Data integration through database federation

Haas, Laura M.; Lin, Eileen; Roth, Mark A.

doi:10.1147/sj.414.0578

Cited by 118 publications

(77 citation statements)

References 24 publications

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“…These remote objects can be transparently cached and queried using dynamically optimized SQL. 7 The WebSphere Federation Server also provides configurable mappings between other schema objects such as functions and user accounts that simplify management of data sources. The WebSphere Federation Server runs on different operating systems and integrates with open source development work through free products like Java/JDBC 15 and Eclipse.…”

Section: Methodsmentioning

confidence: 99%

“…6 For the TwinNET, an alternative approach was chosen where data are loaded directly at the data provider site and made available using database federation. 7,8 Benefit of the approach is that data can be made available faster since data management work is distributed and done by most experienced personnel. There is also the possibility to quickly explore new unharmonized data sets, which can be copied from productions systems using SQL statements.…”

Section: Interoperability and Data Managementmentioning

confidence: 99%

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The federated database – a basis for biobank-based post-genome studies, integrating phenome and genome data from 600 000 twin pairs in Europe

2007

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Integration of complex data and data management represent major challenges in large-scale biobankbased post-genome era research projects like GenomEUtwin (an international collaboration between eight Twin Registries) with extensive amounts of genotype and phenotype data combined from different data sources located in different countries. The challenge lies not only in data harmonization and constant update of clinical details in various locations, but also in the heterogeneity of data storage and confidentiality of sensitive health-related and genetic data. Solid infrastructure must be built to provide secure, but easily accessible and standardized, data exchange also facilitating statistical analyses of the stored data. Data collection sites desire to have full control of the accumulation of data, and at the same time the integration should facilitate effortless slicing and dicing of the data for different types of data pooling and study designs. Here we describe how we constructed a federated database infrastructure for genotype and phenotype information collected in seven European countries and Australia and connected this database setting via a network called TwinNET to guarantee effortless data exchange and pooled analyses. This federated database system offers a powerful facility for combining different types of information from multiple data sources. The system is transparent to end users and application developers, since it makes the set of federated data sources look like a single system. The user need not be aware of the format or site where the data are stored, the language or programming interface of the data source, how the data are physically stored, whether they are partitioned and/or replicated or what networking protocols are used. The user sees a single standardized interface with the desired data elements for pooled analyses.

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Section: Methodsmentioning

confidence: 99%

Section: Interoperability and Data Managementmentioning

confidence: 99%

The federated database – a basis for biobank-based post-genome studies, integrating phenome and genome data from 600 000 twin pairs in Europe

2007

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“…DB2 [27] can be seen as a baseline system. It provides queries over heterogeneous sources using a mapping-based mediation approach where mappings are built with significant human intervention, but, significantly, some of the advances resulting from the Clio project [55,56,16,34] were incorporated into DB2.…”

Section: Dataspace Management Systemsmentioning

confidence: 99%

A Functional Model for Dataspace Management Systems

Hedeler

Fernandes

Belhajjame

et al. 2013

Advanced Query Processing

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Dataspace management systems (DSMSs) hold the promise of pay-asyou-go data integration. We describe a comprehensive model of DSMS functionality using an algebraic style. We begin by characterizing a dataspace life cycle and highlighting opportunities for both automation and user-driven improvement techniques. Building on the observation that many of the techniques developed in model management are of use in data integration contexts as well, we briefly introduce the model management area and explain how previous work on both data integration and model management needs extending if the full dataspace life cycle is to be supported. We show that many model management operators already enable important functionality (e.g., the merging of schemas, the composition of mappings, etc.) and formulate these capabilities in an algebraic structure, thereby giving rise to the notion of the core functionality of a DSMS as a many-sorted algebra. Given this view, we show how core tasks in the dataspace life cycle can be enacted by means of algebraic programs. An extended case study illustrates how such algebraic programs capture a challenging, practical scenario.

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“…As such, it closely relates to the work on traditional database federation. In federated databases, middleware (typically an extension of a relational database management system) provides uniform access to a number of heterogeneous data sources (e.g., [7,8,9]). Similarly, we have built MaxStream as a middle layer between clients and underlying systems, extending a relational engine infrastructure.…”

Section: Related Workmentioning

confidence: 99%

“…MaxStream follows the typical architecture of a database federation system [9], providing a middleware layer between the application program and the data sources, and connecting to those sources via wrappers. Like a database federation engine, it provides a common programming interface and query language to the applications, and queries are translated into the languages supported by the underlying systems.…”

Section: The Maxstream Federated Stream Processing Systemmentioning

confidence: 99%

Federated Stream Processing Support for Real-Time Business Intelligence Applications

Botan

Cho

Derakhshan

et al. 2010

Lecture Notes in Business Information Processing

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Abstract. In this paper, we describe the MaxStream federated stream processing architecture to support real-time business intelligence applications. MaxStream builds on and extends the SAP MaxDB relational database system in order to provide a federator over multiple underlying stream processing engines and databases. We show preliminary results on usefulness and performance of the MaxStream architecture on the SAP Sales and Distribution Benchmark.

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Data integration through database federation

Cited by 118 publications

References 24 publications

The federated database – a basis for biobank-based post-genome studies, integrating phenome and genome data from 600 000 twin pairs in Europe

The federated database – a basis for biobank-based post-genome studies, integrating phenome and genome data from 600 000 twin pairs in Europe

A Functional Model for Dataspace Management Systems

Federated Stream Processing Support for Real-Time Business Intelligence Applications

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