Finding Haystacks with Needles: Ranked Search for Data Using Geospatial and Temporal Characteristics

  • V. M. Megler
  • David Maier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6809)


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 coastalmargin observatory.


spatio-temporal queries querying scientific data metadata 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • V. M. Megler
    • 1
  • David Maier
    • 1
  1. 1.Computer Science DepartmentPortland State UniversityUSA

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