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Interactive Search and Exploration of Waveform Data with Searchlight

Published:26 June 2016Publication History

ABSTRACT

Searchlight enables search and exploration of large, multi-dimensional data sets interactively. It allows users to explore by specifying rich constraints for the "objects" they are interested in identifying. Constraints can express a variety of properties, including a shape of the object (e.g., a waveform interval of length 10-100ms), its aggregate properties (e.g., the average amplitude of the signal over the interval is greater than 10), and similarity to another object (e.g., the distance between the interval's waveform and the query waveform is less than 5). Searchlight allows users to specify an arbitrary number of such constraints, with mixing different types of constraints in the same query. Searchlight enhances the query execution engine of an array DBMS (currently SciDB) with the ability to perform sophisticated search using the power of Constraint Programming (CP). This allows an existing CP solver from Or-Tools (an open-source suite of operations research tools from Google) to directly access data inside the DBMS without the need to extract and transform it.

This demo will illustrate the rich search and exploration capabilities of Searchlight, and its innovative technical features, by using the real-world MIMIC II data set, which contains waveform data for multi-parameter recordings of ICU patients, such as ABP (Arterial Blood Pressure) and ECG (electrocardiogram). Users will be able to search for interesting waveform intervals by specifying aggregate properties of the corresponding signals. In addition, they will be able to search for intervals similar to already found, where similarity is defined as a distance between the signal sequences.

References

  1. Google or-tools. https://code.google.com/p/or-tools/.Google ScholarGoogle Scholar
  2. Multiparameter intelligent monitoring in intensive care (mimic ii). https://physionet.org/mimic2/.Google ScholarGoogle Scholar
  3. Scidb. http://www.scidb.org/.Google ScholarGoogle Scholar
  4. Tableau. http://www.tableau.com/.Google ScholarGoogle Scholar
  5. P. G. Brown. Overview of scidb: large scale array storage, processing and analysis. In SIGMOD, pages 963--968, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. C. Faloutsos, M. Ranganathan, and Y. Manolopoulos. Fast subsequence matching in time-series databases. In SIGMOD, pages 419--429, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. P. Jayachandran, K. Tunga, N. Kamat, and A. Nandi. Combining user interaction, speculative query execution and sampling in the dice system. VLDB, 7(13):1697--1700, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. A. Kalinin, U. Cetintemel, and S. Zdonik. Interactive data exploration using semantic windows. In SIGMOD, pages 505--516, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. A. Kalinin, U. Cetintemel, and S. Zdonik. Searchlight: Enabling integrated search and exploration over large multidimensional data. VLDB, 8(10):1094--1105, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. I. Lazaridis and S. Mehrotra. Progressive approximate aggregate queries with a multi-resolution tree structure. In SIGMOD, pages 401--412, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. K. Zoumpatianos, S. Idreos, and T. Palpanas. Rinse: Interactive data series exploration with ads+. VLDB, 8(12):1912--1915, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Conferences
      SIGMOD '16: Proceedings of the 2016 International Conference on Management of Data
      June 2016
      2300 pages
      ISBN:9781450335317
      DOI:10.1145/2882903

      Copyright © 2016 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 26 June 2016

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