Finding Haystacks with Needles: Ranked Search for Data Using Geospatial and Temporal Characteristics
Sponsor
This work is supported by NSF award OCE-0424602.
Document Type
Post-Print
Publication Date
2011
Subjects
Geographic information systems -- Data processing, Database management, Spatial analysis (Statistics), Metadata, Information storage and retrieval systems
Abstract
The past decade has seen an explosion in the number and types of environmental sensors deployed, many of which provide a continuous stream of observations. Each individual observation consists of one or more sensor measurements, a geographic location, and a time. With billions of historical observations stored in diverse databases and in thousands of datasets, scientists have difficulty finding relevant observations. We present an approach that creates consistent geospatial-temporal metadata from large repositories of diverse data by blending curated and automated extracts. We describe a novel query method over this metadata that returns ranked search results to a query with geospatial and temporal search criteria. Lastly, we present a prototype that demonstrates the utility of these ideas in the context of an ocean and coastal margin observatory.
Persistent Identifier
http://archives.pdx.edu/ds/psu/13226
Citation Details
Megler, Veronika Margaret and Maier, David, "Finding Haystacks with Needles: Ranked Search for Data Using Geospatial and Temporal Characteristics" (2011). Computer Science Faculty Publications and Presentations. 129.
http://archives.pdx.edu/ds/psu/13226
Description
This is the authors' final version of a chapter that subsequently appeared in Scientific and Statistical Database Management, © Springer-Verlag Berlin Heidelberg 2011. Available at DOI: 10.1007/978-3-642-22351-8_4