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Data Intensiveness and Cognitive Complexity in Contemporary Collaboration and Decision Making Settings

  • Spyros Christodoulou
  • Nikos Karacapilidis
  • Manolis Tzagarakis
  • Vania Dimitrova
  • Guillermo de la Calle
Chapter
Part of the Studies in Big Data book series (SBD, volume 5)

Abstract

This chapter reviews the state-of-the-art on collaboration and decision making support in contemporary settings. Related issues concerning integration technologies are also discussed. The methodologies, tools and approaches discussed in the chapter are considered with respect to the information overload and cognitive complexity dimensions. The chapter aims to provide useful insights concerning the exploitation and advancement of existing collaboration and decision making support technologies.

Keywords

Collaboration support  Decision making Integration Data intensiveness Cognitive complexity State-of-the-art 

References

  1. 1.
    Economist: A special report on managing information: data, data everywhere. Economist (2010)Google Scholar
  2. 2.
    Schick, A.: Information overload: a temporal approach. Acc. Organ. Soc. 15(3), 199–220 (1990)CrossRefGoogle Scholar
  3. 3.
    Kirsh, D.: A few thoughts on cognitive overload. Intellectica 1(30), 19–51 (2000)Google Scholar
  4. 4.
    Batra, D.: Cognitive complexity in data modeling: causes and recommendations. Requirements Eng. 12, 231–244 (2007)Google Scholar
  5. 5.
    Thompson, J.D.: Organizations in Action. McGraw-Hill, New York (1967)Google Scholar
  6. 6.
    Gorry, G.A., Scott Morton, M.: A framework for management information systems. Sloan Manage. Rev. 13(1), 50–70 (1971)Google Scholar
  7. 7.
    Pearson, J.M., Shim, J.P.: An empirical investigation into DSS structures and environments. Decis. Support Syst. 13, 141–158 (1995)CrossRefGoogle Scholar
  8. 8.
    Forgionne, G., Gupta, J., Mora, M.: Decision making support systems: achievements, challenges and opportunities. In: Mora, M., Forgionne, G., Gupta, J. (eds.) Decision Making Support Systems: Achievements and Challenges for the New Decade, pp. 392–403. Idea Group, Hershey (2002)CrossRefGoogle Scholar
  9. 9.
    Shim, J.P., Warkentin, M., Courtney, J.F., Power, D.J., Sharda, R., Carlsson, C.: Past, present and future of decision support technology. Decis. Support Syst. 33, 111–126 (2002)CrossRefGoogle Scholar
  10. 10.
    DeSanctis, G., Gallupe, R.B.: A foundation for the study of group decision support systems. Manage. Sci. 33(5), 589–609 (1987)CrossRefGoogle Scholar
  11. 11.
    Arnott, D., Pervan, G.: A critical analysis of decision support systems research. J. Inf. Technol. 20(2), 67–87 (2005)CrossRefGoogle Scholar
  12. 12.
    Courtney, J.: Decision making and knowledge management in inquiring organizations: toward a new decision making paradigm for DSS. Decis. Support Syst. 31, 17–38 (2001)CrossRefGoogle Scholar
  13. 13.
    Alter, S.: Why persist with DSS when the real issue is improving decision making? In: Jelassi, T., Klein, M.R., Mayon-White, W.M. (eds.) Decision Support Systems: Experiences and Expectations, IFIP, pp. 1–11. North-Holland, Amsterdam (1992)Google Scholar
  14. 14.
    Angehrn, A., Jelassi, T.: DSS research and practice in perspective. Decis. Support Syst. 12, 267–275 (1994)CrossRefGoogle Scholar
  15. 15.
    Turban, E., Aronson, J.E.: Decision Support Systems and Intelligent Systems, 6th edn. Prentice Hall, Upper Saddle River (2001)Google Scholar
  16. 16.
    O’Brien, James, Marakas, George: Introduction to Information Systems. McGraw-Hill, Inc., New York (2009)Google Scholar
  17. 17.
    Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2nd edn. Wiley, New York (2002)Google Scholar
  18. 18.
    Thomsen, E.: OLAP Solutions: Building Multidimensional Information Systems, 2nd edn. Wiley, New York (2002)Google Scholar
  19. 19.
    Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery in databases. AI Mag. 17, 37–54 (1996)Google Scholar
  20. 20.
    Han, J., , KC-C.: Data Mining for Web Intelligence. Computer. 35(11), 54–60 (2002)Google Scholar
  21. 21.
    Karacapilidis, N.: An overview of future challenges of decision support technologies. In: Gupta, J., Forgionne, G., Mora, M. (eds.) Intelligent Decision-Making Support Systems: Foundations, Applications and Challenges, pp. 385–399. Springer, London (2006)CrossRefGoogle Scholar
  22. 22.
    Smoliar, S.W.: Interaction management: the next (and necessary) step beyond knowledge management. Bus. Process Manage. J. 9(3), 337–352 (2003)CrossRefGoogle Scholar
  23. 23.
    Prahalad, C.K., Hamel, G.: The core competence of the corporation. Harv. Bus. Rev. 68(3), 79–91 (1990)Google Scholar
  24. 24.
    Nonaka, I.: A dynamic theory of organizational knowledge creation. Organ. Sci. 5(1), 14–37 (1994)CrossRefGoogle Scholar
  25. 25.
    Cohendet, P., Steinmueller, W.E.: The codification of knowledge: a conceptual and empirical exploration. Ind Corp. Change 9(2), 195–209 (2000)CrossRefGoogle Scholar
  26. 26.
    Holsapple, C.W., Whinston, A.B.: Decision Support Systems: A Knowledge-Based Approach. West Publishing Company, Saint Paul (1996)Google Scholar
  27. 27.
    Bhagat, J., Tanoh, F., Nzuobontane, E., Laurent, T., Orlowski, J., Roos, M., Wolstencroft, K., Aleksejevs, S., Stevens, R., Pettifer, S., Lopez, R., Goble, C.A.: BioCatalogue: a universal catalogue of web services for the life sciences. Nucleic Acids Res. 38(Web Server issue), W689–W694 (2010)Google Scholar
  28. 28.
    Eemeren, F.H. van, Grootendorst, R., and Snoeck Henkemans, A.F. (eds.) Fundamentals of Argumentation Theory: A Handbook of Historical Backgrounds and Contemporary Developments. Lawrence Erlbaum Associates, Mahwah, NJ (1996)Google Scholar
  29. 29.
    Provis, C.: Negotiation, persuasion and argument. Argumentation 18, 95–112 (2004)CrossRefGoogle Scholar
  30. 30.
    Leuf, B., Cunningham, W.: The Wiki Way: Quick Collaboration on the Web. Addison-Wesley, Boston (2001). ISBN 0-201-71499-XGoogle Scholar
  31. 31.
    Hanneman A., Riddle M.: Introduction to social network methods. http://www.faculty.ucr.edu/hanneman/nettext/ (2005)
  32. 32.
    Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)Google Scholar
  33. 33.
    Scheuer O., Loll F., Pinkwart N., McLaren M.B.: Computer-supported argumentation: a review of the state of the art. Int. J. Comput.-Support. Collab. Learn. 5(1), 43–102 (2010)Google Scholar
  34. 34.
    Eppler, M.J., Mengis, J.: The concept of information overload: a review of literature from organization science, accounting, marketing, mis, and related disciplines. Inf. Soc. 20, 325–344 (2004)CrossRefGoogle Scholar
  35. 35.
    Palla, G., Barabási, A.L., Vicsek, T.: Quantifying social group evolution. Nature 446(7136), 664–667 (2007)CrossRefGoogle Scholar
  36. 36.
    Palla, G., Derefny, I., Farkas, I., Vicsek, T.: Uncovering the overlapping community structure of complex networks in nature and society. Nature 435(9), 814–818 (2005)CrossRefGoogle Scholar
  37. 37.
    Masthoff, J.: Group modeling: selecting a sequence of television items to suit a group of viewers. User Model. User-Adap. Inter. 14(1), 37–85 (2004)CrossRefGoogle Scholar
  38. 38.
    Lin, Y.-R., Chi, Y., Zhu, S., Sundaram, H., Tseng, B.: Facetnet: a framework for analyzing communities and their evolutions in dynamic networks. In: Proceeding of the 17th International Conference on World Wide Web, WWW ‘08. ACM, Beijing, China (2008)Google Scholar
  39. 39.
    Cheng, R., Vassileva, J.: Design and evaluation of an adaptive incentive mechanism for sustained educational online communities. J. User Model. User Adap. Inter. V16(3), 321–348 (2006)CrossRefGoogle Scholar
  40. 40.
    Bretzke, H., Vassileva, J.: Motivating cooperation on peer to peer networks. In: 9th International Conference on User Modelling 2003. Springer, Berlin (2003)Google Scholar
  41. 41.
    Kleanthous, S., Dimitrova, V.: Modelling semantic relationships and centrality to facilitate community knowledge sharing. In: Proceedings of the 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH’08). Springer, Berlin (2008)Google Scholar
  42. 42.
    Kleanthous, S., Dimitrova, V.: Analyzing community knowledge sharing behavior, user modeling. In: Adaptation, and Personalization. Springer, Berlin (2010)Google Scholar
  43. 43.
    Davies, J., Duke, A., Sure, Y.: OntoShare: a knowledge management environment for virtual communities of practice. In: Proceedings of the International Conference on Knowledge Capture, K-CAP ‘03. ACM, Sanibel Island, FL, USA (2003)Google Scholar
  44. 44.
    Kleanthous, S., Dimitrova, V.: Detecting changes over time in a knowledge sharing community. In: Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on WI and IAT. IEEE Computer Society, Washington, DC, USA (2009)Google Scholar
  45. 45.
    Song, X., Tseng, B., Lin, C.-Y. and Sun, M.-T. (2005): ExpertiseNet: relational and evolutionary expert modeling. In: Lecture Notes in Computer Science, vol. 3538. Springer, HeidelbergGoogle Scholar
  46. 46.
    Fu, Y., Xiang, R., Liu, Y., Zhang, M., Ma, S.: Finding experts using social network analysis. In: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI ‘07. IEEE Computer Society, Silicon Valley, CA, USA (2007)Google Scholar
  47. 47.
    Lin, Y.-R., Sundaram, H., Chi, Y., Tatemura, J., Tseng, B.: Blog community discovery and evolution based on mutual awareness expansion. In: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI ‘07. IEEE Computer Society, Silicon Valley, CA, USA (2007)Google Scholar
  48. 48.
    Zhang, J., Ackerman, M., Adamic, L.: Expertise networks in online communities: structure and algorithms. In: International Conference on WWW 2007. ACM, Alberta, Canada (2007)Google Scholar
  49. 49.
    Hubscher, R., Puntambekar, S.: Modeling learners as individuals and as groups. In: Adaptive Hypermedia and Adaptive Web-Based Systems. pp. 300–303 (2004)Google Scholar
  50. 50.
    Kay, J., Maisonneuve, N., Yacef, K., Reimann, P.: The big five and visualisations of team work activity. In: Intelligent Tutoring Systems 2006. Lecture Notes in Computer Science, vol. 4053/2006. Springer, Berlin (2006)Google Scholar
  51. 51.
    Falkowski, T., Barth, A., Spiliopoulou, M.: DENGRAPH: a density-based community detection algorithm. In: IEEE/WIC/ACM International Conference on Web Intelligence. IEEE Computer Society, Silicon Valley (2007)Google Scholar
  52. 52.
    Falkowski, T., Spiliopoulou, M.: Users in volatile communities: studying active participation and community evolution. In: Proceedings of the International Conference on User Modeling 2007. LNCS, vol. 4511/2007. Springer, Berlin (2007)Google Scholar
  53. 53.
    Mohammed, S., Dumville, B.C.: Team mental models in a team knowledge framework: expanding theory and measurement across disciplinary boundaries. J. Organ. Behav. 22(2), 89–106 (2001)Google Scholar
  54. 54.
    Ilgen, D.R., et al.: Teams in Organizations: from input-process-output models to IMOI models. Annu. Rev. Psychol.(56), 517–543 (2005)Google Scholar
  55. 55.
    Wenger, E.: Communities of practice: learning as a social system. Syst. Thinker 9(5), 2–3 (1998)Google Scholar
  56. 56.
    Upton, K., Kay, J.: Narcissus: group and individual models to support small group work. In: Proceedings of the 17th International Conference on UMAP. Springer, Trento (2009)Google Scholar
  57. 57.
    Sankaranarayanan, K., Vassileva, J.: Visualizing reciprocal and non-reciprocal relationships in an online community. In: Proceedings of International Workshop on Adap-tation and Personalization for Web 2.0 (AP-Web 2.0 2009). UMAP’09, CEUR Workshop Proceedings, Trento, Italy (2009)Google Scholar
  58. 58.
    Shami, S., Yuan, C., Cosley, D., Xia, L., Gay, G.: That’s what friends are for: facilitating ‘who knows what’ across group boundaries. In: Proceedings of the ACM 2007 GROUP Conference. ACM, FL, USA (2007)Google Scholar
  59. 59.
    Ardissono, L., Bosio, G.G.A., Petrone, G.: Context-aware notification management in an integrated collaborative environment. In: Proceedings of International Workshop on Adaptation and Personalization for Web 2.0 (AP-Web 2.0 2009). UMAP’09, Trento, Italy (2009)Google Scholar
  60. 60.
    Baghaei, N., Mitrovic, T.: From modelling domain knowledge to metacognitive skills: extending a constraint-based tutoring system to support collaboration. In: International Conference on User Modeling 2007. Springer, Corfu (2007)Google Scholar
  61. 61.
    Farzan, R., DiMicco, J., Brownholtz, B.: Spreading the honey: a system for maintaining an online community. In: Proceedings of the ACM GROUP 2009 Conference. ACM, FL, USA (2009)Google Scholar
  62. 62.
    Kleanthous, S.: Intelligent support for knowledge sharing in virtual communities. Ph.D. thesis, University of Leeds, UK (2010)Google Scholar
  63. 63.
    Ziegler, P. and Dittrich, K.R.: Three decades of data integration—all problems solved? In: 18th IFIP World Computer Congress (WCC 2004), vol. 12. Building the Information Society, vol. 2004, pp. 3–12 (2004)Google Scholar
  64. 64.
    Anguita, A., Martin, L., Perez-Rey, D., Maojo, V.: A review of methods and tools for database integration in biomedicine. Curr. Bioinform. 5(4), 253–269 (2010)Google Scholar
  65. 65.
    Lindberg, C.: The unified medical language system (UMLS) of the national library of medicine. J. Am. Med. Rec. Assoc. 61(5), 40–42 (1990)Google Scholar
  66. 66.
    Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E.: The protein data bank. Nucleic Acids Res. 28(1), 235–242 (2000)CrossRefGoogle Scholar
  67. 67.
    Hulo, N., Bairoch, A., Bulliard, V., Cerutti, L., De Castro, E., Langendijk-Genevaux, P.S., Pagni, M., Sigrist, C.J.: The PROSITE database. Nucleic Acids Res. 34(Database issue) (2006)Google Scholar
  68. 68.
    Etzold, T., Argos, P.: SRS-an indexing and retrieval tool for flat file data libraries. Comput. Appl. Biosci. CABIOS 9(1), 49–57 (1993)Google Scholar
  69. 69.
    Maglott, D., Ostell, J., Pruitt, K.D., Tatusova, T.: Entrez Gene: gene-centered information at NCBI. Nucleic Acids Res. 35(Database issue), D26–D31 (2007)Google Scholar
  70. 70.
    Shah, S.P., Huang, Y., Xu, T., Yuen, M.M., Ling, J., Ouellette, B.F.: Atlas—a data warehouse for integrative bioinformatics. BMC Bioinform. 6(1), 34+ (2005)Google Scholar
  71. 71.
    Lee, T.B., Fielding, R., Masinter, L.: Uniform resource identifier (URI): generic syntax. RFC 3986 (2005)Google Scholar
  72. 72.
    Zhu, X., Wang, J.: MyBASE: a database for genome polymorphism and gene function studies of Mycobacterium. BMC Microbiol. 9, 40+ (2009)Google Scholar
  73. 73.
    Sujansky, W.: Heterogeneous database integration in biomedicine. J. Biomed. Inform. 34(4), 285–298 (2001)CrossRefGoogle Scholar
  74. 74.
    Molina, H.G., Papakonstantinou, Y., Quass, D., Rajaraman, A., Sagiv, Y., Ullman, J.D., Vassalos, V., Widom, J.: The TSIMMIS approach to mediation: data models and languages. J. Intel. Inf. Syst. 8(2), 117–132 (1997)CrossRefGoogle Scholar
  75. 75.
    Tomasic, A., Raschid, L., Valduriez, P.: Scaling access to heterogeneous data sources with DISCO. IEEE Trans. Knowl. Data Eng. 10(5), 808–823 (1998)CrossRefGoogle Scholar
  76. 76.
    Liu, L., Pu, C.: An adaptive object-oriented approach to integration and access of heterogeneous information sources. Distrib. Parallel Databases 5, 167–205 (1997)CrossRefGoogle Scholar
  77. 77.
    Adali, S., Candan, K.S., Papakonstantinou, Y., Subrahmanian, V.S.: Query caching and optimization in distributed mediator systems. SIGMOD Rec. 25(2), 137–146 (1996)CrossRefGoogle Scholar
  78. 78.
    Freier, A., Hofestädt, R., Lange, M., Scholz, U., Stephanik, A.: BioDataServer: a SQL-based service for the online integration of life science data. Silicon Biol. 2(2), 37–57 (2002)Google Scholar
  79. 79.
    Arens, Y., Chee, C.Y., Hsu, C.N., Knoblock, C.A.: Retrieving and integrating data from multiple information sources. Int. J. Coop. Inf. Syst. 2(2), 127–158 (1993)CrossRefGoogle Scholar
  80. 80.
    Knoblock, C.A., Minton, S., Ambite, J.L., et al.: The Ariadne approach to web-based information integration. Int. J. Coop. Inf. Syst. 10(1–2), 145–169 (2001)CrossRefGoogle Scholar
  81. 81.
    Stevens, R., Baker, P., Bechhofer, S., Ng, G., Jacoby, A., Paton, N.W., Goble, C.A., Brass, A.: TAMBIS: transparent access to multiple bioinformatics information sources. Bioinformatics 16(2), 184–185 (2000). (Oxford, England)Google Scholar
  82. 82.
    Mena, E., Kashyap, V., Sheth, A.P., Illarramendi, A.: OBSERVER: an approach for query processing in global information systems based on interoperation across pre-existing ontologies. In: Conference on Cooperative Information Systems, pp. 14–25 (1996)Google Scholar
  83. 83.
    Köhler, J., Philippi, S., Lange, M.: SEMEDA: ontology based semantic integration of biological databases. Bioinformatics 19(18), 2420–2427 (2003)CrossRefGoogle Scholar
  84. 84.
    Pérez-Rey, D., Maojo, V., García-Remesal, M., Alonso-Calvo, R., Billhardt, H., Martin-Sánchez, F., Sousa, A.: ONTOFUSION: ontology-based integration of genomic and clinical databases. Comput. Biol. Med. 36(7–8), 712–730 (2006)CrossRefGoogle Scholar
  85. 85.
    Fielding, R.T.: Architectural styles and the design of network-based software architectures. Ph.D. thesis (2000)Google Scholar
  86. 86.
    Hadley, M.J.: Web application description language (WADL). Technical report, Mountain View, CA, USA (2006)Google Scholar
  87. 87.
    Chinnici, R., Moreau, J.-J., Ryman, A., Weerawarana, S.: Web services description language (WSDL) Version 2.0 Part 1: core language. Technical report (2007)Google Scholar
  88. 88.
    Mandel, L.: Describe REST Web services with WSDL 2.0 (2008)Google Scholar
  89. 89.
    Pautasso, C., Zimmermann, O., Leymann, F.: Restful web services vs. “big” web services: making the right architectural decision. In: Proceeding of the 17th International Conference on World Wide Web, WWW ‘08, pp. 805–814. ACM, New York, USA (2008)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Spyros Christodoulou
    • 1
  • Nikos Karacapilidis
    • 1
  • Manolis Tzagarakis
    • 1
  • Vania Dimitrova
    • 2
  • Guillermo de la Calle
    • 3
  1. 1.University of Patras and Computer Technology Institute & Press “Diophantus”Rio PatrasGreece
  2. 2.School of ComputingUniversity of LeedsLeedsUK
  3. 3.School of Computer ScienceUniversidad Politécnica de MadridMadridSpain

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