Next-Generation Search Engines for Information Retrieval
- ORNL
In the recent years, there have been significant advancements in the areas of scientific data management and retrieval techniques, particularly in terms of standards and protocols for archiving data and metadata. Scientific data is rich, and spread across different places. In order to integrate these pieces together, a data archive and associated metadata should be generated. Data should be stored in a format that can be retrievable and more importantly it should be in a format that will continue to be accessible as technology changes, such as XML. While general-purpose search engines (such as Google or Bing) are useful for finding many things on the Internet, they are often of limited usefulness for locating Earth Science data relevant (for example) to a specific spatiotemporal extent. By contrast, tools that search repositories of structured metadata can locate relevant datasets with fairly high precision, but the search is limited to that particular repository. Federated searches (such as Z39.50) have been used, but can be slow and the comprehensiveness can be limited by downtime in any search partner. An alternative approach to improve comprehensiveness is for a repository to harvest metadata from other repositories, possibly with limits based on subject matter or access permissions. Searches through harvested metadata can be extremely responsive, and the search tool can be customized with semantic augmentation appropriate to the community of practice being served. One such system, Mercury, a metadata harvesting, data discovery, and access system, built for researchers to search to, share and obtain spatiotemporal data used across a range of climate and ecological sciences. Mercury is open-source toolset, backend built on Java and search capability is supported by the some popular open source search libraries such as SOLR and LUCENE. Mercury harvests the structured metadata and key data from several data providing servers around the world and builds a centralized index. The harvested files are indexed against SOLR search API consistently, so that it can render search capabilities such as simple, fielded, spatial and temporal searches across a span of projects ranging from land, atmosphere, and ocean ecology. Mercury also provides data sharing capabilities using Open Archive Initiatives Protocol for Metadata Handling (OAI-PMH). In this paper we will discuss about the best practices for archiving data and metadata, new searching techniques, efficient ways of data retrieval and information display.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- Work for Others (WFO)
- DOE Contract Number:
- DE-AC05-00OR22725
- OSTI ID:
- 1011015
- Journal Information:
- International Journal of Software Engineering (IJSE), Vol. 2, Issue 1
- Country of Publication:
- United States
- Language:
- English
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