effect, the experience we are living, due to this pandemic, pushes us to rethink our pedagogical tools and practices as well as our technical devices set up, at a distance learning, via Information and Communication Technologies (ICT). In this context, it seems useful that these pedagogical activities, whatever the tools, techniques and platforms put in place, during this period of pandemic, should be able to be re-verified. To this end, a modelling based on five layers has been proposed, in order to analysis the feedbacks of the different actors participating in the learning process (students, teachers, and administrative agents), and this with the aim of proposing a data virtualization approach to help decision making and to improve the distance learning device and the different activities of the pedagogical approaches.

关键词： data virtualization Pedagogical Technology Approaches Higher Education COVID-19 Distance Learning Feedback and MOOC

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A systematic overview of data federation systems

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SEMANTIC WEB 2024年第1期15卷 107-165页

作者： Gu, Zhenzhen Corcoglioniti, Francesco Lanti, Davide Mosca, Alessandro Xiao, Guohui Xiong, Jing Calvanese, Diego Free Univ Bozen Bolzano Fac Comp Sci KRDB Res Ctr Bolzano Italy Univ Bergen Dept Informat Sci & Media Studies Bergen Norway Univ Oslo Dept Informat Oslo Norway Ontopic Srl Milan Italy Umea Univ Dept Comp Sci Umea Sweden

data federation addresses the problem of uniformly accessing multiple, possibly heterogeneous data sources, by mapping them into a unified schema, such as an RDF(S)/OWL ontology or a relational schema, and by supporting the execution of queries, like SPARQL or SQL queries, over that unified schema. data explosion in volume and variety has made data federation increasingly popular in many application domains. Hence, many data federation systems have been developed in industry and academia, and it has become challenging for users to select suitable systems to achieve their objectives. In order to systematically analyze and compare these systems, we propose an evaluation framework comprising four dimensions: (i) federation capabilities, i.e., query language, data source, and federation techniques;(ii) data security, i.e., authentication, authorization, auditing, encryption, and data masking;(iii) interface, i.e., graphical interface, command line interface, and application programming interface;and (iv) development, i.e., main development language, deployment, commercial support, open source, and release. Using this framework, we thoroughly studied 51 data federation systems from the Semantic Web and database communities. This paper shares the results of our investigation and aims to provide reference material and insights for users, developers and researchers selecting or further developing data federation systems.

关键词： data federation systems federated query answering data virtualization heterogeneous data integration system evaluation framework

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A hierarchical blockchain-enabled security-threat assessment architecture for IoV

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Digital Communications and Networks 2024年第4期10卷 1035-1047页

作者： Yuanni Liu Ling Pan Shanzhi Chen School of Cyber Security and Information Law Chongqing University of Posts and TelecommunicationsChongqing400065China State Key Laboratory of Wireless Mobile Communications China Academy of Telecommunication TechnologyBeijing100191China

In Internet of Vehicles(IoV),the security-threat information of various traffic elements can be exploited by hackers to attack vehicles,resulting in accidents,privacy ***,it is necessary to establish security-threat assessment architectures to evaluate risks of traffic elements by managing and sharing securitythreat ***,most assessment architectures process data in a centralized manner,causing delays in query *** address this issue,in this paper,a Hierarchical Blockchain-enabled Security threat Assessment Architecture(HBSAA)is proposed,utilizing edge chains and global chains to share *** addition,data virtualization technology is introduced to manage multi-source heterogeneous data,and a metadata association model based on attribute graph is designed to deal with complex data *** order to provide high-speed query service,the ant colony optimization of key nodes is designed,and the HBSAA prototype is also developed and the performance is *** results on the large-scale vulnerabilities data gathered from NVD demonstrate that the HBSAA not only shields data heterogeneity,but also reduces service response time.

关键词： Internet of vehicles Blockchain Edge computing data virtualization data service composition

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Intermediate triple table: A general architecture for virtual knowledge graphs

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KNOWLEDGE-BASED SYSTEMS 2025年 314卷

作者： Arenas-Guerrero, Julian Corcho, Oscar Perez, Maria S. Univ Politecn Madrid Madrid Spain

Virtual knowledge graphs (VKGs) have been widely applied to access relational data with a semantic layer by using an ontology in use cases that are dynamic in nature. However, current VKG techniques focus mainly on accessing a single relational database and remain largely unstudied for data integration with several heterogeneous data sources. To overcome this limitation, we propose intermediate triple table (ITT), a general VKG architecture to access multiple and diverse data sources. Our proposal is based on data shipping and addresses heterogeneity by adopting a schema-oblivious graph representation that intervenes between the sources and the queries. We minimize data computation by just materializing a relevant subgraph fora specific query. We employ star-shaped query processing and extend this technique to mapping candidate selection. For rapid materialization of the ITT, we apply a mapping partitioning technique to parallelize mapping execution, which also guarantees duplicate-free subgraphs and reduces memory consumption. We use SPARQL-to-SQL query translation to homogeneously evaluate queries over the ITT and execute them with an in-process analytical store. We implemented ITT on top of a knowledge graph materialization engine and evaluated it with two VKG benchmarks. The experimental results show that our proposal outperforms state-of-the-art techniques for complex graph queries in terms of execution time. It also decreases the number of timeouts although it uses more memory as a trade-off. The experiments also demonstrate the source independence of the architecture on a mixed distribution of data with SQL and document stores together with various file formats.

关键词： Virtual knowledge graph data integration Graph querying data virtualization Declarative mappings

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data-driven and On-Demand Conceptual Modeling 25th

Data-driven and On-Demand Conceptual Modeling

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25th International Conference on Big data Analytics and Knowledge Discovery (DaWaK)

作者： Chatziantoniou, Damianos Kantere, Verena Athens Univ Econ & Business Dept Management Sci & Technol Athens Greece Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada

ISBN: (纸本)9783031398308;9783031398315

The data infrastructure of an organization involves data stored in different models and systems, spreadsheets, files, data mining models, streams, even output of stand-alone programs. In many cases, it is necessary to build on demand, agilely a virtual schema on top of this data infrastructure. We propose a novel graph-based conceptual model, called data virtual machine (DVM), which is designed bottom-up. DVM nodes represent attribute domains and edges represent programs that (through their output) relate values between domains. The data engineer defines a collection of such programs - which can be done quickly, on demand - and the schema, a graph, is derived. This is the inverse process of traditional approaches, where the schema is a priori set and the data engineer designs how to "fit" existing data to this schema. In a DVM, nodes are entities and attributes at the same time, which is useful in many settings. In this paper we also formalize the translation of the relational model to DVM and we present an extended use case that showcases the novelty of the DVM model and the new capabilities it comes with.

关键词： data virtualization data-driven and on-demand modeling

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