Advertisement

Process Modelling, Web Services and Geoprocessing

  • Nicolas RegnauldEmail author
  • Guillaume Touya
  • Nicholas Gould
  • Theodor Foerster
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Process modelling has always been an important part of research in generalisation. In the early days this would take the form of a static sequence of generalisation actions, but currently the focus is on modelling much more complex processes, capable of generalising geographic data into various maps according to specific user requirements. To channel the growing complexity of the processes required, better process models had to be developed. This chapter discusses several aspects of the problem of building such systems. As the system gets more complex, it becomes important to be able to reuse components which already exist. Web services have been used to encapsulate generalisation processes in a way that maximises their interoperability and therefore reusability. However, for a system to discover and trigger such a service, it needs to be formalised and described in a machine understandable way, and the system needs to have the knowledge about where and when to use such tools. This chapter therefore explores the requirements and potential approaches to the design and building of such systems.

Keywords

Generalisation Operator Procedural Knowledge Generalisation Process Generalisation System Generalisation Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Alameh N (2003) Chaining geographic information web services. IEEE Internet Comput 07:22–29CrossRefGoogle Scholar
  2. Armstrong MP (1991) Knowledge classification and organization. In: Buttenfield B, McMaster RB (eds) Map generalization: making rules for knowledge representation. Longman, London, pp 86–102Google Scholar
  3. Bader M, Barrault M, Weibel R (2005) Building displacement over a ductile truss. Int J Geog Inform Sci 19(8):915–936CrossRefGoogle Scholar
  4. Balley S, Regnauld N (2011) Models and standards for on-demand mapping. In: Proceedings of the 25th international cartographic conference. Paris, Jul 2011Google Scholar
  5. Balley S, Jaara K, Regnauld N (2012) Towards a prototype for deriving custom maps from multisource data. 15th workshop of the ICA commission on generalisation and multiple representation. Istanbul, Sep 2012Google Scholar
  6. Baranski B (2008) Grid computing enabled web processing service. In: Pebesma E, Bishr M, and Bartoschek T (eds) Proceedings of the 6th geographic information Days, IfGI prints, vol 32. Presented at the GI-days 2008 in the institute for geoinformatics. Muenster, Germany, pp 243–256. Retrieved from http://www.gi-tage.de/archive/2008/downloads/acceptedPapers/Papers/Baranski.pdf
  7. Baranski B, Foerster T, Schäffer B, Lange K (2011) Matching INSPIRE quality of service requirements with hybrid clouds. Transactions GIS 15(s1):125–142. doi: 10.1111/j.1467-9671.2011.01265.x CrossRefGoogle Scholar
  8. Bertolotto M, Egenhofer MJ (2001) Progressive transmission of vector map data over the World Wide Web. Geoinformatica 5(4):345–373CrossRefGoogle Scholar
  9. Brauner J (2012) Ad-hoc-geoprocessing in spatial data infrastructures—formalizations for geooperators. In: Bernard L, Pundt H (eds) 1st AGILE PhD School. Shaker, Wernigerode, GermanyGoogle Scholar
  10. Brenner C, Sester M (2005) Cartographic generalization using primitives and constraints. In: Proceedings of the 22nd international cartographic conference. A Coruna, Jul 2005Google Scholar
  11. Burghardt D, Neun M, Weibel R (2005) Generalisation services on the web—a classification and an initial prototype implementation. Cartography Geogr Inf Sci 32(4):257–268CrossRefGoogle Scholar
  12. Burghardt D, Petzold I, Bobzien M (2010) Relation modelling within multiple representation databases and generalisation services. Cartographic J 47(3):238–249CrossRefGoogle Scholar
  13. Buttenfield (2002) Transmitting vector geospatial data across the internet. GIScience 2002: 51–64Google Scholar
  14. Dean J, Ghemawat S (2004) MapReduce: simplified data processing on large clusters. In: Proceedings of the 6th symposium on operating system design and implementation, San Francisco, CA, Dec 2004Google Scholar
  15. Di L, Chen A, Yang W, Zhao P (2003). The integration of grid technology with OGC web services (OWS) in NWGISS for NASA EOS data. Presented at the GGF8 & HPDC12 2003. Science Press, Seattle, pp 24–27Google Scholar
  16. Douglas D, Peucker T (1973) Algorithms for the reduction of the number of points required to represent a digitised line or its caricature. Can Cartographer 10(2):112–122CrossRefGoogle Scholar
  17. Dutton G, Edwardes A (2006) Ontological modeling of geographical relationships for map generalization. In: Proceedings of the 9th workshop of the ICA commission on map generalization and multiple representation, Portland, USAGoogle Scholar
  18. Edwardes A, Burghardt D, Bobzien M, Harrie L, Reichenbacher T, Sester M, Weibel R (2003) Map generalisation technology: addressing the need for a common research platform. In: Proceedings of the 21st international cartographic conference, Durban, pp 170–179Google Scholar
  19. Foerster T, Stoter J, Köbben B (2007) Towards a formal classification of generalization operators. In: Proceedings of the 23rd international cartographic conference, Moscow, Aug 2007Google Scholar
  20. Foerster T, Stoter J, van Oosterom P (2012a) On-demand base maps on the web generalized according to user profiles. Int J Geogr Inf Sci 26(1):99–121CrossRefGoogle Scholar
  21. Foerster T, Baranski B, Borsutzky H (2012b) Live geoinformation with standardized geoprocessing services. In: Gensel J, Josselin D, Vandenbroucke D (eds) Bridging the geographic information sciences. Springer, Berlin, pp 99–118CrossRefGoogle Scholar
  22. Genesererh MR, Nilsson NJ (1998) Logical foundations of artificial intelligence. Morgan Kaufmann Publishers, Palo AltoGoogle Scholar
  23. Gore A (1998) The digital earth: understanding our planet in the 21st century. Aust surveyor 43(2):89–91CrossRefGoogle Scholar
  24. Gruber T (1993) A translation approach to portable ontology specifications. Knowl Acquisition 5(2):199–220CrossRefGoogle Scholar
  25. Guercke R, Sester M (2011) Building footprint simplification based on hough transform and least squares adjustment. In: Proceedings of the 14th workshop of the ICA commission on generalisation and multiple representation, ParisGoogle Scholar
  26. Harrie LE, Sarjakoski T (2002) Simultaneous graphic generalization of vector data sets. Geoinformatica 6(3):233–261. doi: 10.1023/A:1019765902987 CrossRefGoogle Scholar
  27. Jäger E (1991) Investigations on automated feature displacement for small scale maps in raster format. In: Proceedings of the 15th international cartographic conference, pp 245–256Google Scholar
  28. Janowicz K, Schade S, Broring A, Kessler C, Maue P, Stasch C (2010) Semantic enablement for spatial data infrastructures. Trans GIS 14(2):111CrossRefGoogle Scholar
  29. Jenks GF (1989) Geographic logic in line generalisation. Cartographica 26(1):27–42CrossRefGoogle Scholar
  30. Kilpelainen T (2000) Knowledge acquisition for generalization rules. Cartography Geogr Inf Sci 27(1):41–50CrossRefGoogle Scholar
  31. Kulik L, Duckham M, Egenhofer M (2005) Ontology-driven map generalization. J Vis Lang Comput 16(3):245–267CrossRefGoogle Scholar
  32. Lanig S, Schilling A, Stollberg B, Zipf A (2008). Towards standards-based processing of digital elevation models for grid computing through web processing service (WPS). ICCSA, Lecture notes in computer science vol 5073. Presented at the computational science and its applications—ICCSA 2008. Springer, Perugia, pp 191–203 doi:http://dx.doi.org/10.1007/978-3-540-69848-7_17
  33. Lemmens R, de By RA, Gould M, Wytzisk A, Granell C, van Oosterom P (2007) Enhancing geo-service chaining through deep service descriptions. Trans GIS 11(6):849–871CrossRefGoogle Scholar
  34. Lüscher P, Burghardt D, Weibel R (2007) Ontology-driven enrichment of spatial databases. In: Proceedings of the 10th workshop of the ICA commission on generalisation and multiple representation. Moscow, Aug 2007Google Scholar
  35. Lutz M (2007) Ontology-based descriptions for semantic discovery and composition of geoprocessing services. GeoInformatica 11(1):1–36. doi: 10.1007/s10707-006-7635-9 CrossRefGoogle Scholar
  36. Mackaness WA, Edwards G (2002) The importance of modelling pattern and structure in automated map generalisation. In: Proceedings of the joint ISPRS/ICA workshop on multi-scale representations of spatial data, pp 7–8Google Scholar
  37. Maue P, Schade S, Duchesne P (2009) Semantic annotations in OGC standards open geospatial consortiumGoogle Scholar
  38. McMaster RB, Shea KS (1992) Generalization in digital cartography. Association of American Geographers, Washington DCGoogle Scholar
  39. Mladenic D, Moraru A, Skrjanc M (2011) Deliverable D4.2 model annotation component and guidelines. Envision consortium. http://www.envision-project.eu/2011/01/deliverable-4-2-model-annotation-components-and-guidelines. Accessed 15 Mar 2013
  40. Müller M, Bernard L, Brauner J (2010) Moving code in spatial data infrastructures—web service based deployment of geoprocessing algorithms. Trans GIS 14(S1):101–118Google Scholar
  41. Müller M, Kadner D, Bernard L (2012) Moving code—sharing geospatial computation logic on the web. In: Proceedings of the 15th AGILE international conference on geographic information sciences, AvignonGoogle Scholar
  42. Neun M, Burghardt D (2005) Web services for an open generalisation research platform. In: Proceedings of the 8th ICA workshop on generalisation and multiple representation, A CorunaGoogle Scholar
  43. Noy NF, McGuinness D (2001) Ontology development 101: a guide to creating your first ontology. Stanford University. http://www.ksl.stanford.edu/people/dlm/papers/ontology-tutorial-noy-mcguinness.pdf. Accessed 15 Mar 2013
  44. Regnauld N, McMaster RB (2007) A synoptic view of generalisation operators. In: Mackaness WA, Ruas A, Sarjakoski LT (eds) Generalisation of geographic information. Elsevier Science B.V, Amsterdam, pp 37–66CrossRefGoogle Scholar
  45. Rieger MK, Coulson MRC (1993) Consensus or confusion: cartographers’ knowledge of generalization. Cartographica Int J Geogr Inf Geovisualization 30(2):69–80CrossRefGoogle Scholar
  46. Ruas A, Duchêne C (2007) A prototype generalisation system based on the multi-agent system paradigm. In: Mackaness WA, Ruas A, Sarjakoski LT (eds) The generalisation of geographic information: models and applications. Elsevier, Amsterdam, pp 269–284 (Chapter 14)Google Scholar
  47. Ruas A, Plazanet C (1996) Strategies for automated generalization. In: 7th international symposium on spatial data handling, Delft, pp 319–336Google Scholar
  48. Schaeffer B, Foerster T (2008) A Client for distributed geo-processing and workflow design. J Location Based Serv 2(3):194–210CrossRefGoogle Scholar
  49. Scholten M, Klamma R, Kiehle C (2006) Evaluating performance in spatial data infrastructures for geoprocessing. IEEE Internet Comput 10(5):34–41CrossRefGoogle Scholar
  50. Stigmar H, Harrie L (2011) Evaluation of analytical measures of map legibility. Cartographic J 48(1):41–53CrossRefGoogle Scholar
  51. Stoter J, Burghardt D, Duchêne C, Baella B, Bakker N, Blok C, Pla M, Regnauld N, Touya G, Schmid S (2009) Methodology for evaluating automated map generalization in commercial software. Comput Environ Urban Syst 3(5):311–324CrossRefGoogle Scholar
  52. Swan J, Anand S, Ware M, Jackson M (2007) Automated schematization for web service applications. In: Web and wireless geographical information systems—W2GIS. Cardiff, pp 216–226Google Scholar
  53. Taillandier P, Gaffuri J (2012) Improving map generalisation with new pruning heuristics. Int J Geogr Inf Sci 26(7):1309–1323CrossRefGoogle Scholar
  54. Taillandier P, Duchêne C, Drogoul A (2008) Knowledge revision in systems based on an informed tree search strategy: application to cartographic generalisation. In: Proceedings of the international conference on soft computing as transdisciplinary science and technology (CSTST), Cergy-Pontoise, Jul 2008Google Scholar
  55. Taillandier P, Duchêne C, Drogoul A (2011) Automatic revision of rules used to guide the generalisation process in systems based on a trial and error strategy. Int J Geogr Inf Sci 25(12):1971–1999CrossRefGoogle Scholar
  56. Touya G (2008) First thoughts for the orchestration of generalisation methods on heterogeneous landscapes. In: Proceedings of 11th ICA workshop on generalisation and multiple representation, MontpellierGoogle Scholar
  57. Touya G (2010) Relevant space partitioning for collaborative generalisation. In: Proceedings of 12th ICA workshop on generalisation and multiple representation, ZurichGoogle Scholar
  58. Touya G (2012) Social welfare to assess the global legibility of a generalized map. In: Xiao N, Kwan MP, Goodchild MF, Shekhar S (eds) Geographic information science. 7th international conference, GIScience 2012, Columbus. Lecture notes in computer science, vol 7478. Springer, Berlin, pp 198–211Google Scholar
  59. Touya G, Duchêne C (2011) CollaGen: collaboration between automatic cartographic generalisation processes. In: Ruas A (eds) Advances in cartography and GIScience. Lecture notes in geoinformation and cartography, vol 1. Springer, Berlin, pp 541–558Google Scholar
  60. Touya G, Duchêne C, Ruas A (2010) Collaborative generalisation: formalisation of generalisation knowledge to orchestrate different cartographic generalisation processes. In: Fabrikant S, Reichenbacher T, van Kreveld M, Schlieder C (eds) Geographic information science. Lecture notes in computer science, vol 6292. Springer, Heidelberg, pp 264–278Google Scholar
  61. van Oosterom P (2005) Variable-scale topological data structures suitable for progressive data transfer: the GAP-face tree and GAP-edge forest. Cartography Geogr Inf Sci 32(4):331–346CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nicolas Regnauld
    • 1
    Email author
  • Guillaume Touya
    • 2
  • Nicholas Gould
    • 3
  • Theodor Foerster
    • 4
  1. 1.1Spatial, Tennyson HouseCambridge Business ParkCambridgeUK
  2. 2.Laboratoire COGITIGNSaint-MandéFrance
  3. 3.Manchester Metropolitan UniversityManchesterUK
  4. 4.Institute for GeoinformaticsUniversity of MuensterMünsterGermany

Personalised recommendations