Integration of Temporal and Semantic Components into the Geographic Information through Mark-up Languages. Part I: Definition

  • Willington Siabato
  • Miguel-Angel Manso-Callejo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6782)


This paper raises the issue of a research work oriented to the storage, retrieval, representation and analysis of dynamic GI, taking into account the semantic, the temporal and the spatiotemporal components. We intend to define a set of methods, rules and restrictions for the adequate integration of these components into the primary elements of the GI: theme, location, time [62]. We intend to establish and incorporate three new structures into the core of data storage by using mark-up languages: a semantic-temporal structure, a geosemantic structure, and an incremental spatiotemporal structure. The ultimate objective is the modelling and representation of the dynamic nature of geographic features, establishing mechanisms to store geometries enriched with a temporal structure (regardless of space) and a set of semantic descriptors detailing and clarifying the nature of the represented features and their temporality. Thus, data would be provided with the capability of pinpointing and expressing their own basic and temporal characteristics, enabling them to interact with each other according to their context, and their time and meaning relationships that could be eventually established. All of this with the purpose of enriching GI storing and improving the spatial and temporal analyses.


spatiotemporal temporal reasoning GIS time geosemantic dynamic storage GIR 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Armstrong, M.P. (ed.): Temporality in spatial databases The Urban and Regional Information Systems Association, Falls Church, USA (1988)Google Scholar
  2. 2.
    Association forComputing Machinery,
  3. 3.
    Bates, M.J., Wilde, D.N., Siegfried, S.: An analysis of search terminology used by humanities scholars: the Getty Online Searching Project. The Library Quarterly 63(1), 1–39 (1993)CrossRefGoogle Scholar
  4. 4.
    Berry, B.J.: Approaches to regional analysis: a synthesis. Annals of the Association of American Geographers 54(1), 2–11 (1964)CrossRefGoogle Scholar
  5. 5.
  6. 6.
  7. 7.
    Chen, Y.R., Fabbrizio, G.D., Gibbon, D., Jora, S., Renger, B., Wei, B.: Geotracker: geospatial and temporal RSS navigation. In: WWW 2007, pp. 41–50. ACM Press, New York (2007)Google Scholar
  8. 8.
    Corporation, T.M.: Time Expression Recognition and Normalization Evaluation. In: TERN-2004 Evaluation Workshop, MITRE (2004)Google Scholar
  9. 9.
    Couclelis, H.: Aristotelian Spatial Dynamics in the Age of Geographic Information Systems. In: Egenhofer, M.J., Colledge, R.G. (eds.) Spatial and temporal reasoning in geographic information systems, pp. 109–118. Oxford University Press, New York (1998)Google Scholar
  10. 10.
    DARPA’s InformationExploitation Office,
  11. 11.
    Dipartimento diInformaticai Comunicazione,
  12. 12.
  13. 13.
  14. 14.
    Erwig, M., Güting, R.H., et al.: Spatio-Temporal Data Types: An Approach to Modeling and Querying Moving Objects in Databases. GeoInformatica 3(3), 269–296 (1999)CrossRefGoogle Scholar
  15. 15.
  16. 16.
    Galton, A. (ed.): Qualitative spatial change. Oxford University Press, Oxford (2001)zbMATHGoogle Scholar
  17. 17.
    Galton, A.: Desiderata for a Spatio-temporal Geo-ontology. In: Kuhn, W., Worboys, M.F., Timpf, S. (eds.) COSIT 2003. LNCS, vol. 2825, pp. 1–12. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  18. 18.
    Galton, A.: Fields and objects in space, time, and space-time. Spatial Cognition and Computation 4(1), 39–68 (2004)CrossRefGoogle Scholar
  19. 19.
    Galton, A.: Space, time, and the representation of geographical reality. Topoi 20(2), 173–187 (2001)CrossRefGoogle Scholar
  20. 20.
    Güting, R.H., Böhlen, M.H., Erwig, M., Jensen, C.S., Lorentzos, N.A., Schneider, M., Vazirgiannis, M.: A foundation for representing and querying moving objects. ACM Transactions on Database Systems (TODS) 25(1), 1–42 (2000)CrossRefGoogle Scholar
  21. 21.
    Güting, R.H., Schneider, M.: Moving Objects Databases. Morgan Kaufmann, San Francisco (2005)zbMATHGoogle Scholar
  22. 22.
    Thompson, H.S., Beech, D., Maloney, M., Mendelsohn, N.:
  23. 23.
    Hornsby, K.S., Yuan, M.: Understanding Dynamics of Geographic Domains, 1st edn. CRC Press, USA (2008)zbMATHGoogle Scholar
  24. 24.
    Language, I.S.O.: resource management – Semantic Annotation Framework (SemAF) – Part1: Time and events. Technical Report (ISO/CD 24617-1). ISO, Geneva - Switzerland (2007)Google Scholar
  25. 25.
    Iowa State University and National Science Foundation,
  26. 26.
  27. 27.
  28. 28.
  29. 29.
  30. 30.
    Jones, C.B., Abdelmoty, A.I., Finch, D., Fu, G., Vaid, S.: The SPIRIT spatial search engine: Architecture, ontologies and spatial indexing. In: Egenhofer, M.J., Freksa, C., Miller, H.J. (eds.) GIScience 2004. LNCS, vol. 3234, pp. 125–139. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  31. 31.
    Jones, C.B., Alani, H., Tudhope, D.: Geographical Information Retrieval with Ontologies of Place. In: Montello, D.R. (ed.) COSIT 2001. LNCS, vol. 2205, pp. 322–335. Springer, Heidelberg (2001)Google Scholar
  32. 32.
    Jones, C.B., Purves, R.S.: Geographical Information Retrieval. Intl. J. of Geographical Information Science 22(3), 219–228 (2008)CrossRefGoogle Scholar
  33. 33.
    Sellis, T.K., Koubarakis, M., Frank, A., Grumbach, S., Güting, R.H., Jensen, C., Lorentzos, N.A., Manolopoulos, Y., Nardelli, E., Pernici, B., Theodoulidis, B., Tryfona, N., Schek, H.-J., Scholl, M.O.: Spatio-Temporal Databases. LNCS, vol. 2520. Springer, Heidelberg (2003)CrossRefzbMATHGoogle Scholar
  34. 34.
    Langran, G., Chrisman, N.: A framework for temporal geographic information. Cartographica 25(3), 1–14 (1988)CrossRefGoogle Scholar
  35. 35.
    Langran, G.: A review of temporal database research and its use in GIS applications. Intl. J. of Geographical Information Systems 3(3), 215–232 (1989)CrossRefGoogle Scholar
  36. 36.
    Langran, G.: Issues of implementing a spatiotemporal system. Intl. J. of Geographical Information Systems 7(4), 305–314 (1993)CrossRefGoogle Scholar
  37. 37.
    Langran, G.: Temporal GIS design tradeoffs. URISA Journal 2(2), 16–25 (1990)Google Scholar
  38. 38.
    Langran, G.: Time in geographic information systems. Taylor & Francis, London (1992)Google Scholar
  39. 39.
    Lemmens, R., Wytzisk, A., By, R., Granell, C., et al.: Integrating Semantic and Syntactic Descriptions to Chain Geographic Services. IEEE Internet Computing 10(5), 42–52 (2006)CrossRefGoogle Scholar
  40. 40.
    Manning, C., Schütze, H.: Foundations of statistical natural language processing, 6th edn. MIT Press, Cambridge (2003)zbMATHGoogle Scholar
  41. 41.
    Markowetz, A., Brinkhoff, T., Seeger, B.: Geographic information retrieval. In:Agouris P, Croitoru A (eds.). In: Next generation geospatial information, pp. 5–17. Taylor & Francis, Abington (2005)Google Scholar
  42. 42.
    Martins, B., Manguinhas, H., Borbinha, J., Siabato, W.: A geo-temporal information extraction service for processing descriptive metadata in digital libraries. e-Perimetron 4(1), 25–37 (2009)Google Scholar
  43. 43.
    Mazur, P., Dale, R.: The DANTE temporal expression tagger. In: Vetulani, Z., Uszkoreit, H. (eds.) LTC 2007. LNCS, vol. 5603, pp. 245–257. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  44. 44.
    Mennis, J.L., Peuquet, D.J., Qian, L.: A conceptual framework for incorporating cognitive principles into geographical database representation. Intl. J. of Geographical Information Science 14(6), 501–520 (2000)CrossRefGoogle Scholar
  45. 45.
    Mennis, J.L.: Derivation and implementation of a semantic GIS data model informed by principles of cognition. Computers, Environment and Urban Systems 27(5), 455–479 (2003)CrossRefGoogle Scholar
  46. 46.
    Nixon, V., Hornsby, K.S.: Using geolifespans to model dynamic geographic domains. Intl J of Geographical Information Science 24(9), 1289–1308 (2010)CrossRefGoogle Scholar
  47. 47.
    Office, D.A.: Proceedings of the 6th conference on Message understanding. In: MUC6 1995, Association for Computational Linguistics, Morristown (1995)Google Scholar
  48. 48.
    OGC OGC® KML. OGC Standard (OGC 07-147r2). Open GIS Consortium Inc. (2008)Google Scholar
  49. 49.
    OGC OpenGIS® Geography Markup Language (GML) Encoding Standard 3.2.1. OGC Standard (OGC 07-036). Open Geospatial Consortium Inc. (2007)Google Scholar
  50. 50.
    Openshaw, S.: Two exploratory space-time-attribute pattern analysers relevant to GIS. In: Fotheringham, S., Rogerson, P. (eds.) Spatial analysis and GIS, 1st edn., pp. 83–104. Taylor & Francis, London (1994)Google Scholar
  51. 51.
    Ott, T., Swiaczny, F.: Time-integrative Geographic Information Systems - Management and Analysis of Spatio-Temporal Data, 1st edn. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  52. 52.
    Peuquet, D.J., Duan, N.: An event-based spatiotemporal data model (ESTDM) for temporal analysis of geographical data. Intl J of Geographical Information Systems 9(1), 7–24 (1995)CrossRefGoogle Scholar
  53. 53.
    Peuquet, D.J.: A conceptual framework and comparison of spatial data models. Cartographica 21(4), 66–113 (1984)CrossRefGoogle Scholar
  54. 54.
    Peuquet, D.J.: It’s About Time: A Conceptual Framework for the Representation of Temporal Dynamics in Geographic Information Systems. Annals of the Association of American Geographers 84(3), 441–461 (1994)CrossRefGoogle Scholar
  55. 55.
    Peuquet, D.J.: Making space for time: Issues in space-time data representation. GeoInformatica 5(1), 11–32 (2001)CrossRefzbMATHGoogle Scholar
  56. 56.
    Peuquet, D.J.: Representations of geographic space: toward a conceptual synthesis. Annals of the Association of American Geographers 78(3), 375–394 (1988)CrossRefGoogle Scholar
  57. 57.
    Peuquet, D.J.: Representations of space and time. The Guilford Press, London (2002)Google Scholar
  58. 58.
    Peuquet, D.J.: Theme section on advances in spatio-temporal analysis and representation. ISPRS Journal of Photogrammetry and Remote Sensing 60(1), 1–2 (2005)CrossRefGoogle Scholar
  59. 59.
    Pustejovsky, J., Hanks, P., Saurí, R., et al.: The TIMEBANK corpus. In: Proceedings of the Corpus Linguistics 2003 conference, pp. 647–656 (2003)Google Scholar
  60. 60.
    Lemmens, R.: Semantic interoperability of distributed geo-services, vol.63, (Doctoral Dissertation), NCG, Delft - Netherlands (2006),
  61. 61.
    Siabato, W., Fernández-Wyttenbach, A., Martins, B., Bernabé, M.Á., Álvarez, M.: Análisis semántico del lenguaje natural para expresiones geotemporales. In: Jornadas Técnicas de la IDE de España -JIDEE 2008, Cartográfica de Canarias S.A., Tenerife - España (2008)Google Scholar
  62. 62.
    Sinton, D.F.: The inherent structure of information as a constraint to analysis: Mapped thematic data as a case study. In: First Intl Advanced Study Symposium on topological data structures for GIS, pp. 1–17. Harvard University LCGSA, Cambridge (1978)Google Scholar
  63. 63.
    Snodgrass, R.T.: Temporal databases status and research directions. ACM SIGMOD Record 19(4), 83–89 (1990)CrossRefGoogle Scholar
  64. 64.
    Snodgrass, R.T.: Temporal databases. In: Frank, A.U., Formentini, U., Campari, I., et al. (eds.) GIS 1992. LNCS, vol. 639, pp. 22–64. Springer, Heidelberg (1992), doi:10.1007/3-540-55966-3-2Google Scholar
  65. 65.
  66. 66.
    Spatio Temporal MITRE: SpatialML: Annotation Scheme for Marking Spatial Expressions in Natural Language 3.0. Technical Report ©The MITRE Corporation (2009)Google Scholar
  67. 67.
    Stoimenov, L., Dordevic-Kajan, S.: Framework for semantic GIS interoperability. Facta Universitatis (Series: Mathematics and Informatics) 17(1), 107–125 (2002)zbMATHGoogle Scholar
  68. 68.
    Tanasescu, V., et al.: A Semantic Web GIS based emergency management system. In: Semantic Web for eGovernment 2006, pp. 1–12. Tech University of Athens, Greece (2006)Google Scholar
  69. 69.
  70. 70.
    Turing, A.M.: Computing machinery and intelligence. MIND 59(236), 443–460 (1950)MathSciNetGoogle Scholar
  71. 71.
    Verhagen, M., Mani, I., et al.: Automating Temporal Annotation with TARSQI. In: Interactive Poster and Demonstration Sessions, pp. 81–84. Univ. of Michigan, USA (2005)Google Scholar
  72. 72.
    Verne J: Viaje al centro de la Tierra, vol.19. Casa Editorial El Tiempo, Bogota D.C (2001)Google Scholar
  73. 73.
    Wachowicz, M., Healey, R.G.: Towards temporality in GIS. In: Worboys, M. (ed.) Innovations in GIS: selected papers from the first National Conference on GIS Research UK. Innovations in GIS, vol. 1, pp. 105–115. CRC Press, London (1994)Google Scholar
  74. 74.
    Wachowicz, M., Owens, J.B.: Space-time representations of complex networks: What is next? GeoFocus 9(1), 1–8 (2009)Google Scholar
  75. 75.
    Worboys, M.: A generic model for spatio-bitemporal geographic information. In: Egenhofer, M.J., Colledge, R.G. (eds.) Spatial and Temporal Reasoning in Geographic Information Systems. Spatial Information Systems, pp. 25–39. Oxford University Press, New York (1998)Google Scholar
  76. 76.
    Worboys, M.: A model for spatio-temporal information. In: 5th Intl Symposium on Spatial Data Handling, pp. 602–611. University of South California, USA (1992)Google Scholar
  77. 77.
    Worboys, M.: A unified model for spatial and temporal information. The Computer Journal 37(1), 26–34 (1994)CrossRefGoogle Scholar
  78. 78.
    Worboys, M.: Unifying the spatial and temporal components of geographic information. In: Sixth Intl Symp on Spatial Data Handling, pp. 505–517. Taylor & Francis, London (1994)Google Scholar
  79. 79.
  80. 80.
  81. 81.
    Yuan, M., Hornsby, K.S.: Computation and visualization for understanding dynamics in geographic domains: a research agenda, 1st edn. CRC Press, Boca Raton (2007)CrossRefzbMATHGoogle Scholar
  82. 82.
    Yuan, M., Mark, D.M., Egenhofer, M.J., Peuquet, D.J.: Extensions to Geographic Representation. In: McMaster, R.B., Usery, E.L. (eds.) A Research Agenda for Geographic Information Science, pp. 129–156. CRC Press, Boca Raton (2004)Google Scholar
  83. 83.
    Yuan, M.: Modeling semantical, temporal and spatial information in geographic information systems. In: Craglia, M., Couclelis, H. (eds.) Geographic Information Research: Bridging the Atlantic, vol. 1, pp. 334–347. Taylor & Francis, London - UK (1997)Google Scholar
  84. 84.
    Yuan, M.: Temporal GIS and spatio-temporal modeling. In: 3rd Intl Conf. on Integrating GIS and Environmental Modeling, pp. 21–26. Univ of California, Santa Barbara (1996)Google Scholar
  85. 85.
    Yuan, M.: Use of a Three-Domain Representation to Enhance GIS Support for Complex Spatiotemporal Queries. Transactions in GIS 3(2), 137–159 (1999)MathSciNetCrossRefGoogle Scholar
  86. 86.
    Yuan, M.: Use of knowledge acquisition to build wildfire representation in Geographical Information Systems. Intl J. of Geographical Information Science 11(8), 723–746 (1997)CrossRefGoogle Scholar
  87. 87.
    Yuan, M.: Wildfire conceptual modeling for building GIS space-time models. In: GIS/LIS 1994, pp. 860–889. ASPRS, Falls Church (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Willington Siabato
    • 1
  • Miguel-Angel Manso-Callejo
    • 1
  1. 1.Mercator Research GroupUniversidad Politécnica de MadridMadridSpain

Personalised recommendations