Zhang Zhang, Cheung Kei-Hoi, Townsend Jeffrey P
Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06520, USA.
Brief Bioinform. 2009 Jan;10(1):1-10. doi: 10.1093/bib/bbn041. Epub 2008 Oct 8.
Enabling deft data integration from numerous, voluminous and heterogeneous data sources is a major bioinformatic challenge. Several approaches have been proposed to address this challenge, including data warehousing and federated databasing. Yet despite the rise of these approaches, integration of data from multiple sources remains problematic and toilsome. These two approaches follow a user-to-computer communication model for data exchange, and do not facilitate a broader concept of data sharing or collaboration among users. In this report, we discuss the potential of Web 2.0 technologies to transcend this model and enhance bioinformatics research. We propose a Web 2.0-based Scientific Social Community (SSC) model for the implementation of these technologies. By establishing a social, collective and collaborative platform for data creation, sharing and integration, we promote a web services-based pipeline featuring web services for computer-to-computer data exchange as users add value. This pipeline aims to simplify data integration and creation, to realize automatic analysis, and to facilitate reuse and sharing of data. SSC can foster collaboration and harness collective intelligence to create and discover new knowledge. In addition to its research potential, we also describe its potential role as an e-learning platform in education. We discuss lessons from information technology, predict the next generation of Web (Web 3.0), and describe its potential impact on the future of bioinformatics studies.
实现从众多、大量且异构数据源进行灵活的数据集成是一项重大的生物信息学挑战。已经提出了几种方法来应对这一挑战,包括数据仓库和联邦数据库。然而,尽管这些方法有所兴起,但来自多个源的数据集成仍然存在问题且繁琐。这两种方法遵循用户与计算机之间的数据交换通信模型,并未促进更广泛的数据共享概念或用户之间的协作。在本报告中,我们讨论了Web 2.0技术超越此模型并加强生物信息学研究的潜力。我们提出了一种基于Web 2.0的科学社会社区(SSC)模型来实施这些技术。通过建立一个用于数据创建、共享和集成的社交、集体和协作平台,我们推动了一个基于网络服务的流程,该流程以用户添加价值时用于计算机到计算机数据交换的网络服务为特色。此流程旨在简化数据集成和创建,实现自动分析,并促进数据的重用和共享。SSC可以促进协作并利用集体智慧来创建和发现新知识。除了其研究潜力外,我们还描述了它作为教育中的电子学习平台的潜在作用。我们讨论了信息技术方面的经验教训,预测了下一代网络(Web 3.0),并描述了其对生物信息学研究未来的潜在影响。