Knowledge and Information Systems

, Volume 51, Issue 1, pp 311–338 | Cite as

A formal framework to represent spatial knowledge

  • Giuseppe Della Penna
  • Daniele Magazzeni
  • Sergio Orefice
Regular Paper


Visual representations are an essential element in human–computer interaction and can be conceived as a collection of graphical objects arranged in a two-dimensional space. It is quite natural to model visual representations through the qualitative relationships holding between their objects, and therefore, qualitative spatial relations are a fundamental way of representing spatial knowledge. To this aim, in this paper we present a framework of qualitative spatial relations providing a general, domain-independent approach to specify visual representations.


Spatial knowledge representation Spatial relations Human–computer interaction Information extraction 


  1. 1.
    Allen JF Maintaining knowledge about temporal intervals. Commun ACM 26(11):832–843. doi: 10.1145/182.358434
  2. 2. (2015) Apache commons scxml.
  3. 3.
    Balbiani P, Condotta J, del Cerro LF (1998) A model for reasoning about bidemsional temporal relations. In: Proceedings of the sixth international conference on principles of knowledge representation and reasoning (KR’98), Trento, Italy, 2–5 June 1998, pp 124–130Google Scholar
  4. 4.
    Chen J, Cohn AG, Liu D, Wang S, Ouyang J, Yu Q (2015) A survey of qualitative spatial representations. Knowl Eng Rev 30:106–136.
  5. 5.
    Clementini E, Di Felice P, Hernández D (1997) Qualitative representation of positional information. Artif Intell 95(2):317–356. doi: 10.1016/S0004-3702(97)00046-5 MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Clementini E, Felice PD, Oosterom PV (1993) A small set of formal topological relationships suitable for end-user interaction. In: Proceedings of the third international symposium on advances in spatial databases, SSD ’93, Springer, London, pp 277–295.
  7. 7.
    Cohn AG, Li S, Liu W, Renz J (2014) Reasoning about topological and cardinal direction relations between 2-dimensional spatial objects. J Artif Intell Res (JAIR) 51:493–532. doi: 10.1613/jair.4513 MathSciNetzbMATHGoogle Scholar
  8. 8.
    Cohn AG, Randell DA, Cui Z (1995) Taxonomies of logically defined qualitative spatial relations. Int J Hum Comput Stud 43(5–6):831–846. doi: 10.1006/ijhc.1995.1077 CrossRefGoogle Scholar
  9. 9.
    Della Penna G, Magazzeni D, Orefice S (2012) A spatial relation-based framework to perform visual information extraction. Knowl Inf Syst 30(3):667–692. doi: 10.1007/s10115-011-0394-4 CrossRefGoogle Scholar
  10. 10.
    Devlin P (2007) Brachytherapy: applications and techniques. Lippincott Williams & Wilkins, PhiladelphiaGoogle Scholar
  11. 11.
    Du Y, Liang F, Sun Y (2012) Integrating spatial relations into case-based reasoning to solve geographic problems. Knowl Based Syst 33:111–123CrossRefGoogle Scholar
  12. 12.
    Dube MP, Egenhofer MJ ( 2014) Partitions to improve spatial reasoning. In: Proceedings of the 1st ACM SIGSPATIAL PhD workshop, SIGSPATIAL PhD ’14, ACM, New York, NY, USA, pp 1:1–1:5. doi: 10.1145/2694859.2694864
  13. 13.
    Egenhofer MJ, Franzosa RD (1991) Point set topological relations. Int J Geogr Inf Syst 5(2):161–174. doi: 10.1080/02693799108927841 CrossRefGoogle Scholar
  14. 14.
    Egenhofer MJ, Mark DM, Herring J ( 1994) The 9-intersection: formalism and its use for natural-language spatial predicates. Technical Report 94-1, National Center for Geographic Information and AnalysisGoogle Scholar
  15. 15.
    Feder J (1971) Plex languages. Inf Sci 3(3):225–241. doi: 10.1016/S0020-0255(71)80008-7 MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Frank AU (1991) Qualitative spatial reasoning with cardinal directions. In: Proceedings 7th Austrian conference on artificial intelligence, ÖGAI-91, Wien, 24–27 Sept 1991, pp 157–167Google Scholar
  17. 17.
    Freksa C (1992) Using orientation information for qualitative spatial reasoning. In: Theories and methods of spatio-temporal reasoning in geographic space, Proceedings of international conference GIS - from space to territory: Theories and methods of spatio-temporal reasoning, Pisa, Italy, 21–23 Sept 1992, pp 162–178. doi: 10.1007/3-540-55966-3_10
  18. 18.
    Fuccella V, Costagliola G (2015) Unistroke gesture recognition through polyline approximation and alignment. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems, CHI 2015, Seoul, Republic of Korea, 18–23 April 2015, pp 3351–3354. doi: 10.1145/2702123.2702505
  19. 19.
    Goyal R, Egenhofer M (2001) Similarity of cardinal directions. In: Jensen C, Schneider M, Seeger B, Tsotras V (eds) Advances in spatial and temporal databases, vol 2121, lecture notes in computer science. Springer, Berlin, pp 36–55. doi: 10.1007/3-540-47724-1_3
  20. 20.
    Hernández D, Clementini E, Felice PD ( 1995) Qualitative distances. In: COSIT, pp 45–57. doi: 10.1007/3-540-60392-1_4
  21. 21.
    Kong J, Zhang K, Zeng X (2006) Spatial graph grammars for graphical user interfaces. ACM Trans Comput Hum Interact 13(2):268–307. doi: 10.1145/1165734.1165739 CrossRefGoogle Scholar
  22. 22.
    Kor A-L, Bennett B (2013) A hybrid reasoning model for “whole and part” cardinal direction relations. Adv Artif Intell 3(3–3):3. doi: 10.1155/2013/205261 Google Scholar
  23. 23.
    Krantz S (1999) Handbook of complex variables. Birkhäuser Basel, Boston. doi: 10.1007/978-1-4612-1588-2
  24. 24.
    Kunze L, Doreswamy KK, Hawes N (2014) Using qualitative spatial relations for indirect object search. In: 2014 IEEE international conference on robotics and automation, ICRA 2014, Hong Kong, China, May 31–June 7, 2014, pp 163–168. doi: 10.1109/ICRA.2014.6906604
  25. 25.
    Li S, Cohn AG (2012) Reasoning with topological and directional spatial information. Comput Intell 28(4):579–616. doi: 10.1111/j.1467-8640.2012.00431.x MathSciNetCrossRefzbMATHGoogle Scholar
  26. 26.
    Li S, Liu W (2015) Cardinal directions: a comparison of direction relation matrix and objects interaction matrix. Int J Geogr Inf Sci 29(2):194–216. doi: 10.1080/13658816.2014.954580 CrossRefGoogle Scholar
  27. 27.
    Li S, Long Z, Liu W, Duckham M, Both A (2015) On redundant topological constraints. Artif Intell 225(C):51–76. doi: 10.1016/j.artint.2015.03.010 MathSciNetCrossRefzbMATHGoogle Scholar
  28. 28.
    Li S, Ying M (2003) Region connection calculus: its models and composition table. Artif Intell 145(1–2):121–146MathSciNetCrossRefzbMATHGoogle Scholar
  29. 29.
    Lober WB, Trigg LJ, Bliss D, Brinkley JM (2001) Iml: an image markup language. In: Proceedings AMIA symposium, pp 403–7.
  30. 30.
    Moens M-F (2006) Information extraction: algorithms and prospects in a retrieval context, vol 21 of the information retrieval series. Springer, New YorkzbMATHGoogle Scholar
  31. 31.
    Moratz R ( 2006) Representing relative direction as a binary relation of oriented points. In: ECAI 2006, 17th European conference on artificial intelligence, Aug 29–Sept 1, 2006, Riva del Garda, Italy, including prestigious applications of intelligent systems (PAIS 2006), Proceedings’, pp 407–411Google Scholar
  32. 32.
    Moratz R, Ragni M (2008) Qualitative spatial reasoning about relative point position. J Vis Lang Comput 19(1):75–98. doi: 10.1016/j.jvlc.2006.11.001 CrossRefGoogle Scholar
  33. 33.
    Mossakowski T, Moratz R (2012) Qualitative reasoning about relative direction of oriented points. Artif Intell 180–181:34–45. doi: 10.1016/j.artint.2011.10.003 MathSciNetCrossRefzbMATHGoogle Scholar
  34. 34.
    Navarrete I, Morales A, Sciavicco G, Cardenas-Viedma M (2013) Spatial reasoning with rectangular cardinal relations. Ann Math Artif Intell 67(1):31–70. doi: 10.1007/s10472-012-9327-5 MathSciNetCrossRefzbMATHGoogle Scholar
  35. 35.
    Pokrajac D, Hoskinson RL, Obradovic Z (2003) Modeling spatial-temporal data with a short observation history. Knowl Inf Syst 5(3):368–386. doi: 10.1007/s10115-002-0094-1 CrossRefGoogle Scholar
  36. 36.
    Randell DA, Cui Z, Cohn AG ( 1992) A spatial logic based on regions and connection. In: Proceedings of the 3rd international conference on principles of knowledge representation and reasoning (KR’92). Cambridge, MA, 25-29 Oct 1992, pp 165–176Google Scholar
  37. 37.
    Schneider M, Chen T, Viswanathan G (2012) Cardinal directions between complex regions. ACM Trans Database Syst 37(2):8:1–8:40. doi: 10.1145/2188349.2188350 CrossRefGoogle Scholar
  38. 38.
    Skiadopoulos S, Koubarakis M (2004) Composing cardinal direction relations. Artif Intell 152(2):143–171MathSciNetCrossRefzbMATHGoogle Scholar
  39. 39.
    Sun H (2009) Efficient algorithms for spatial configuration information retrieval. Knowl Based Syst 22(6):403–409CrossRefGoogle Scholar
  40. 40.
    Tang X (2010) A quantitative directional relations model considering topology and distance. Int J Image Graph Signal Process 2(2):18–24MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  1. 1.Department of Information Engineering, Computer Science and MathematicsUniversity of L’AquilaCoppito, L’AquilaItaly
  2. 2.Department of InformaticsKing’s College LondonLondonUK

Personalised recommendations