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A Grid-based graph data model for Pedestrian Route Analysis in a Micro-spatial Environment

International Journal of Automation and computing 2016年第3期13卷 296-304页

作者： Yi-Quan Song Lei Niu Long He Rui Wang College of Urban and Environmental Science Tianjin Normal University School of Surveying Engineering Henan University of Urban Construction

Due to limitations in geometric representation and semantic description, the current pedestrian route analysis models are inadequate. To express the geometry of geographic entities in a micro-spatial environment accurately, the concept of a grid is presented, and grid-based methods for modeling geospatial objects are described. The semantic constitution of a building environment and the methods for modeling rooms, corridors, and staircases with grid objects are described. Based on the topology relationship between grid objects, a grid-based graph for a building environment is presented, and the corresponding route algorithm for pedestrians is proposed. The main advantages of the graph model proposed in this paper are as follows： 1） consideration of both semantic and geometric information, 2） consideration of the need for accurate geometric representation of the micro-spatial environment and the efficiency of pedestrian route analysis, 3） applicability of the graph model to route analysis in both static and dynamic environments, and 4） ability of the multi-hierarchical route analysis to integrate the multiple levels of pedestrian decision characteristics, from the high to the low, to determine the optimal path.

关键词： graph data model route analysis pedestrian micro-spatiM environment building.

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QMDS: a file system metadata management service supporting a graph data model-based query language

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INTERNATIONAL JOURNAL OF PARALLEL EMERGENT AND DISTRIBUTED SYSTEMS 2013年第2期28卷 159-183页

作者： Ames, Sasha Gokhale, Maya Maltzahn, Carlos Univ Calif Santa Cruz Comp Sci Dept Santa Cruz CA 95064 USA Lawrence Livermore Natl Lab Livermore CA 94550 USA

File system metadata management has become a bottleneck for many data-intensive applications that rely on high-performance file systems. Part of the bottleneck is due to the limitations of an almost 50-year-old interface standard with metadata abstractions that were designed at a time when high-end file systems managed less than 100 MB. Today's high-performance file systems store 7-9 orders of magnitude more data, resulting in a number of data items for which these metadata abstractions are inadequate, such as directory hierarchies unable to handle complex relationships among data. Users of file systems have attempted to work around these inadequacies by moving application-specific metadata management to relational databases to make metadata searchable. Splitting file system metadata management into two separate systems introduces inefficiencies and systems management problems. To address this problem, we propose QMDS: a file system metadata management service that integrates all file system metadata and uses a graph data model with attributes on nodes and edges. Our service uses a query language interface for file identification and attribute retrieval. We present our metadata management service design and architecture and study its performance using a text analysis benchmark application. Results from our QMDS prototype show the effectiveness of this approach. Compared to the use of a file system and relational database, the QMDS prototype shows superior performance for both ingest and query workloads.

关键词： graph data model query language metadata management

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A graph data model-based Micro-Provenance Approach for Multi-level Provenance Exploration in End-to-End Climate Workflows

A Graph Data Model-based Micro-Provenance Approach for Multi...

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2023 IEEE International Conference on Big data, Bigdata 2023

作者： Fiore, Sandro Rampazzo, Mattia Elia, Donatello Sacco, Ludovica Antonio, Fabrizio Nassisi, Paola University of Trento Department of Information Engineering and Computer Science Trento Italy Cmcc Foundation Advanced Scientific Computing Division Lecce Italy

ISBN: (纸本)9798350324457

Open Science is a vital part in the current and future research agenda worldwide. In order to meet Open Science goals, it is of paramount importance to fully support the research process, which includes also properly addressing provenance and reproducibility of scientific experiments. Indeed, provenance and reproducibility are two key requirements for analytics workflows in Open Science contexts. Handling provenance at different levels of granularity and during the entire experiment lifecycle becomes key to properly and flexibly managing lineage information related to large-scale experiments as well as enabling reproducibility scenarios. To this end, this work introduces the micro-provenance concept, and it provides an in-depth description of its design, implementation and exploitation in the context of a multi-model climate analytics workflow. © 2023 IEEE.

关键词： climate domain graph data model micro-provenance Open Science reproducibility

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GDM： A New graph Based data model Using Functional Abstractionx

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Journal of Computer Science & Technology 2006年第3期21卷 430-438页

作者： Sankhayan Choudhury Nabendu Chaki Swapan Bhattacharya Department of Computer Science and Engineering University of Calcutta India Department of Computer Science and Engineering Jadavpur University India

In this paper, a graph-based semantic data model （GDM） is proposed with the primary objective of bridging the gap between the human perception of an enterprise and the needs of computing infrastructure to organize information in some particular manner for efficient storage and retrieval. The graph data model （GDM） has been proposed as an alternative data model to combine the advantages of the relational model with the positive features of semantic data models. The proposed GDM offers a structural representation for interacting to the designer, making it always easy to comprehend the complex relations amongst basic data items. GDM allows an entire database to be viewed as a graph （V, E） in a layered organization. Here, a graph is created in a bottom up fashion where V represents the basic instances of data or a functionally abstracted module, called primary semantic group （PSG） and secondary semantic group （SSG）. An edge in the model implies the relationship among the secondary semantic groups. The contents of the lowest layer are the semantically grouped data values in the form of primary semantic groups. The SSGs are nothing but the higher-level abstraction and are created by the method of encapsulation of various PSGs, SSGs and basic data elements. This encapsulation methodology to provide a higher-level abstraction continues generating various secondary semantic groups until the designer thinks that it is sufficient to declare the actual problem domain. GDM, thus, uses standard abstractions available in a semantic data model with a structural representation in terms of a graph. The operations on the data model are formalized in the proposed graph algebra. A graph Query Language （GQL） is also developed, maintaining similarity with the widely accepted user-friendly SQL. Finally, the paper also presents the methodology to make this GDM compatible with the distributed environment, and a corresponding query processing technique for distributed environment is also sugg

关键词： graph data model semantic group semantic data model distributed database fragmentation and allocation schema

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Integrating graph data models in Advanced Water Resource Management: A New Paradigm for Complex Hydraulic Systems

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WATER 2025年第1期17卷 3-3页

作者： Qiao, Jiabin Shen, Keyan Xiao, Wenzhe Tang, Jiarun Chen, Yurun Xu, Jing China Yangtze Power Co Ltd Hubei Key Lab Intelligent Yangtze & Hydroelect Sci Yichang 443000 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Elect Informat & Commun Wuhan 430074 Peoples R China

The efficient management of water resources is crucial due to increasing environmental and societal pressures, requiring advanced data handling capabilities. Traditional relational data models, while foundational, struggle to capture the complex relationships inherent in water systems, limiting analytical and decision-making effectiveness. To address these challenges, this paper proposes a comprehensive graph data model for water resource management. Our model includes conceptual, logical, and physical frameworks that enable the structured representation of hydraulic objects and their relationships. We categorize hydraulic objects, examine their spatial, structural, and operational interconnections, and construct an adaptable graph data model. This model provides the enhanced integration, mining, and analysis of hydraulic data, supporting intelligent, data-driven water management applications. Example applications demonstrate the model's utility in improving watershed management, hydropower scheduling, and uncovering latent relationships among hydraulic components through graph neural networks. This work establishes a robust data foundation for the sustainable and scientific management of water resources.

关键词： water resource management hydraulic systems data modeling graph data model

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Design graph Multi-Dimensional data model of a data Warehouse and conversion of its equivalent Object - Oriented Schema

Design Graph Multi-Dimensional Data Model of a Data Warehous...

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18th IEEE Symposium on Computers and Communications (ISCC)

作者： Rahim, Sk. Abdul Chakraborty, Baisakhi Debnath, Joyati Debnath, Narayan Bengal Coll Engn & Technol Durgapur India Natl Inst Technol Durgapur India Winona State Univ Winona MN 55987 USA

ISBN: (纸本)9781479937554

This paper proposes graph Multi -Dimensional data model (GMDDM) of a data Warehouse and conversion of its equivalent Object - Oriented Schema. data warehouse representation is complex itself. Thus the pictorial representation of the data Warehouse should increase the understandability to the warehouse designer. The warehouse representation through graph G [V, E] may be an effective approach that reduces the inherent complexity of any multi - dimensional data model. But there is no need to develop this model from scratch, rather, in contrast, it may be considered as a software layer on the top of any standard data model representation. Here the scope of the project work is to form a software tool that is able to convert the graph based data Warehouse representation to its equivalent Object - Oriented representation. Hence the tool helps the warehouse designer to interact with the graph without knowing anything about Object - Oriented representation and thus ease the entire complex design mechanism. The project work contains a detailed graph based representation of an Online Shopping House and its equivalent Object - Oriented Schema. It also provides the generic rules for conversion of any graph based representation to Object - Oriented Schema.

关键词： graph Multi -Dimensional data model (GMDDM) Object - Oriented Schema Warehouse Designer Software Layer Software Tool graph data model

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graph - semantic based web data model: Conceptual design to logical representation

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2011年第1_suppl期11卷 S77-S88页

作者： Sanyal, Abhijit Sarkar, Anirban Choudhury, Sankhayan Bae, Wan D. IBM India Pvt Ltd Kolkata India Natl Inst Technol Dept Comp Applicat Durgapur India Univ Calcutta Dept Comp Sci & Engn Kolkata India Univ Wisconsin Stout Math Stat & Comp Sci Menomonie WI USA

Real life web based information system is complex due to the presence of hypertext and semi-structured hierarchical data. This paper proposes a graph-semantic based web data model called, EGDM, to conceptualize the web based information system in a better way. Design of such complex system not only demands a strong conceptual model with high degree of understandability but a proper methodological support for the designer is also needed to specify the system at logical level. In this context, this paper also proposed an Object Specification Language for EGDM (OSLE). It allows converting the conceptual level design with graphical notation to its equivalent logical level Object model in terms of classes and class hierarchies. The proposed OSLE based Class templates of object model are platform independent. Moreover, we have proposed an rule based approach for mapping the OSLE based class templates to product dependent Object Relational (OR) model for the ease of implementation.

关键词： Web data model conceptual model graph data model semi-structured data object orientation object model

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Operational Algebra for a graph Based Semantic Web data model

Operational Algebra for a Graph Based Semantic Web Data Mode...

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10th International Conference on Computer Information Systems and Industrial Management Applications (CISIM 2011)

作者： Sanyal, Abhijit Choudhury, Sankhayan IBM India Pvt Ltd Kolkata India Univ Calcutta Kolkata India

ISBN: (纸本)9783642272448

An operational algebra with formal definition is necessary for any conceptual data model for smooth data retrieval. We have already proposed a graph-based aspect-oriented data model for a web based application, called 'Semantic graph data model' (SGDM) [7]. The proposed model aims to represent the semantic within data in a web based application in an efficient way. SGDM should be supported by an operational algebra for retrieval of data. In this paper, we have proposed a graph based algebra that consists of semantic and non-semantic operators for the evaluation of a semantic query within SGDM. The proposed operators of SGDM are being implemented in a way such that the corresponding object relational operators are being executed on the equivalent object relational data model to offer a doable solution for the end users.

关键词： Operational Algebra Semantic Web data model graph data model Query Processing

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Design of a data model for social network applications

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JOURNAL OF dataBASE MANAGEMENT 2007年第4期18卷 51-79页

作者： Mitra, Susanta Bagchi, Aditya Bandyopadhyay, A. K. IIIT Kolkata India Indian Stat Inst Comp & Stat Serv Ctr Kolkata India Jadavpur Univ Dept Elect & Telecommun Engn Kolkata 700032 W Bengal India

A social network defines the structure of a social community like an organization or institution, covering its members and their inter-relationships. Social relationships among the members of a community can be of different types like friendship, kinship, professional, academic, and so forth. Traditionally, a social network is represented by a directed graph. Analysis of graph structure representing a social network is done by the sociologists to study a community. Hardly any effort has been made to design a data model to store and retrieve social-network-related data. In this paper, an object-relational graph data model has been proposed for modeling a social network. The objective is to illustrate the power of this generic model to represent the common structural and node-based properties of different social network applications. A novel, multi-paradigm architecture has been proposed to efficiently manage the system. New structural operators have been defined in the paper and the application of these operators has been illustrated through query examples. The completeness and the minimality of the operators have also been shown.

关键词： graph data model multi-paradigm architecture object-relational data model social network

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An Advanced Search System to Manage SARS-CoV-2 and COVID-19 data Using a model-Driven Development Approach

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IEEE ACCESS 2022年 10卷 43528-43534页

作者： Leon, A. Garcia Simon, A. Pastor, O. Univ Politecn Valencia Valencian Res Inst Artificial Intelligence VRAIN E-46022 Valencia Spain

The pandemic outbreak of COVID-19 has allowed the proliferation of an unprecedented amount of data that must be organized and connected in a way that allows its efficient management. Nevertheless, the speed at which all of this knowledge is being generated has highlighted the shortcomings of the research community in creating well-organized, standardized, and structured databases. Despite the efforts of the community to develop advanced integrative platforms such as Covidgraph, we have identified some limitations when using these solutions that we think are derived from the lack of a sound ontological schema to guide the collection, standardization, and integration of data. This work explores the advantages and disadvantages for the final user of building advanced information systems using a model Driven Development approach to integrate heterogeneous and complex data using an ontological background as a basis. As a proof of concept, we built a database (CovProt) to integrate data about different aspects of SARS-CoV-2 using this approach, we analyzed the advantages and disadvantages of using this approach compared to Covidgraph by performing a set of queries in CovProt and Covidgraph, and finally, we compared the structure and redundancy of the retrieved data.

关键词： databases COVID-19 data models Proteins Coronaviruses Unified modeling language Soft sensors Conceptual model graph data model MDD COVID-19 design methods

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