摘要: One of the largest continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available. Approac... 展开 One of the largest continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available. Approaches used in Earth science research such as case study analysis and climatology studies involve gathering discovering and gathering diverse data sets and information to support the research goals. Research based on case studies involves a detailed description of specific weather events using data from different sources, to characterize physical processes in play for a specific event. Climatology-based research tends to focus on the representativeness of a given event, by studying the characteristics and distribution of a large number of events. This allows researchers to generalize characteristics such as spatio-temporal distribution, intensity, annual cycle, duration, etc. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the datasets of interest can obtain the specific files they need using these systems. However, in cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. In these cases, a search process needs to be organized around the event rather than observing instruments. In addition, the existing data systems assume users have sufficient knowledge regarding the domain vocabulary to be able to effectively utilize their catalogs. These systems do not support new or interdisciplinary researchers who may be unfamiliar with the domain terminology. This paper presents a specialized search, aggregation and curation tool for Earth science to address these existing challenges. The search tool automatically creates curated 'Data Albums', aggregated collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non-relevant information and data. 收起