Human Centric Data Representation: From Fuzzy Relational Databases into Fuzzy XML

2010 ◽  
pp. 55-77 ◽  
Author(s):  
Keivan Kianmehr ◽  
Tansel Özyer ◽  
Anthony Lo ◽  
Jamal Jida ◽  
Alnaar Jiwani ◽  
...  
Keyword(s):  
Relational Databases ◽  
Data Representation ◽  
Fuzzy Xml

SEDRIS Transmittal Storing and Retrieval System using Relational Databases

2014 ◽  
Vol 25 (4) ◽  
pp. 38-65
Author(s):  
Yongkwon Kim ◽  
Heejung Yang ◽  
Chin-Wan Chung
Keyword(s):  
Complex Systems ◽  
Relational Database ◽  
Relational Databases ◽  
Data Representation ◽  
Environmental Data ◽  
Natural Phenomena ◽  
Type Conversion ◽  
Weather System ◽  
Relational Database System ◽  
Efficient Management

Modeling and simulation (M&S) are widely used for design, analysis, and optimization of complex systems and natural phenomena in various areas such as the defense industry and the weather system. In many cases, the environment is a key part of complex systems and natural phenomena. It includes physical aspects of the real world which provide the context for a specific simulation. Recently, several simulation systems are integrated to work together when they have needs for exchanging information. Interoperability of heterogeneous simulations depends heavily on sharing complex environmental data in a consistent and complete manner. SEDRIS (Synthetic Environmental Data Representation and Interchange Specification) is an ISO standard for representation and interchange of environmental data and widely adopted in M&S area. As the size of the simulation increases, the size of the environmental data which should be exchanged between simulations increases. Therefore, an efficient management of the environmental data is very important. In this paper, the authors propose storing and retrieval methods of SEDRIS transmittals using a relational database system in order to be able to retrieve data efficiently in the environmental data server cooperating with many heterogeneous distributed simulations. By analyzing the structure and the content of SEDRIS transmittals, relational database schemas are designed. To reduce query processing time of SEDRIS transmittals, direct storing and retrieval methods which do not require the type conversion of SEDRIS transmittals are proposed. Experimental analyses are conducted to show the efficiency of the proposed approach. The results confirm that the proposed approach greatly reduces the storing time and retrieval time compared to comparison approaches.

Hybridation of Labeling Schemes for Efficient Dynamic Updates

2016 ◽  
Vol 4 (1) ◽  
pp. 184 ◽  
Author(s):  
Su Cheng Haw ◽  
Samini Subramaniam ◽  
Wei Siang Lim ◽  
Fang Fang Chua
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Data Representation ◽  
Xml Database ◽  
Extended Range ◽  
Database Technology ◽  
Wise Choice ◽  
Labeling Scheme ◽  
Dynamic Updates ◽  
Mapping Scheme

<p>With XML as the leading standard for data representation over the Web, it is crucial to store and query XML data. However, relational databases are the dominant database technology in most organizations. Thus, replacing relational database with a pure XML database is not a wise choice. One most prominent solution is to map XML into relational database. This paper introduces a robust labeling scheme which is a hybrid labeling scheme combining the beauty features of extended range and ORDPATH schemes to supports dynamic updates. In addition, we also proposed a mapping scheme based on the hybrid labeling scheme. Our proposed approach is evaluated in terms of (i) loading time, (ii) storage size, (iii) query retrieval time, and (iv) dynamic updates time, as compared to ORDPATH and ME schemes. The experimental evaluation results shows that our proposed approach is scalable to support huge datasets and dynamic updates.</p>

Storing and querying fuzzy XML data in relational databases

2013 ◽  
Vol 39 (2) ◽  
pp. 386-396 ◽  
Author(s):  
Jian Liu ◽  
Z. M. Ma ◽  
Xue Feng
Keyword(s):  
Relational Databases ◽  
Xml Data ◽  
Fuzzy Xml

scholarly journals Transforming data-centric eXtensible markup language into relational databases using hybrid approach

2021 ◽  
Vol 10 (6) ◽  
pp. 3256-3264
Author(s):  
Su-Cheng Haw ◽  
Emyliana Song
Keyword(s):  
Relational Databases ◽  
Hybrid Approach ◽  
Data Representation ◽  
Extensible Markup Language ◽  
Markup Language ◽  
Seamless Integration ◽  
Structural Relationships ◽  
Extensible Markup ◽  
Core Framework ◽  
Labelling Scheme

eXtensible markup language (XML) appeared internationally as the format for data representation over the web. Yet, most organizations are still utilising relational databases as their database solutions. As such, it is crucial to provide seamless integration via effective transformation between these database infrastructures. In this paper, we propose XML-REG to bridge these two technologies based on node-based and path-based approaches. The node-based approach is good to annotate each positional node uniquely, while the path-based approach provides summarised path information to join the nodes. On top of that, a new range labelling is also proposed to annotate nodes uniquely by ensuring the structural relationships are maintained between nodes. If a new node is to be added to the document, re-labelling is not required as the new label will be assigned to the node via the new proposed labelling scheme. Experimental evaluations indicated that the performance of XML-REG exceeded XMap, XRecursive, XAncestor and Mini-XML concerning storing time, query retrieval time and scalability. This research produces a core framework for XML to relational databases (RDB) mapping, which could be adopted in various industries.

scholarly journals Deepint.net: A Rapid Deployment Platform for Smart Territories

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 236 ◽  
Author(s):  
Juan M. Corchado ◽  
Pablo Chamoso ◽  
Guillermo Hernández ◽  
Agustín San Roman Gutierrez ◽  
Alberto Rivas Camacho ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Relational Databases ◽  
Smart Cities ◽  
Data Representation ◽  
Intelligent Sensors ◽  
Intelligence Models ◽  
Artificial Intelligence Models ◽  
Decision Making Processes ◽  
Processing Techniques ◽  
New Applications

This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques.

SEDRIS Transmittal Storing and Retrieval System Using Relational Databases

2016 ◽  
pp. 855-877
Author(s):  
Yongkwon Kim ◽  
Heejung Yang ◽  
Chin-Wan Chung
Keyword(s):  
Complex Systems ◽  
Relational Database ◽  
Relational Databases ◽  
Data Representation ◽  
Environmental Data ◽  
Natural Phenomena ◽  
Type Conversion ◽  
Weather System ◽  
Relational Database System ◽  
Efficient Management

Modeling and simulation (M&S) are widely used for design, analysis, and optimization of complex systems and natural phenomena in various areas such as the defense industry and the weather system. In many cases, the environment is a key part of complex systems and natural phenomena. It includes physical aspects of the real world which provide the context for a specific simulation. Recently, several simulation systems are integrated to work together when they have needs for exchanging information. Interoperability of heterogeneous simulations depends heavily on sharing complex environmental data in a consistent and complete manner. SEDRIS (Synthetic Environmental Data Representation and Interchange Specification) is an ISO standard for representation and interchange of environmental data and widely adopted in M&S area. As the size of the simulation increases, the size of the environmental data which should be exchanged between simulations increases. Therefore, an efficient management of the environmental data is very important. In this paper, the authors propose storing and retrieval methods of SEDRIS transmittals using a relational database system in order to be able to retrieve data efficiently in the environmental data server cooperating with many heterogeneous distributed simulations. By analyzing the structure and the content of SEDRIS transmittals, relational database schemas are designed. To reduce query processing time of SEDRIS transmittals, direct storing and retrieval methods which do not require the type conversion of SEDRIS transmittals are proposed. Experimental analyses are conducted to show the efficiency of the proposed approach. The results confirm that the proposed approach greatly reduces the storing time and retrieval time compared to comparison approaches.

Closing the Gap Between XML and Relational Database Technologies

2010 ◽  
pp. 1-27
Author(s):  
Mary Ann Malloy ◽  
Irena Mlynkova
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Database Systems ◽  
Data Representation ◽  
Xml Data ◽  
Advantages And Disadvantages ◽  
Closing The Gap ◽  
Relational Database Systems ◽  
Xml Technologies

As XML technologies have become a standard for data representation, it is inevitable to propose and implement efficient techniques for managing XML data. A natural alternative is to exploit tools and functions offered by relational database systems. Unfortunately, this approach has many detractors, especially due to inefficiency caused by structural differences between XML data and relations. But, on the other hand, relational databases represent a mature, verified and reliable technology for managing any kind of data including XML documents. In this chapter, the authors provide an overview and classification of existing approaches to XML data management in relational databases. They view the problem from both state-of-the-practice and state-of-the-art perspectives. The authors describe the current best known solutions, their advantages and disadvantages. Finally, they discuss some open issues and their possible solutions.

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