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Supporting Situation Awareness in Spatio-Temporal Databases

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Abstract

Situation awareness refers to the capability of systems to perceive an existing or predicted context that determines the values of variables in a changing environment. Despite the enhanced support for managing temporal data, current database systems still lack mechanisms for handling highly dynamic situations in which data may change frequently. We present first results from an ongoing research project investigating these missing database features. In particular, we identify (i) the requirements for representing complex spatio-temporal data, (ii) the reasoning capabilities needed for detecting valid relationships between situations, and (iii) the operators necessary for supporting situation-based reasoning. Our investigations are based on a new perception concept, which comprises interval timestamped data derived from observed events and processed using the sequenced semantics. Perceptions provide a high level (and qualitative) description of past and current situations, complemented by projections into the future.

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References

  1. Allen JF (1983) Maintaining knowledge about temporal intervals. Commun ACM 26(11):832–843

    Article  MATH  Google Scholar 

  2. Alvaro P et al (2010) Dedalus: Datalog in time and space. Datalog, pp 262–281

    Google Scholar 

  3. Behrend A et al (2015) Mastering situation awareness in healtcare database systems. IRI, pp 334–341

    Google Scholar 

  4. Behrend A, Schüller G (2014) A case study in optimizing continuous queries using the magic update technique. SSDBM, pp 1–4

  5. Belleghem KV et al (1995) Combining situation calculus and event calculus. ICLP, pp 83–97

    Google Scholar 

  6. Böhlen MH, Jensen CS, Snodgrass RT (2000) Temporal statement modifiers. TODS 25(4):48

    Article  MATH  Google Scholar 

  7. Büscher W et al (2013) Milchvieh-Informationsmanagement auf Versuchsbetrieben – Beispielanwendungen und Nutzen für Praxisbetriebe. GIL Jahrestagung, pp 31–34

    Google Scholar 

  8. Dignös A, Böhlen MH, Gamper J (2012) Temporal alignment. SIGMOD, pp 433–444

    Google Scholar 

  9. Dignös A, Böhlen MH, Gamper J (2014) Overlap interval partition join. SIGMOD, pp 1459–1470

    Google Scholar 

  10. Duggan J (2014) The case for personal data-driven decision making. PVLDB 7(11):943–946

    Google Scholar 

  11. Gawlick D (2015) Mastering situation awareness: the next frontier? CIDR

    Google Scholar 

  12. Kaufmann M et al (2013) Timeline index: a unified data structure for processing queries on temporal data in SAP HANA. SIGMOD, pp 1173–1184

    Google Scholar 

  13. Kowalski RA, Sergot MJ (1986) A logic-based calculus of events. New Gener Comput 4(1):67–95

    Article  Google Scholar 

  14. Labrinidis A (2015) The Big Data – same humans problem. CIDR

    Google Scholar 

  15. Lazaridis I, Mehrotra S, Porkaew K (2001) Database support for situational awareness. Computer Science Handbook. Rockwell LLC, California

  16. Liu ZH, Behrend A, Chan E, Gawlick D, Ghoneimy A (2012) Kids – a model for developing evolutionary database applications. DATA, pp 129–134

    Google Scholar 

  17. McCarthy J, Hayes PJ (1969) Some philosophical problems from the standpoint of artificial intelligence. Mach Intell 4:463–502

    MATH  Google Scholar 

  18. Schüller G, Behrend A, Manthey R (2010) AIMS: an SQL-based system for airspace monitoring. IWGS, pp 31–38

    Google Scholar 

  19. Wieringa RJ (2003) Design methods for reactive systems: Yourdon, Statemate and the UML. Morgan Kaufmann Publishers, San Francisco

    Google Scholar 

Download references

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Correspondence to Andreas Behrend.

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Behrend, A., Schmiegelt, P. & Dohr, A. Supporting Situation Awareness in Spatio-Temporal Databases. Datenbank Spektrum 16, 207–218 (2016). https://doi.org/10.1007/s13222-016-0233-6

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  • DOI: https://doi.org/10.1007/s13222-016-0233-6

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