Goddard Nigel H, Cannon Robert C, Howell Fred W
Axiope Limited, Charteris Land, 15 St. Johns Street, Edinburgh EH8 8AQ, UK.
Neuroinformatics. 2003;1(3):271-84. doi: 10.1385/NI:1:3:271.
Many areas of biological research generate large volumes of very diverse data. Managing this data can be a difficult and time-consuming process, particularly in an academic environment where there are very limited resources for IT support staff such as database administrators. The most economical and efficient solutions are those that enable scientists with minimal IT expertise to control and operate their own desktop systems. Axiope provides one such solution, Catalyzer, which acts as flexible cataloging system for creating structured records describing digital resources. The user is able specify both the content and structure of the information included in the catalog. Information and resources can be shared by a variety of means, including automatically generated sets of web pages. Federation and integration of this information, where needed, is handled by Axiope's Mercat server. Where there is a need for standardization or compatibility of the structures usedby different researchers this canbe achieved later by applying user-defined mappings in Mercat. In this way, large-scale data sharing can be achieved without imposing unnecessary constraints or interfering with the way in which individual scientists choose to record and catalog their work. We summarize the key technical issues involved in scientific data management and data sharing, describe the main features and functionality of Axiope Catalyzer and Axiope Mercat, and discuss future directions and requirements for an information infrastructure to support large-scale data sharing and scientific collaboration.
生物学研究的许多领域都会产生大量极为多样的数据。管理这些数据可能是一个困难且耗时的过程,尤其是在学术环境中,像数据库管理员这样的信息技术支持人员的资源非常有限。最经济高效的解决方案是那些能让具备最少信息技术专业知识的科学家控制和操作自己桌面系统的方案。Axiope提供了这样一种解决方案,即Catalyzer,它作为一个灵活的编目系统,用于创建描述数字资源的结构化记录。用户能够指定编目中所包含信息的内容和结构。信息和资源可以通过多种方式共享,包括自动生成的网页集。在需要时,这些信息的联合与整合由Axiope的Mercat服务器处理。当需要对不同研究人员所使用结构进行标准化或兼容性处理时,这可以稍后通过在Mercat中应用用户定义的映射来实现。通过这种方式,可以实现大规模的数据共享,而不会施加不必要的限制,也不会干扰个别科学家记录和编目其工作的方式。我们总结了科学数据管理和数据共享中涉及的关键技术问题,描述了Axiope Catalyzer和Axiope Mercat的主要特性和功能,并讨论了支持大规模数据共享和科学合作的信息基础设施的未来方向和要求。