Data from: The new bioinformatics: integrating ecological data from the gene to the biosphere

Bioinformatics, the application of computational tools to the management and analysis of biological data, has stimulated rapid research advances in genomics through the development of data archives such as GenBank, and similar progress is just beginning within ecology. One reason for the belated adoption of informatics approaches in ecology is the breadth of ecologically pertinent data (from genes to the biosphere) and its highly heterogeneous nature. The variety of formats, logical structures, and sampling methods in ecology create significant challenges. Cultural barriers further impede progress, especially for the creation and adoption of data standards. Here we describe informatics frameworks for ecology, from subject-specific data warehouses, to generic data collections that use detailed metadata descriptions and formal ontologies to catalog and cross-reference information. Combining these approaches with automated data integration techniques and scientific workflow systems will maximize the value of data and open new frontiers for research in ecology.生物信息学（Bioinformatics）是将计算工具应用于生物数据管理与分析的学科，依托基因银行（GenBank）这类数据档案库的开发，推动了基因组学领域研究的快速进展；而类似的发展态势在生态学领域才刚刚拉开序幕。生态学领域之所以迟迟未能普及信息学方法，原因之一在于生态学相关数据的覆盖范围极广（从基因层面延伸至生物圈），且数据性质高度异质。生态学数据在格式、逻辑结构与采样方法上的多样性，带来了诸多严峻挑战。文化层面的壁垒进一步阻碍了发展进程，尤其是在数据标准的制定与采纳环节。本文将介绍面向生态学领域的信息学框架，涵盖针对特定学科的数据仓库，以及借助详尽的元数据（metadata）描述与形式化本体（ontologies）实现信息编目与交叉引用的通用数据集合。将这些方法与自动化数据集成技术及科学工作流系统（scientific workflow systems）相结合，将最大化数据的应用价值，并为生态学研究开辟全新的前沿方向。