Dynamic integration of biological data sources using the data concierge.

Peng Gong

doi:10.1186/2047-2501-1-7

Abstract

BackgroundThe ever-changing landscape of large-scale network environments and innovative biology technologies require dynamic mechanisms to rapidly integrate previously unknown bioinformatics sources at runtime. However, existing integration technologies lack sufficient flexibility to adapt to these changes, because the techniques used for integration are static, and sensitive to new or changing bioinformatics source implementations and evolutionary biologist requirements.MethodsTo address this challenge, in this paper we propose a new semantics-based adaptive middleware, the Data Concierge, which is able to dynamically integrate heterogeneous biological data sources without the need for wrappers. Along with the architecture necessary to facilitate dynamic integration, API description mechanism is proposed to dynamically classify, recognize, locate, and invoke newly added biological data source functionalities. Based on the unified semantic metadata, XML-based state machines are able to provide flexible configurations to execute biologist's abstract and complex operations.Results and discussionExperimental results demonstrate that for obtaining dynamic features, the Data Concierge sacrifices reasonable performance on reasoning knowledge models and dynamically doing data source API invocations. The overall costs to integrate new biological data sources are significantly lower when using the Data Concierge.ConclusionsThe Data Concierge facilitates the rapid integration of new biological data sources in existing applications with no repetitive software development required, and hence, this mechanism would provide a cost-effective solution to the labor-intensive software engineering tasks.

Highlights

The ever-changing landscape of large-scale network environments and innovative biology technologies require dynamic mechanisms to rapidly integrate previously unknown bioinformatics sources at runtime
The Data Concierge facilitates the rapid integration of new biological data sources in existing applications with no repetitive software development required, and this mechanism would provide a cost-effective solution to the labor-intensive software engineering tasks
To address the above issues, in this paper we demonstrate how the Data Concierge adaptive middleware platform [25,26] can be extended to integrate new biological data sources without the need for application-level programming

Summary

Introduction

The ever-changing landscape of large-scale network environments and innovative biology technologies require dynamic mechanisms to rapidly integrate previously unknown bioinformatics sources at runtime. High throughput experimental processes in life science have led to a large variety of biological data sources continuously emerging on the Internet [1,2]. These data sources provide great research potential for biology researchers to obtain data that support their new biological insights in areas such as gene prediction, proteomics analysis, mutations, and drug discovery. The lack of standardization means biological data is available in a wide variety of formats Various data schemas such as flat files, structured data (e.g. database), semi-structured data (e.g. XML [8]), and arbitrary data structures, result in syntactical difficulties for data unification [9]

Methods

Results

Conclusion