GeoInformatica

, Volume 18, Issue 2, pp 405–433 | Cite as

Context-based mobile GeoBI: enhancing business analysis with contextual metrics/statistics and context-based reasoning

  • Belko Abdoul Aziz Diallo
  • Thierry Badard
  • Frédéric Hubert
  • Sylvie Daniel
Article

Abstract

Business professionals are increasingly mobile and should be supported by suitable mobile Decision Support Systems (DSS). In our previous work, we have established that such suitable mobile DSS should be (i) GeoBI(Geospatial Business Intelligence)-enabled and (ii) context-based, and have addressed issues regarding context characterization and context modeling. The present paper deals with mobile GeoBI context-based reasoning. Through realistic scenarios, it highlights (i) the requirement for context-based reasoning to enhance mobile GeoBI experience, (ii) the need for contextual metrics/statistics to help mobile business professionals discover their local context, (iii) the need for crossing business performance metrics with contextual metrics to help mobile business professionals in discovering the context hidden behind business performance figures, and proposes convenient solutions to tackle these needs.

Keywords

Business Intelligence (BI) Mobile Geospatial Business Intelligence (GeoBI) Context-awareness Context reasoning Contextual metrics/statistics Business performance metrics/indicators Service Oriented Architecture (SOA) 

References

  1. 1.
    Richman A, Noble K, Johnson A (2002) When the workplace is many places: the extent and nature of off-site work today. WFD Consulting, WatertownGoogle Scholar
  2. 2.
    Gartner.com. “Gartner forecasts global business intelligence market to grow 9.7 % in 2011,” Gartner, 18 02 2011. [Online]. Available: http://www.gartner.com/it/page.jsp?id=1553215. [Accessed 26 05 2012]
  3. 3.
    Diallo BAA, Badard T, Hubert F, Daniel S (2011) “Towards context awareness mobile Geospatial BI (GeoBI) applications.” In: International Cartography Conference (ICC). ParisGoogle Scholar
  4. 4.
    Diallo BAA, Badard T, Hubert F, Daniel S (2012) Mobile and context-aware GeoBI applications: a multilevel model for structuring and sharing of contextual information. J Geogr Inf Syst (JGIS) 4:425–443Google Scholar
  5. 5.
    Diallo BAA, Badard T, Hubert F, Daniel S (2012) “An OWL-based mobile GeoBI context ontology enabling location-based and context-based reasoning and supporting contextual business analysis.” J Locat Based Serv, vol. under reviewGoogle Scholar
  6. 6.
    Gu T, Wang X, Pung H, Zhang D (2004) “An ontology-based context model in intelligent environments.” In: Communication networks and distributed systems modeling and simulation conference. San Diego, CA, USAGoogle Scholar
  7. 7.
    Cuzzocrea A, Furfaro F, Saccam D (2003) “Hand-olap: a system for delivering olap services on handheld devices.” In: ISADS 2003. Pisa, ItalyGoogle Scholar
  8. 8.
    Maniatis A (2004) “The case for mobile OLAP.” In: First International Workshop on Pervasive Information Management (in conjunction with EDBT’04). Heraklion, GreeceGoogle Scholar
  9. 9.
    Dubé É, Badard T, Bédard Y (2007) “Service web de constitution en temps réel de mini-cubes SOLAP pour clients mobiles.” In: Atelier SIG ubiquitaire–SIG mobiles, CQFD-Géo/Sageo. Clermont-Ferrand, FranceGoogle Scholar
  10. 10.
    BusinessObject.com. “Getting information where and when you need it,” 2008. [Online]. Available: http://www.businessobjects.com/pdf/product/catalog/information_delivery/mobile/mobile_product_sheet.pdf
  11. 11.
    IBM.com. “Cognos 8 Go! mobile extend business intelligence value by accessing information on mobile devices.,” 2009. [Online]. Available: http://www-01.ibm.com/software/data/cognos/products/cognos-8-go/mobile/
  12. 12.
    I. f. S. Research. “Institute for Survey Research–Temple University,” Temple University, 01 01 2012. [Online]. Available: http://www.temple.edu/isr/. [Accessed 19 05 2012]
  13. 13.
    fedstats. “fedstats,” fedstats, 12 03 2007. [Online]. Available: http://www.fedstats.gov/. [Accessed 15 05 2012]
  14. 14.
    statcan. “statcan,” statcan, 30 04 2012. [Online]. Available: http://www.statcan.gc.ca. [Accessed 15 05 2012]
  15. 15.
    EuroStat. “EuroStat, your key to European statistics,” EuroStat, 16 06 2012. [Online]. Available: http://epp.eurostat.ec.europa.eu/. [Accessed 16 06 2012]
  16. 16.
    Black K (2011) Business statistics, contemporary decision making. West Publishing, Los AngelesGoogle Scholar
  17. 17.
    Hebeler J, Fisher M, Blace R, Perez-Lopez A (2009) Semantic web programming. Wiley Publishing, IncGoogle Scholar
  18. 18.
    Wikipedia. “Chinese Canadian,” 01 10 2012. [Online]. Available: http://en.wikipedia.org/wiki/Chinese_Canadian#Language. [Accessed 01 10 2012]
  19. 19.
    Hayes P, Eskridge TC, Mehrotra M, Bobrovniko D, Reichherzer T, Saavedra R (2005) “COE: tools for collaborative ontology development and reuse.” In: Knowledge Capture Conference (K-CAP) 2005Google Scholar
  20. 20.
    Perry M, Herring J (2012) “GeoSPARQL—a geographic query language for RDF data.” Open Geospatial ConsortiumGoogle Scholar
  21. 21.
    Microsoft (2009) “Architectural patterns and styles.” In: Microsoft® application architecture guide, 2nd edition (Patterns & Practices). Microsoft PressGoogle Scholar
  22. 22.
    Badard T, Bédard Y, Hubert F, Bernier E, Dubé É (2008) Web services oriented architectures for mobile SOLAP applications. Int J Web Eng Technol (IJWET) 4(4):434–464CrossRefGoogle Scholar
  23. 23.
    Lhotka R (2005) “Is SOA just N-tier in other clothing?,” Magenic Technologies, http://www.lhotka.net/decks/vslive05/Is%20SOA%20Just%20N-Tier.pdf
  24. 24.
    AlShahwan F, Moessner K. “Providing SOAP web services and RESTful web services from mobile hosts.” In: In Internet and Web Applications and Services (ICIW), 2010 Fifth International Conference on (pp. 174–179). IEEE., Guildford, UK, 2010, May 9–15Google Scholar
  25. 25.
    Zur Muehlen M, Nickerson JV, Swenson KD (2005) Developing web services choreography standards—the case of REST vs. SOAP. Decis Support Syst 40(1):9–29CrossRefGoogle Scholar
  26. 26.
    Pautasso C (2009) RESTful web service composition with BPEL for REST. Data Knowl Eng 68(9):851–866CrossRefGoogle Scholar
  27. 27.
    Richardson L, Ruby S (2007) RESTful web services, O'Reilly Media, IncorporatedGoogle Scholar
  28. 28.
    Grzech A, Swiatek P (2009) Modeling and optimization of complex services in service-based systems. Cybern Syst 40:706–723CrossRefGoogle Scholar
  29. 29.
    Milanovic M, Malek M (2004) Current solutions for web service composition. IEEE Internet Comput 8(6):51–59CrossRefGoogle Scholar
  30. 30.
    Akram A, Meredith D, Allan R (2006) “Evaluation of BPEL to scientific workflows.” In: In Cluster Computing and the Grid, 2006. CCGRID 06. Sixth IEEE International Symposium on (vol. 1, pp. 269–274). IEEEGoogle Scholar
  31. 31.
    He K (2009) “Integration and orchestration of heterogeneous services.” In: In pervasive computing (JCPC), December 2009 Joint Conferences on (pp. 467–470). IEEEGoogle Scholar
  32. 32.
  33. 33.
    Kiehle C, Greve K, Heier C (2007) Requirements for next generation spatial data infrastructures–standardized web based geoprocessing and web service orchestration. Trans GIS 11(6):819–834CrossRefGoogle Scholar
  34. 34.
    Mühl G, Ulbrich A, Herrmann K, Weis T (2004) Disseminating information to mobile clients using publish-subscribe. IEEE Internet Comput 8(3):46–53CrossRefGoogle Scholar
  35. 35.
    Franklin M, Zdonik S (1997) “A framework for scalable dissemination-based information in proceedings of the ACM OOPSLA Systems Conf.” AtlantaGoogle Scholar
  36. 36.
    Bozdag E, Duersen A (2008) “An adaptive push/pull algorithm for AJAX applications.” In: AEWSEGoogle Scholar
  37. 37.
    Cugola G, Nitto ED (2001) “Using a publish/subscribe middleware to support mobile computing.” Heidelberg, GermanyGoogle Scholar
  38. 38.
    Jacobsen HA (2001) “Middleware services for selective and location-based information dissemination in mobile wireless networks.” In: Advanced topic workshop on middleware for mobile computing. Heidelberg, GermanyGoogle Scholar
  39. 39.
    Podnar I, Hauswirth M, Jazayeri M (2002) “Mobile push: delivering content to mobile users.” In: ICDCSW“02Google Scholar
  40. 40.
  41. 41.
  42. 42.
    Google I. “GCM architectural overview,” 2012. [Online]. Available: http://developer.android.com/google/gcm/gcm.html
  43. 43.
    Microsoft. “Push notications for windows phone,” 2011. [Online]. Available: http://msdn.microsoft.com/en-us/library/ff402537(v=VS.92).aspx. [Accessed 2011]
  44. 44.
    Horrocks I, Patel-Schneider PF, Boley H, Tabet S, Grosof B, Dean M. “SWRL: a semantic web rule language,” 21 05 2004. [Online]. Available: http://www.w3.org/Submission/SWRL/. [Accessed 03 07 2012]
  45. 45.
    Carroll JJ, Dickinson I, Dollin C, Reynolds D, Seaborne A, Wilkinson K (2004) “Jena: implementing the semantic web recommendations.” In: 13th World Wide Web Conference, WWW2004Google Scholar
  46. 46.
    Wang XH, Zhang DQ, Gu T, Pung HK (2004) “Ontology based context modeling and reasoning using OWL.” In: 2nd IEEE Conf. Pervasive Computing and Communications (PerCom 2004) Workshop on Context Modeling and ReasoningGoogle Scholar
  47. 47.
    Ejigu D, Scuturici M, Brunie L (2007) “An ontology-based approach to context modeling and reasoning in pervasive computing.” In: CoMoRea Workshop of the IEEE International Conference (PerCom’07). New York, USAGoogle Scholar
  48. 48.
    Kumar P, Gopalan S, Sridhar V (2005) “Context enabled multi-CBR based recommendation engine for ecommerce.” In: IEEE International Conference on e-Business Engineering, Beijing, ChinaGoogle Scholar
  49. 49.
    Stefanov V, List B (2006) “Business metadata for the DataWarehouse–weaving enterprise goals and multidimensional models.” In: 10th IEEE Int.Enterprise Distributed Object Computing Conference WorkshopsGoogle Scholar
  50. 50.
    Cabanac G, Chevalier M, Ravat F, Teste O (2007) “An annotation management system for multidimensional databases.” In: In data warehousing and knowledge discovery. Springer Berlin, Heidelberg, pp 89–98Google Scholar
  51. 51.
    Rouse M. “call failure rate (CFR),” SearchNetworking, 01 08 2006. [Online]. Available: http://searchnetworking.techtarget.com/definition/call-failure-rate. [Accessed 18 06 2012]
  52. 52.
    Station OI. “Access failure rate and drop call rate,” Radio Frequency Optimisation IBase Station, 08 03 2011. [Online]. Available: http://rf-optimization.blogspot.ca/2010/03/access-failure-rate-and-drop-call-rate.html. [Accessed 18 06 2012]

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Belko Abdoul Aziz Diallo
    • 1
  • Thierry Badard
    • 1
  • Frédéric Hubert
    • 1
  • Sylvie Daniel
    • 1
  1. 1.Centre de Recherche en GéomatiqueUniversité LavalQuébecCanada

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