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TPC-DI: The First Industry Benchmark for data integration

PROCEEDINGS OF THE VLDB ENDOWMENT 2014年第13期7卷 1367-1378页

作者： Poess, Meikel Rabl, Tilmann Jacobsen, Hans-Arno Caufield, Brian Oracle Corp Server Technol Redwood Shores CA 94065 USA Univ Toronto Res Grp Middleware Syst Toronto ON Canada IBM Corp InfoSphere DataStage San Jose CA USA

Historically, the process of synchronizing a decision support system with data from operational systems has been referred to as Extract, Transform, Load (ETL) and the tools supporting such process have been referred to as ETL tools. Recently, ETL was replaced by the more comprehensive acronym, data integration (DI). DI describes the process of extracting and combining data from a variety of data source formats, transforming that data into a unified data model representation and loading it into a data store. This is done in the context of a variety of scenarios, such as data acquisition for business intelligence, analytics and data warehousing, but also synchronization of data between operational applications, data migrations and conversions, master data management, enterprise data sharing and delivery of data services in a service-oriented architecture context, amongst others. With these scenarios relying on up-to-date information it is critical to implement a highly performing, scalable and easy to maintain data integration system. This is especially important as the complexity, variety and volume of data is constantly increasing and performance of data integration systems is becoming very critical. Despite the significance of having a highly performing DI system, there has been no industry standard for measuring and comparing their performance. The TPC, acknowledging this void, has released TPC-DI, an innovative benchmark for data integration. This paper motivates the reasons behind its development, describes its main characteristics including workload, run rules, metric, and explains key decisions.

关键词： Artificial intelligence data acquisition data warehouses Decision support systems Information management Information services Metadata Service oriented architecture (SOA) data integration system Enterprise data Industry benchmarks Industry standards Master data management Model representation Operational applications Operational systems data integration

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A Survey on dataspace

A Survey on Dataspace

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4th International Conference on Network Security and Applications (CNSA 2011)

作者： Singh, Mrityunjay Jain, S. K. Natl Inst Technol Dept Comp Engn Kurukshetra 136119 Haryana India

ISBN: (纸本)9783642225390

In many large/small organization or enterprises, managing the heterogeneity among data at various level has made a challenging task for its management community. In an organization, data may vary from fully structured to completely unstructured. The existing data management systems fail to manage such data in efficient manner. Now, dataspace technology addresses the problem of heterogeneity present in data and solving various shortcomings of the existing systems. This paper presents a survey on dataspace and discusses issues related to the dataspace like system architecture, data modelling, querying and answering techniques, and indexing.

关键词： dataspace data integration system pay-as-you-go data integration PIM mediated schema semantic mappings inverted list

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Enhancing Big data Conversion Validation with Alpha-Lightweight Coreset

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SN Computer Science 2023年第6期4卷 799页

作者： Hoang, Nguyen Le Dang, Tran Khanh Ritsumeikan University Kusatsu Shiga Japan Ho Chi Minh City University of Industry and Trade Ho Chi Minh City Viet Nam

In this paper, we apply a previously proposed data conversion system that leverages the α -lightweight coreset for efficient and accurate validation in the context of big data. The system is designed to migrate data from MySQL to MongoDB while preserving consistency across columns, rows, and data types. We focus on the validation process, which employs the α -lightweight coreset to identify errors in the transformed data quickly and with high accuracy. We investigate the optimal value of α for various scenarios by comparing different α values from 0 to 1. Our experimental results demonstrate that the α value around 3/4 generally provides optimal performance. However, for datasets requiring more focus on the additive error, the optimal α value may differ. This study highlights the effectiveness of the α -lightweight coreset in improving the speed and accuracy of the validation process in data conversion systems for big data. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Coreset data conversion data integration system data sampling data transformation

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Modeling data Heterogeneity Using Big dataSpace Architecture 9th

Modeling Data Heterogeneity Using Big DataSpace Architecture

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9th International Conference on Advanced Computing and Communication Technologies (ICACCT)

作者： Sheokand, Vishal Singh, Vikram Natl Inst Technol Dept Comp Engn Kurukshetra 136119 Haryana India

ISBN: (纸本)9789811010231;9789811010217

With the wide use of information expertise in advanced analytics, basically three characteristics of big data have been identified. These are volume, velocity and variety. The first of these two have enjoyed quite a lot of focus, volume of data and velocity of data, less thought has been focused on variety of available data worldwide. data variety refers to the nature of data in store and under processing, which has three orthogonal natures: structured, semi-structured and unstructured. To handle the variety of data, current universally acceptable solutions are either costlier than customized solutions or less efficient to cater data heterogeneity. Thus, a basic idea is to, first design data processing systems that create abstraction that covers a wide range of data types and support fundamental processing on underlying heterogeneous data. In this paper, we conceptualized data management architecture 'Big dataSpace', for big data processing with the capability to combine heterogeneous data from various data sources. Further, we explain how Big dataSpace architecture can help in processing the heterogeneous and distributed data, a fundamental task in data management.

关键词： Big data Mining dataspace system data Intensive Computing data Variety data Volume data integration system

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A Deeper Analysis of the Hierarchical Clustering and Set Unionability-Based data Union Method

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SN Computer Science 2022年第6期3卷 486页

作者： Dang, Tran Khanh Ta, Manh Huy Ho Chi Minh City University of Food Industry (HUFI) 140 Le Trong Tan Street Tan Phu District Ho Chi Minh City Viet Nam Ho Chi Minh City University of Technology VNU-HCM 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Viet Nam

data nowadays are an extremely valuable resource. data can come from different sources, and it can originate from the government of a country, an organization, a company, or just a normal person. Furthermore, the content of data is varied: the data could be about primary education in the U.K, it could be about medical care in the U.S., or it could be about agriculture in Vietnam, etc. It is reasonable to assume that among those datasets, some datasets would be about the same topic. Moreover, those datasets could have the same structures, or at least, similar structures. It is beneficial that we can union those datasets into more meaningful datasets: The unionized datasets would contain the collective information of the datasets, and the users and scientists do not have to spend a lot of time searching and combining the datasets themselves, etc. In this paper, we proposed a data union method based on hierarchical clustering and Set Unionability for JSON-format data. Besides, we also performed some experiments to evaluate our method and prove its feasibility. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： data integration system data union Hierarchical clustering Open data

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Rewriting Fuzzy Queries Using Imprecise Views

Rewriting Fuzzy Queries Using Imprecise Views

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15th International Conference on Advances in databases and Information systems

作者： Jaudoin, Helene Pivert, Olivier Univ Rennes 1 Irisa Enssat F-22305 Lannion France

ISBN: (纸本)9783642237362;9783642237379

This paper proposes an approach to the tolerant rewriting of queries in terms of views when the views and the queries may involve fuzzy value constraints in the context of a Local-As-View mediation system. These constraints describe attribute values as a set of elements attached with a degree in [0, 1] that expresses the plausibility attached to a given element, i.e., attribute values more or less plausible/typical in the views, while in the queries, they denotes preferences, i.e., more or less desired values. The problem of rewriting queries is formalized in the setting of the description logic FL0 extended to fuzzy value constraints. We propose an algorithm of gradual and structural subsumption for this extended logic, that plays a key role in the query rewriting algorithm. Finally, we characterize the tolerant query rewriting forms and propose an algorithm to compute them.

关键词： data integration system LAV Approach Fuzzy preferences Imprecise views

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MapSDI: A Scaled-Up Semantic data integration Framework for Knowledge Graph Creation

MapSDI: A Scaled-Up Semantic Data Integration Framework for ...

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27th International Conference on Cooperative Information systems, (CoopIS) / International Conference on Ontologies, databases, and Applications of Semantics (ODBASE) / Conference on Cloud and Trusted Computing (C and TC)

作者： Jozashoori, Samaneh Vidal, Maria-Esther Leibniz Univ Hannover L3S Res Ctr Hannover Germany TIB Leibniz Informat Ctr Sci & Technol Hannover Germany

ISBN: (纸本)9783030332464;9783030332457

Semantic web technologies have significantly contributed with effective solutions for the problems of data integration and knowledge graph creation. However, with the rapid growth of big data in diverse domains, different interoperability issues still demand to be addressed, being scalability one of the main challenges. In this paper, we address the problem of knowledge graph creation at scale and provide MapSDI, a mapping rule-based framework for optimizing semantic data integration into knowledge graphs. MapSDI allows for the semantic enrichment of large-sized, heterogeneous, and potentially low-quality data efficiently. The input of MapSDI is a set of data sources and mapping rules being generated by a mapping language such as RML. First, MapSDI pre-processes the sources based on semantic information extracted from mapping rules, by performing basic database operators;it projects out required attributes, eliminates duplicates, and selects relevant entries. All these operators are defined based on the knowledge encoded by the mapping rules which will be then used by the semantification engine (or RDFizer) to produce a knowledge graph. We have empirically studied the impact of MapSDI on existing RDFizers, and observed that knowledge graph creation time can be reduced on average in one order of magnitude. It is also shown, theoretically, that the sources and rules transformations provided by MapSDI are data-lossless.

关键词： Knowledge graph creation Semantic data integration Transformation rules data integration system

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Intermediate data Format for the Elastic data Conversion Framework 15

Intermediate Data Format for the Elastic Data Conversion Fra...

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15th International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Tran Khanh Dang Ta Manh Huy Nguyen Le Hoang Ho Chi Minh City Univ Technol HCMUT VNU HCM 268 Ly Thuong Kiet StDist 10 Ho Chi Minh City Vietnam

ISBN: (数字)9781665423182

ISBN: (纸本)9781665423182

With the development of technology, data is becoming an extremely valuable resource. data is being created, analyzed and used in a massive scale in every modern system. As a result, data analysis and data mining are very essential in each aspect of social applications. The value of data will be more useful if it can be linked and merged with other different data resources, especially for solving current social problems. In order to make a reality of this big challenge, data transformation is a crucial step that we have to overcome. Among data conversion methods, the intermediate method is to be a preferable one due to its expandable ability. However, for this type of model, finding the intermediate data type for the system is the crucial problem that needs to be solved firstly. In this paper, we will make comparisons among some popular data formats to find the appropriate data type for this elastic data conversion system.

关键词： data format data type data conversion data integration system data transformation open data

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An Elastic data Conversion Framework: A Case Study for MySQL and MongoDB

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SN Computer Science 2021年第4期2卷 1-15页

作者： Dang, Tran Khanh Huy, Ta Manh Dang, Ly Hoang Le Hoang, Nguyen Ho Chi Minh City University of Technology Vietnam National University Ho Chi Minh City 268 Ly Thuong Kiet District 10 Ho Chi Minh City Viet Nam

data nowadays are extremely valuable resource. However, data are created and stored in different places with various formats and types. As a result, it is not easy and efficient for data analysis and data mining which can make profits for every aspect of social applications. To overcome this problem, data conversion is a crucial step that we have to build for linking and merging different data resources to a unified data store. In this paper, based on the intermediate data conversion model, we proposed an elastic data conversion framework for data integration system. Besides, we also performed an experiment to evaluate our model using MySQL and MongoDB. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： data conversion data integration system data transformation Open data

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Evaluating the accuracy of a functional SNP annotation system

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BMC BIOINFORMATICS 2009年第Sup9期10卷 S11-S11页

作者： Shen, Terry H. Carlson, Christopher S. Tarczy-Hornoch, Peter Univ Washington Dept Biomed & Hlth Informat Seattle WA 98195 USA Univ Washington Dept Genome Sci Seattle WA 98195 USA Univ Washington Dept Comp Sci & Engn Seattle WA 98195 USA Univ Washington Dept Pediat Seattle WA 98195 USA Fred Hutchinson Canc Res Ctr Seattle WA 98104 USA

Many common and chronic diseases are influenced at some level by genetic variation. Research done in population genetics, specifically in the area of single nucleotide polymorphisms (SNPs) is critical to understanding human genetic variation. A key element in assessing role of a given SNP is determining if the variation is likely to result in change in function. The SNP integration Tool (SNPit) is a comprehensive tool that integrates diverse, existing predictors of SNP functionality, providing the user with information for improved association study analysis. To evaluate the SNPit system, we developed an alternative gold standard to measure accuracy using sensitivity and specificity. The results of our evaluation demonstrated that our alternative gold standard produced encouraging results.

关键词： data integration system Annotation Category Regulatory SNPs Mediate Schema Public Health Geneticist

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