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Making Temporal Search Central in a Spatial Data Infrastructure


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Making Temporal Search Central in a Spatial Data Infrastructure

  1. 1. Making Temporal Search More Central in a Spatial Data Infrastructure Benjamin Lewis, Paolo Corti 2017 2nd International Symposium on Spatiotemporal Computing Harvard University
  2. 2. Thesis • Time is an underutilized dimension for improving search in geosystems. • Straightforward methods exist which can be transformative for research. (Better use of the Temporal is just one of several ways in which SDIs can be modernized.)
  3. 3. GeoPlatform Search UI
  4. 4. GeoNode Search UI
  5. 5. Systems we have been working on 1. WorldMap – General purpose public mapping platform. In existence since 2012. 2. The Billion Object Platform (BOP) – Prototype to lower barriers to access to big streaming datasets. Recently released.
  6. 6. Different systems, common need to improve search 1. WorldMap (Many Datasets) - Thousands of data layers with imperfect metadata. 2. BOP (One Big Dataset) - A billion georeferenced, time stamped tweets.
  7. 7. List of enhancements to be discussed • Time Miner for unstructured text metadata • Sorting BC / AD dates • Time bar for date range definition • Logarithmic time bar increments • Dynamic temporal histogram • Ability to zoom on temporal histogram
  8. 8. Python TimeMiner to enrich metadata • Metadata for map layers is often inconsistent for time referencing. • Standard ways of describing date/time such as ISO 8601 are rarely used. • Temporal characteristics mentioned as unstructured text in the title, abstract, and elsewhere.
  9. 9. Initial simple TimeMiner Logic 1. Look for date in the date range section of the metadata and choose the earlier date. (Date: from Metadata) 2. If there is no #1 above, look for 4 digit numbers in title first, then abstract, which are less than or equal to 2017 (present year) (Date: Detected) 3. If there IS a date in #2 above, check to see whether there is a CE or AD or BCE or BC after it and apply math accordingly (Date: Detected) 4. If there IS NO #2 above, look for 1, 2, or 3 digit numbers with associated CE, AD, BCE, BC, and apply math accordingly (Date: Detected)
  10. 10. Another technique: Historic Periods Example: Chinese Dynasties • Xia, Hsia ca. 2100-1600 BCE • Shang ca. 1600-1050 BCE • Zhou, Chou ca. 1046-256 BCE • Qin, Ch'in 221-206 BCE • Han 206 BCE-220 CE • Sui 581-618 CE • Tang, T'ang 618-906 • Song, Sung 960-1279 • Yuan 1279-1368 • Ming 1368-1644 • Qing, Ch'ing 1644-1912 Source:
  11. 11. WorldMap Search Demo
  12. 12. • animation
  13. 13. • anim
  14. 14. Temporal Histogram
  15. 15. Conclusion • Most spatial data describes events in time though often not explicitly. • When data does have a time component it is often not easily accessed. • An opportunity exists to increase the value of existing data by: 1. Making latent temporal information explicit using enrichment techniques 2. Implementing UI/backend enhancements on existing systems 3. Increase research on space/time data exploration
  16. 16. More information WorldMap / HHypermap • Information open-source-spatiotemporal-search-platform-spatial-data- infrastructures • Source code BOP • Information consultation/project-resume/billion-object-platform-bop • Source code bop
  17. 17. Thank you Benjamin Lewis Paolo Corti

Editor's Notes

  • Today I’m going to talk about work we have been doing at CGA to develop Temporal search capabilities for some geospatial data systems.

    As with most of the work we do here, its undertaken to solve practical problems, problems we faced developing mapping systems for serving an interdisciplinary user community.

  • I will present some ways we are addressing this through data enrichment and UI improvements.
    This is a work in progress.
  • As an example, here we have the UI for the main U.S. Govt Geo-Data search tool.
  • Here is the GeoNode search UI. Buried down here we have the option to key in a start date and an end date.
  • Different contents require different approaches but still there in much in common between the two approaches.

    Being able to search through large holdings and find what one needs for a particular purpose is key in both systems.

    In addition to keyword, spatial location is a useful filter because all records have a spatial extent. Space cuts across disciplines nicely.
    The attempt to add time. Why time? Everything happens sometime. Cuts across disciplines as with space.
  • Any dates determined using the TimeMiner should be denoted as “detected”. Those in metadata will be “from metadata”
  • With demarcations from metadata or detected.
  • Use period name string to define time periods. Can be used with spatial extent to improve accuracy.

    This approach could be applied to other situations where reasonably unique strings are associated with defined time periods. As a starting point:

    ca. = circa = "more or less" or "approximately"
    BCE = Before the Common Era
    B.C. = “before Christ”
    A.D. = Anno Domini (Latin : "In the year of (our) Lord")
  • Ability to sort results in UI
  • Date detected
  • Time bar past
  • Time bar future end
  • The idea here is to give the human user the tools and visual feedback needed to efficiently explore a large collection.