International Workshop on Data Warehousing and OLAP最新文献_第4页

Type 2 slowly changing dimensions: a case study using the co>operating system 类型2缓慢变化的维度:使用co>操作系统的案例研究

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390059

C. Stanfill

引用次数: 6

Warehousing and querying trajectory data streams with error estimation 带误差估计的轨迹数据流的存储和查询

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390064

E. Masciari

引用次数: 4

Query processing on cubes mapped from ontologies to dimension hierarchies 对从本体映射到维度层次结构的多维数据集进行查询处理

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390055

Carlos Garcia-Alvarado, C. Ordonez

{"title":"Query processing on cubes mapped from ontologies to dimension hierarchies","authors":"Carlos Garcia-Alvarado, C. Ordonez","doi":"10.1145/2390045.2390055","DOIUrl":"https://doi.org/10.1145/2390045.2390055","url":null,"abstract":"Text columns commonly extend core information stored as atomic values in a relational database, creating a need to explore and summarize text data. OLAP cubes can precisely accomplish such tasks. However, cubes have been overlooked as a mechanism for capturing not only text summarizations, but also for representing and exploring the hierarchical structure of an ontology. In this paper, we focus on exploiting cubes to compute multidimensional aggregations on classified documents stored in a DBMS (keyword frequency, document count, document class frequency and so on). We propose CUBO (CUBed Ontologies), a novel algorithm, which efficiently manipulates the hierarchy behind an ontology. Our algorithm is optimized to compute desired summarizations without having to search all possible dimension combinations, exploiting the sparseness of the document classification frequency matrix. Experiments on large text data sets show CUBO can explore faster more dimension combinations than a standard cube algorithm, especially when the cube has a large number of dimensions. CUBO was developed entirely inside a DBMS, using SQL queries and extensibility features.","PeriodicalId":335396,"journal":{"name":"International Workshop on Data Warehousing and OLAP","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133333868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

An in-depth analysis of data aggregation cost factors in a columnar in-memory database 对列式内存数据库中数据聚合成本因素的深入分析

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390057

Stephan Müller, H. Plattner

引用次数: 10

Towards benchmarking stream data warehouses 对流数据仓库进行基准测试

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390062

A. Bär, Lukasz Golab

{"title":"Towards benchmarking stream data warehouses","authors":"A. Bär, Lukasz Golab","doi":"10.1145/2390045.2390062","DOIUrl":"https://doi.org/10.1145/2390045.2390062","url":null,"abstract":"Data management systems are facing two challenges driven by the requirements of emerging data-intensive applications: more data and less time to process the data. Data volumes continue to increase as new sources and data collecting mechanisms appear. At the same time, these sources tend to be highly dynamic and generate data in the form of a stream, which requires quick reaction to newly arrived data. Traditional data warehouses enable scalable data storage and analytics, including the ability to define nested levels of materialized views. However, views are typically refreshed during downtimes---e.g., every night---which does not meet the latency requirements of many applications. Stream data warehousing is a new data management technology that allows nearly-continuous view refresh as new data arrive, which enables seamless integration of real-time monitoring and business intelligence with long-term data mining. In this paper, we argue that a new benchmark is required for stream warehouses, which should focus on measuring the property that determines the utility of these systems, namely how well they can keep up with the incoming data and guarantee the \"freshness\" of materialized views.","PeriodicalId":335396,"journal":{"name":"International Workshop on Data Warehousing and OLAP","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124957305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Approximate answers to OLAP queries on streaming data warehouses 流数据仓库上的OLAP查询的近似答案

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390065

M. D. Rougemont, Phuong Thao Cao

引用次数: 10

Improving the maintainability of data warehouse designs: modeling relationships between sources and user concepts 改进数据仓库设计的可维护性:对数据源和用户概念之间的关系进行建模

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390050

A. Maté, J. Trujillo, Elisa de Gregorio, I. Song

{"title":"Improving the maintainability of data warehouse designs: modeling relationships between sources and user concepts","authors":"A. Maté, J. Trujillo, Elisa de Gregorio, I. Song","doi":"10.1145/2390045.2390050","DOIUrl":"https://doi.org/10.1145/2390045.2390050","url":null,"abstract":"In data warehouse (DW) development, a series of mappings must be specified between user concepts and data source elements, in order to identify which sources must undergo an integration process. Until now, these mappings are either assumed to be implied by name matching or identified according to the designer's experience. Then, the result is implemented as Extraction/Transformation/Loading (ETL) processes. Since ETL processes relate elements at the logical level, designers cannot adequately analyze how a change in requirements or in the data sources affects the analysis capabilities. Furthermore, this approach makes it difficult to perform incremental changes in DW design, requiring in some cases to perform the whole analysis again. In this paper we present a set of semantic mappings that relate user concepts specified by requirements to those obtained from data sources. In turn, this allows us to accurately identify how any potential change affects the different structures and ETL processes. As a DW evolves over time, our approach easily allows us to incorporate new concepts, as well as any change introduced at requirements or data sources into the DW repository with no need to redesign the whole DW. In order to show the application of our proposal, we show a real case study focusing on the Digital library of the University of Alicante.","PeriodicalId":335396,"journal":{"name":"International Workshop on Data Warehousing and OLAP","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128143195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Multidimensional models meet the semantic web: defining and reasoning on OWL-DL ontologies for OLAP 多维模型满足语义web:在OLAP的OWL-DL本体上定义和推理

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390049

N. Prat, I. Megdiche, J. Akoka

引用次数: 20

Towards intensional answers to OLAP queries for analytical sessions 对分析会话的OLAP查询进行深入的回答

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390054

Patrick Marcel, R. Missaoui, S. Rizzi

引用次数: 14

FedDW global schema architect: UML-based design tool for the integration of data mart schemas FedDW全局模式架构师:用于集成数据集市模式的基于uml的设计工具

International Workshop on Data Warehousing and OLAP Pub Date : 2012-11-02 DOI: 10.1145/2390045.2390051

Stefan Berger, M. Schrefl

{"title":"FedDW global schema architect: UML-based design tool for the integration of data mart schemas","authors":"Stefan Berger, M. Schrefl","doi":"10.1145/2390045.2390051","DOIUrl":"https://doi.org/10.1145/2390045.2390051","url":null,"abstract":"Extending analytical decision making beyond the boundaries of a single organization is a key challenge of modern Business Intelligence systems. Federated Data Warehouses (FDWs) are an important cornerstone to this end, offering new opportunities for business collaboration and similar scenarios. The FedDW approach provides such a federated architecture with a mediated multidimensional schema over autonomous data marts---with advantages for both, OLAP users and data warehouse administrators. Users comfortably access the global mediated schema with traditional OLAP applications while administrators retain full schema and data management autonomy. Although the underlying concepts are mature, comprehensive design tools for FDWs remain an open issue. To tackle the challenge, this paper presents FedDW Global Schema Architect (GSA), a visual design tool for federations of autonomous ROLAP data marts. FedDW integrates data marts at the schema level which avoids the laborious and error-prone physical DW integration. GSA manages all metadata--the global mediated schema, the import schemas, and the semantic mappings repairing multidimensional heterogeneity among the data marts--within one and the same tool. Its implementation employs the extension mechanisms of Eclipse and is based on the UML and CWM (Common Warehouse Metamodel) standards. Thus, the tool is extensible, intuitive for its users, and supports DW platforms of multiple vendors.","PeriodicalId":335396,"journal":{"name":"International Workshop on Data Warehousing and OLAP","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122464659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4