Intuitive Knowledge Connectivity: Design and Prototyping of Cross-Platform Knowledge Networks

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9983)


Individual users are overwhelmed with a flood of data. Current big-data strategies focus mainly on organizational uses of data analytics. To address this gap, we focus on personal data management (PDM) in the era of big data and cloud computing. We are developing and testing a PDM software that enables individuals to construct a cross-platform knowledge network by semi-automatically connecting new relevant data to an existing network of interlinked digital objects. Because the cloud-based services that support our knowledge work are currently fragmented, we suggest an integrated federated platform for editing and searching the personal-knowledge context as a network. This forms a directed edge-labeled property multigraph that spans over all of the cloud-based data silos. We present a design and a proof-of-concept implementation of a PDM tool that allows the creation of a personal-knowledge network that incorporates digital objects from different cloud services.


Personal data management Big data Cloud computing Knowledge network Connectivism 



This research is funded by the Hasler Foundation ( under the project “Intuitive Knowledge Connectivity” with grant number 15026.


  1. 1.
    De Filippi, P.: Big data, big responsibilities. Internet Policy Rev. 3 (2014)Google Scholar
  2. 2.
    Hilbert, M., López, P.: The world’s technological capacity to store, communicate, and compute information. Science 332, 60–65 (2011)CrossRefGoogle Scholar
  3. 3.
    Hildebrandt, M., O’Hara, K., Waidner, M.: Personal data management – a structured discussion. In: Digital Enlightenment Yearbook 2013: The Value of Personal Data, pp. 270–287. IOS Press (2013)Google Scholar
  4. 4.
    Lehner, F.: Wissensmanagement: Grundlagen, Methoden und technische Unterstützung. Carl Hanser Verlag GmbH & Co. KG, Munich (2012)CrossRefGoogle Scholar
  5. 5.
    Jones, W.: Personal information management. Annu. Rev. Inf. Sci. Technol. 41, 453–504 (2007)CrossRefGoogle Scholar
  6. 6.
    Razmerita, L., Kirchner, K., Sudzina, F.: Personal knowledge management: the role of Web 2.0 tools for managing knowledge at individual and organisational levels. Online Inf. Rev. 33, 1021–1039 (2009)CrossRefGoogle Scholar
  7. 7.
    Wiederhold, G.: Mediators in the architecture of future information systems. Computer 25, 38–49 (1992)CrossRefGoogle Scholar
  8. 8.
    Milton, N., Shadbolt, N., Cottam, H., Hammersley, M.: Towards a knowledge technology for knowledge management. Int. J. Hum. Comput. Stud. 51, 615–641 (1999)CrossRefGoogle Scholar
  9. 9.
    Shadbolt, N.: Knowledge technologies. Ingenia R. Acad. Eng. 8, 58–61 (2001)Google Scholar
  10. 10.
    Preece, A., Flett, A., Sleeman, D., Curry, D., Meany, N., Perry, P.: Better knowledge management through knowledge engineering. IEEE Intell. Syst. 16, 36–43 (2001)CrossRefGoogle Scholar
  11. 11.
    Nemati, H.R., Steiger, D.M., Iyer, L.S., Herschel, R.T.: Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing. Decis. Support Syst. 33, 143–161 (2002)CrossRefGoogle Scholar
  12. 12.
    Kephart, J.O., Chess, D.M.: The vision of autonomic computing. Computer 36, 41–50 (2003)CrossRefGoogle Scholar
  13. 13.
    Nilsson, M., Palmér, M.: Conzilla - towards a concept browser. Department Computing Science, Centre for User Oriented IT Design, Royal Institute of Technology KTH, Stockholm (1999)Google Scholar
  14. 14.
    Young, R., Letch, N.: Knowledge contexts-through the theoretical lens of Niklas Luhmann. In: Proceedings of PACIS 2003 (2003)Google Scholar
  15. 15.
    Siemens, G.: Connectivism: a learning theory for the digital age. Int. J. Instr. Technol. Distance Learn. 2 (2005)Google Scholar
  16. 16.
    Codd, E.F., Date, C.J.: Interactive support for non-programmers: the relational and network approaches. In: Proceedings of the 1974 ACM SIGFIDET (Now SIGMOD) Workshop on Data Description, Access and Control: Data Models: Data-Structure-Set Versus Relational, pp. 11–41. ACM, New York (1975)Google Scholar
  17. 17.
    Angles, R., Gutierrez, C.: Survey of graph database models. ACM Comput Surv. 40, 1–39 (2008)CrossRefGoogle Scholar
  18. 18.
    Berners-Lee, T.: Information management: a proposal. CERN (1989)Google Scholar
  19. 19.
    Nelson, T.: Literary Machines. Mindful Press, Swarthmore (1981)Google Scholar
  20. 20.
    Knauer, U.: Algebraic Graph Theory: Morphisms, Monoids and Matrices. De Gruyter, Berlin, Boston (2011)CrossRefzbMATHGoogle Scholar
  21. 21.
    Österle, H., Becker, J., Frank, U., Hess, T., Karagiannis, D., Krcmar, H., Loos, P., Mertens, P., Oberweis, A., Sinz, E.J.: Memorandum on design-oriented information systems research. Eur. J. Inf. Syst. 20, 7–10 (2010)CrossRefGoogle Scholar

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© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Lucerne School of Information TechnologyZug-RotkreuzSwitzerland
  2. 2.Institute of Information ManagementUniversity of BernBernSwitzerland
  3. 3.Faculty of Mathematics and Computer ScienceUniversity of HagenHagenGermany

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