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XML Based Data Cube and X-OLAP 认领 引用 被引量：2
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作者 王晓玲 董逸生 《Journal of Southeast University(English Edition)》 CAS 2001年第2期5-9,共5页
Data warehouse provides storage and management for mass data, but data schema evolves with time on. When data schema is changed, added or deleted, the data in data warehouse must comply with the changed data schema, s... Data warehouse provides storage and management for mass data, but data schema evolves with time on. When data schema is changed, added or deleted, the data in data warehouse must comply with the changed data schema, so data warehouse must be re organized or re constructed, but this process is exhausting and wasteful. In order to cope with these problems, this paper develops an approach to model data cube with XML, which emerges as a universal format for data exchange on the Web and which can make data warehouse flexible and scalable. This paper also extends OLAP algebra for XML based data cube, which is called X OLAP.  展开更多
关键词 data warehouse data cube XML X OLAP semi structured data
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Fast Computation of Sparse Data Cubes with Constraints 认领 引用 被引量：2
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作者 FengYu-cai ChenChang-qing FengJian-lin XiangLong-gang 《Wuhan University Journal of Natural Sciences》 EI CAS 2004年第2期167-172,共6页
For a data cube there are always constraints between dimensions or among attributes in a dimension, such as functional dependencies. We introduce the problem that when there are functional dependencies, how to use the... For a data cube there are always constraints between dimensions or among attributes in a dimension, such as functional dependencies. We introduce the problem that when there are functional dependencies, how to use them to speed up the computation of sparse data cubes. A new algorithm CFD (Computation by Functional Dependencies) is presented to satisfy this demand. CFD determines the order of dimensions by considering cardinalities of dimensions and functional dependencies between dimensions together, thus reduce the number of partitions for such dimensions. CFD also combines partitioning from bottom to up and aggregate computation from top to bottom to speed up the computation further. CFD can efficiently compute a data cube with hierarchies in a dimension from the smallest granularity to the coarsest one. Key words sparse data cube - functional dependency - dimension - partition - CFD CLC number TP 311 Foundation item: Supported by the E-Government Project of the Ministry of Science and Technology of China (2001BA110B01)Biography: Feng Yu-cai (1945-), male, Professor, research direction: database system. 展开更多
关键词 sparse data cube functional dependency dimension partition CFD
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基于时态层次链的Data Cube多版本维护方案 认领 引用 被引量：1
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作者 肖磊 胡众义 《计算机系统应用》 2010年第1期161-164,共4页
针对Data Cube的模式变动造成的多版本问题,对时态聚集关系与时态层次链进行了形式化描述,并基于这些关系实现了多个版本的Data Cube的统一生成算法,不仅可以高效地进行Data Cube多个版本的维护,而且在OLAP查询也可以基于时态层次链来执... 针对Data Cube的模式变动造成的多版本问题,对时态聚集关系与时态层次链进行了形式化描述,并基于这些关系实现了多个版本的Data Cube的统一生成算法,不仅可以高效地进行Data Cube多个版本的维护,而且在OLAP查询也可以基于时态层次链来执行,从而提高系统的整体效率。 展开更多
关键词 时态层次链 多维数据集 多版本维护
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Watermarking Data Cubes 认领 引用
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作者 郭捷 邱卫东 《Journal of Shanghai Jiaotong university(Science)》 EI 2009年第1期117-121,共5页
We propose a robust watermarking scheme and several extensions for digital right management of data cubes.The ownership information is hidden into a data cube by modifying a set of selected cell values.Its owner can u... We propose a robust watermarking scheme and several extensions for digital right management of data cubes.The ownership information is hidden into a data cube by modifying a set of selected cell values.Its owner can use his private key to control all the watermarking parameters freely.Neither original data cube nor the watermark is required in watermark detection.Detailed analysis and extensive experiments are conducted for the proposed schemes in terms of watermark detectability,robustness and efficiency.Our results show that the scheme performs well in actual applications. 展开更多
关键词 data cube watermarking digital right management robustness
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基于语义的Data Cube数字水印技术 认领 引用
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作者 杨科华 杨宇华 《湖南大学学报（自然科学版）》 EI CAS 北大核心 2010年第2期70-73,共4页
数字水印技术可以有效地保护版权,数据仓库中用于OLAP(OnLine Analyti-cal Processing,联机分析处理)的Data Cube(数据立方体,亦称多维数据集)不仅包含有价值的数据,而且其设计模式与分析模式也体现了Data Cube拥有者的知识产权.将数字... 数字水印技术可以有效地保护版权,数据仓库中用于OLAP(OnLine Analyti-cal Processing,联机分析处理)的Data Cube(数据立方体,亦称多维数据集)不仅包含有价值的数据,而且其设计模式与分析模式也体现了Data Cube拥有者的知识产权.将数字水印技术引入Data Cube中,并充分利用Data Cube的语义信息,从而提供一个通用、实用的Da-ta Cube数字水印技术解决方案. 展开更多
关键词 数字水印 语义 数据立方体 版权
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一种基于多层次链的Data Cube维层次编码 认领 引用
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作者 杨科华 张伟 《湖南大学学报（自然科学版）》 EI CAS 北大核心 2007年第9期74-77,共4页
研究了Data Cube的索引技术,提出一种能够处理复杂维层次结构情况的维层次编码.维层次编码充分利用了Data Cube中维的层次性及其语义特性,结合二进制编码与维层次结构编码对维成员值进行编码,通过二进制操作,可以快速检索出与查询关键... 研究了Data Cube的索引技术,提出一种能够处理复杂维层次结构情况的维层次编码.维层次编码充分利用了Data Cube中维的层次性及其语义特性,结合二进制编码与维层次结构编码对维成员值进行编码,通过二进制操作,可以快速检索出与查询关键字相匹配的维层次编码.同时,基于维层次编码定义的层次链掩码,层次掩码及检索函数能够充分利用多维数据中的语义信息,实现基于语义的检索,减少了I/O开销,提高了OLAP查询效率. 展开更多
关键词 索引 数据立方体 联机分析处理 维层次编码
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一种特殊DATA CUBE的技术研究 认领 引用
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作者 叶茂枝 《乐山师范学院学报》 2013年第5期49-51,共3页
封闭数据立方体利用元组间的关联,除去冗余信息,在减小数据立方体体积的同时,避免了查询时的解压缩。从源数据的分组角度对封闭数据立方体概念进行了解释,并在此基础上详细分析了由于源数据的更新而导致的对应封闭数据立方体的更新过程... 封闭数据立方体利用元组间的关联,除去冗余信息,在减小数据立方体体积的同时,避免了查询时的解压缩。从源数据的分组角度对封闭数据立方体概念进行了解释,并在此基础上详细分析了由于源数据的更新而导致的对应封闭数据立方体的更新过程,给出了更新算法的框架。 展开更多
关键词 DATACUBE 分组 更新 算法框架
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Web Data Cube Construction in Multidimensional On-line Analytical Processing Environment 认领 引用
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作者 朱焱 《Journal of Southwest Jiaotong University(English Edition)》 2007年第1期1-7,共7页
This paper investigates how to integrate Web data into a multidimensional data warehouse （cube） for comprehensive on-line analytical processing （OLAP） and decision making. An approach for Web data-based cube const... This paper investigates how to integrate Web data into a multidimensional data warehouse （cube） for comprehensive on-line analytical processing （OLAP） and decision making. An approach for Web data-based cube construction is proposed, which includes Web data modeling based on MIX （ Metadam based Integration model for data X-change ）, generic and specific mapping rules design, and a transformation algorithm for mapping Web data to a multidimensional array. Besides, the structure and implementation of the prototype of a Web data base cube are discussed. 展开更多
关键词 Web data warehousing Web data-based cube MOLAP
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China Earth Observation Data Cube:The 30-m Seamless Annual Leaf-On Landsat Composites from 1985 to 2023 认领 引用 被引量：2
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作者 Yaotong Cai Xing Li +4 位作者 Peng Zhu Sheng Nie Cheng Wang Xiaoping Liu Yuhe Chen 《Journal of Remote Sensing》 EI CSCD 2025年第1期536-551,共16页
The growing demand for high-quality,temporally consistent satellite imagery for environmental monitoring and land use research has exposed a substantial data gap in China.Unlike the United States,which provides Analys... The growing demand for high-quality,temporally consistent satellite imagery for environmental monitoring and land use research has exposed a substantial data gap in China.Unlike the United States,which provides Analysis Ready Data(ARD)for Landsat imagery,Chinese researchers currently lack an equivalent resource,resulting in time-intensive data processing and potential research inaccuracies.In this study,we introduce the first seamless,annual Leaf-On Landsat composite data cube for China,covering 1985 to 2023.Leveraging the comprehensive image compositing approach,our dataset harmonizes images across multiple Landsat sensors and addresses key challenges such as cloud and shadow contamination,reflectance consistency,and the data gaps.Over this period,an average of 7.9% of data remained unavailable due to cloud/shadow cover and limited data accessibility.To address this,we applied segmented linear interpolation to generate proxies,which we validated for stability,achieving high consistency with actual Landsat references for both stable and dynamic pixel sequences(r=0.77 to 0.99,root mean square error[RMSE]=0.0043 to 0.0232).Additionally,representativeness assessments indicate a strong correlation between our composites and Landsat reference images(closest to day of year 225)(r=0.75 to 0.94,RMSE=0.025 to 0.063),confirming that these composites effectively capture seasonal vegetation conditions across diverse land cover types.This dataset is expected to help reduce preprocessing efforts for researchers and provide a solid basis for land use monitoring and environmental assessments across China. 展开更多
关键词 analysis ready data ard environmental monitoring satellite imagery data processing composite data cube Landsat data gap land use research
Interactive Earth system data cube visualization in Jupyter notebooks 认领 引用
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作者 Maximilian Söchting Gerik Scheuermann +1 位作者 David Montero Miguel D.Mahecha 《Big Earth Data》 EI CSCD 2025年第2期321-335,共15页
Visualization is key for interpreting the rapid growth of gridded,spatio-temporal data sets in Earth system sciences.However,today's tools are often designed as standalone applications,insuffi-ciently integrated i... Visualization is key for interpreting the rapid growth of gridded,spatio-temporal data sets in Earth system sciences.However,today's tools are often designed as standalone applications,insuffi-ciently integrated into scientific workflows,and typically not designed for directly interacting with data.Here,we introduce"Lexcube for Jupyter",an open-source tool designed to facilitate the interactive visualization of 3D data cubes within Jupyter note-books.This integration aims to empower researchers to more effec-tively interpret complex datasets,e.g.during model development,data curation,or for model-data comparisons.Lexcube for Jupyter builds upon the established Lexcube.org architecture by Söchting et al.(2024),but is substantially advanced in order to make it part of a scientific Python workflow.Lexcube for Jupyter incluudes efi cient data handling strategies,such as chunked data access and caching,as well as the implementation of LZ4 compression to optimize performance during interactive sessions.Employing the described techniques,Lexcube for Jupyter significantly reduces data proces-sing and visualization times compared to existing tools,facilitating real-time data exploration. 展开更多
关键词 Interactive visualization Earth system data cubes Jupyter notebooks
Think global,cube local:an Earth Observation Data Cube’s contribution to the Digital Earth vision 认领 引用 被引量：6
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作者 Martin Sudmanns Hannah Augustin +5 位作者 Brian Killough Gregory Giuliani Dirk Tiede Alex Leith Fang Yuan Adam Lewis 《Big Earth Data》 EI CSCD 2023年第3期831-859,共29页
The technological landscape for managing big Earth observation(EO)data ranges from global solutions on large cloud infrastructures with web-based access to self-hosted implementations.EO data cubes are a leading techn... The technological landscape for managing big Earth observation(EO)data ranges from global solutions on large cloud infrastructures with web-based access to self-hosted implementations.EO data cubes are a leading technology for facilitating big EO data analysis and can be deployed on different spatial scales:local,national,regional,or global.Several EO data cubes with a geographic focus(“local EO data cubes”)have been implemented.However,their alignment with the Digital Earth(DE)vision and the benefits and trade-offs in creating and maintaining them ought to be further examined.We investigate local EO data cubes from five perspectives(science,business and industry,government and policy,education,communities and citizens)and illustrate four examples covering three continents at different geographic scales(Swiss Data Cube,semantic EO data cube for Austria,DE Africa,Virginia Data Cube).A local EO data cube can benefit many stakeholders and players but requires several technical developments.These developments include enabling local EO data cubes based on public,global,and cloud-native EO data streaming and interoperability between local EO data cubes.We argue that blurring the dichotomy between global and local aligns with the DE vision to access the world’s knowledge and explore information about the planet. 展开更多
关键词 Earth Observation data cube Digital Earth interoperability workflows open data cube
Rapid,high-resolution detection of environmental change over continental scales from satellite data–the Earth Observation Data Cube 认领 引用 被引量：12
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作者 Adam Lewis Leo Lymburner +13 位作者 Matthew B.J.Purss Brendan Brooke Ben Evans Alex Ip Arnold G.Dekker James R.Irons Stuart Minchin Norman Mueller Simon Oliver Dale Roberts Barbara Ryan Medhavy Thankappan Rob Woodcock Lesley Wyborn 《International Journal of Digital Earth》 SCIE EI CSCD 2016年第1期106-111,共6页
The effort and cost required to convert satellite Earth Observation(EO)data into meaningful geophysical variables has prevented the systematic analysis of all available observations.To overcome these problems,we utili... The effort and cost required to convert satellite Earth Observation(EO)data into meaningful geophysical variables has prevented the systematic analysis of all available observations.To overcome these problems,we utilise an integrated High Performance Computing and Data environment to rapidly process,restructure and analyse the Australian Landsat data archive.In this approach,the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations–the EO Data Cube.This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement.We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous,25 m resolution observations.Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change. 展开更多
关键词 Earth Observation Data Cube HPD HPC surface water Landsat Australia
Building an Earth Observations Data Cube: lessons learned from the Swiss Data Cube (SDC) on generating Analysis Ready Data (ARD) 认领 引用 被引量：18
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作者 Gregory Giuliani Bruno Chatenoux +5 位作者 Andrea De Bono Denisa Rodila Jean-Philippe Richard Karin Allenbach Hy Dao Pascal Peduzzi 《Big Earth Data》 2017年第1期100-117,共18页
Pressures on natural resources are increasing and a number of challenges need to be overcome to meet the needs of a growing population in a period of environmental variability.Some of these environmental issues can be... Pressures on natural resources are increasing and a number of challenges need to be overcome to meet the needs of a growing population in a period of environmental variability.Some of these environmental issues can be monitored using remotely sensed Earth Observations(EO)data that are increasingly available from a number of freely and openly accessible repositories.However,the full information potential of EO data has not been yet realized.They remain still underutilized mainly because of their complexity,increasing volume,and the lack of efficient processing capabilities.EO Data Cubes(DC)are a new paradigm aiming to realize the full potential of EO data by lowering the barriers caused by these Big data challenges and providing access to large spatio-temporal data in an analysis ready form.Systematic and regular provision of Analysis Ready Data(ARD)will significantly reduce the burden on EO data users.Nevertheless,ARD are not commonly produced by data providers and therefore getting uniform and consistent ARD remains a challenging task.This paper presents an approach to enable rapid data access and pre-processing to generate ARD using interoperable services chains.The approach has been tested and validated generating Landsat ARD while building the Swiss Data Cube. 展开更多
关键词 Data Cube Earth Observations Landsat automatic processing analysis ready Data
Monitoring land degradation at national level using satellite Earth Observation time-series data to support SDG15-exploring the potential of data cube 认领 引用 被引量：13
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作者 Gregory Giuliani Bruno Chatenoux +3 位作者 Antonio Benvenuti Pierre Lacroix Mattia Santoro Paolo Mazzetti 《Big Earth Data》 EI 2020年第1期3-22,共20页
Avoiding,reducing,and reversing land degradation and restoring degraded land is an urgent priority to protect the biodiversity and ecosystem services that are vital to life on Earth.To halt and reverse the current tre... Avoiding,reducing,and reversing land degradation and restoring degraded land is an urgent priority to protect the biodiversity and ecosystem services that are vital to life on Earth.To halt and reverse the current trends in land degradation,there is an immediate need to enhance national capacities to undertake quantitative assessments and mapping of their degraded lands,as required by the Sustainable Development Goals(SDGs),in particular,the SDG indicator 15.3.1(“proportion of land that is degraded over total land area”).Earth Observations(EO)can play an important role both for generating this indicator as well as complementing or enhancing national official data sources.Implementations like Trends.Earth to monitor land degradation in accordance with the SDG15.3.1 rely on default datasets of coarse spatial resolution provided by MODIS or AVHRR.Consequently,there is a need to develop methodologies to benefit from medium to high-resolution satellite EO data(e.g.Landsat or Sentinels).In response to this issue,this paper presents an initial overview of an innovative approach to monitor land degradation at the national scale in compliance with the SDG15.3.1 indicator using Landsat observations using a data cube but further work is required to improve the calculation of the three sub-indicators. 展开更多
关键词 Land degradation Sustainable Development Goals Open Data Cube Landsat Sentinel-2 SDG15.3.1
Cache-Conscious Data Cube Computation on a Modern Processor 认领 引用 被引量：3
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作者 Hua Luan Xiao-Yong Du Shan Wang 《Journal of Computer Science & Technology》 SCIE EI 2009年第4期708-722,共15页
Data cube computation is an important problem in the field of data warehousing and OLAP (online analytical processing). Although it has been studied extensively in the past, most of its algorithms are designed without... Data cube computation is an important problem in the field of data warehousing and OLAP (online analytical processing). Although it has been studied extensively in the past, most of its algorithms are designed without considering CPU and cache behavior. In this paper, we first propose a cache-conscious cubing approach called CC-Cubing to efficiently compute data cubes on a modern processor. This method can enhance CPU and cache performances. It adopts an integrated depth-first and breadth-first partitioning order and partitions multiple dimensions simultaneously. The partitioning scheme improves the data spatial locality and increases the utilization of cache lines. Software prefetching techniques are then applied in the sorting phase to hide the expensive cache misses associated with data scans. In addition, a cache-aware method is used in CC-Cubing to switch the sort algorithm dynamically. Our performance study shows that CC-Cubing outperforms BUC, Star-Cubing and MM-Cubing in most cases. Then, in order to fully utilize an SMT (simultaneous multithreading) processor, we present a thread-based CC-Cubing-SMT method. This parallel method provides an improvement up to 27% for the single-threaded CC-Cubing algorithm. 展开更多
关键词 data warehousing OLAF(online analytical processing) data cube computation cache-conscious SMT(simultaneous multithreading)
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PMC: Select Materialized Cells in Data Cubes 认领 引用 被引量：2
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作者 李红松 黄厚宽 《Journal of Computer Science & Technology》 SCIE EI 2006年第2期297-304,F0003,共8页
QC-Tree is one of the most storage-efficient structures for data cubes in an MOLAP system. Although QC- Tree can achieve a high compression ratio, it is still a fully materialized data cube. In this paper, an improved... QC-Tree is one of the most storage-efficient structures for data cubes in an MOLAP system. Although QC- Tree can achieve a high compression ratio, it is still a fully materialized data cube. In this paper, an improved structure PMC is presented allowing us to materialize only a part of the cells in a QC-Tree to save more storage space. There is a notable difference between our partially materialization algorithm and traditional materialized views selection algorithms. In a traditional algorithm, when a view is selected, all the cells in this view are to be materialized. Otherwise, if a view is not selected, all the cells in this view will not be materialized. This strategy results in the unstable query performance. The presented algorithm, however, selects and materializes data in cell level, and, along with further reduced space and update cost, it can ensure a stable query performance. A series of experiments are conducted on both synthetic and real data sets. The results show that PMC can further reduce storage space occupied by the data cube, and can shorten the time to update the cube. 展开更多
关键词 data warehousing data cube multidimensional database partial materialization
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联合K-D树和GPU并行运算的CUBE快速滤波方法 认领 引用 被引量：1
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作者 李枭凯 王力 +2 位作者 李广云 高欣圆 靳海峰 《海洋测绘》 CSCD 北大核心 2025年第2期14-18,共5页
针对多波束测深数据滤波算法的效率问题,提出了一种联合K-D树和GPU并行运算的CUBE(com-bined uncertainty bathymetry estimator,CUBE)快速滤波算法。该算法首先利用K-D树对点云数据进行高效索引,然后将滤波任务分配至GPU的流式多处理... 针对多波束测深数据滤波算法的效率问题,提出了一种联合K-D树和GPU并行运算的CUBE(com-bined uncertainty bathymetry estimator,CUBE)快速滤波算法。该算法首先利用K-D树对点云数据进行高效索引,然后将滤波任务分配至GPU的流式多处理器进行并行处理,从而显著提升了执行速度。实验部分通过比较K-D树与八叉树的索引效率,验证了K-D树在处理大规模点云数据时的优势。将本算法与串行CUBE算法及CARIS HIPS软件的CUBE模块进行对比,结果显示在亿级数据量处理中,滤波速度提高了约13.8倍。此外,本算法在保持数据真实性和去噪效果的前提下,展现了与商业软件相当的处理效率,为多波束测深数据的高效处理提供了有价值的参考。 展开更多
关键词 多波束测深 数据处理 CUBE算法 K-D树 GPU加速
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利用MarchingCubes算法的塔身垂直度激光雷达检验方法 认领 引用 被引量：2
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作者 周命端 覃钰涵 +4 位作者 孟庆龙 徐翔 刘明华 宋峤 王俊杰 《测绘科学》 CSCD 北大核心 2025年第3期123-131,共9页
鉴于移动立方体算法在医学成像、计算机图形学、工程建模等领域被广泛应用,顾及激光雷达检验法具有诸多优点,提出了一种新的利用MarchingCubes算法的塔身垂直度激光雷达检验方法。实验选取施工现场某型号塔式起重机塔身进行测试,采用激... 鉴于移动立方体算法在医学成像、计算机图形学、工程建模等领域被广泛应用,顾及激光雷达检验法具有诸多优点,提出了一种新的利用MarchingCubes算法的塔身垂直度激光雷达检验方法。实验选取施工现场某型号塔式起重机塔身进行测试,采用激光雷达扫描采集塔身标准节原始点云数据,经预处理后获取塔身标准节有效高精度点云数据;给出塔身标准节横向切段立方体点云分割策略,利用MarchingCubes算法提取塔身标准节横向切段立方体点云轮廓线,并求解其体中心点坐标;运用最小二乘法拟合体中心点所在空间直线,计算其方向向量,并在站心空间坐标系下分别与x轴和z轴进行向量运算,获得塔身轴心线倾斜方位角、倾斜角和塔身垂直度。结果表明:采用本文方法设计5种策略方案获得的塔身垂直度中数值为1.80‰,与传统的经纬仪检验法结果为3.02‰基本吻合。本文为塔身垂直度无损检验提供一种高精度激光雷达算法。 展开更多
关键词 激光雷达检验法 经纬仪检验法 移动立方体算法 点云数据 塔身垂直度
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Parallel Data Cube Storage Structure for Range Sum Queries and Dynamic Updates 认领 引用
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作者 HongGao Jian-ZhongLi 《Journal of Computer Science & Technology》 SCIE EI 2005年第3期345-356,共12页
I/O parallelism is considered to be a promising approach to achieving highperformance in parallel data warehousing systems where huge amounts of data and complex analyticalqueries have to be processed. This paper prop... I/O parallelism is considered to be a promising approach to achieving highperformance in parallel data warehousing systems where huge amounts of data and complex analyticalqueries have to be processed. This paper proposes a parallel secondary data cube storage structure(PHC for short) to efficiently support the processing of range sum queries and dynamic updates ondata cube using parallel computing systems. Based on PHC, two parallel algorithms for processingrange sum queries and updates are proposed also. Both the algorithms have the same time complexity,O(log^d n/P). The analytical and experimental results show that PHC and the parallel algorithms havehigh performance and achieve optimum speedup. 展开更多
关键词 data warehouse parallel processing cube range query processing
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Hierarchical Datacubes 认领 引用
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作者 Mickaël Martin Nevot Sébastien Nedjar Lotfi Lakhal 《Journal of Computer and Communications》 2023年第6期43-72,共30页
Many approaches have been proposed to pre-compute data cubes in order to efficiently respond to OLAP queries in data warehouses. However, few have proposed solutions integrating all of the possible outcomes, and it is... Many approaches have been proposed to pre-compute data cubes in order to efficiently respond to OLAP queries in data warehouses. However, few have proposed solutions integrating all of the possible outcomes, and it is this idea that leads the integration of hierarchical dimensions into these responses. To meet this need, we propose, in this paper, a complete redefinition of the framework and the formal definition of traditional database analysis through the prism of hierarchical dimensions. After characterizing the hierarchical data cube lattice, we introduce the hierarchical data cube and its most concise reduced representation, the closed hierarchical data cube. It offers compact replication so as to optimize storage space by removing redundancies of strongly correlated data. Such data are typical of data warehouses, and in particular in video games, our field of study and experimentation, where hierarchical dimension attributes are widely represented. 展开更多
关键词 ROLAP Cubing Data Warehouse Datacube Big Data Business Intelligence Hierarchical Cube Hierarchical Dimensions
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