Gordana Dodig Crnkovic
School of Innovation, Design and Engineering, Computer Science Laboratory, Mälardalen University, Sweden
Juan M. Duran
SimTech, Universität Stuttgart, Deutschland \ University of Córdoba, Argentina
Davor Slutej
ABB, Sweden \ Mälardalen University, Sweden
Download articlePublished in: Proceedings of SIGRAD 2010
Linköping Electronic Conference Proceedings 52:13, p. 77-83
With the rapidly growing amounts of information; visualization is becoming increasingly important; as it allows users to easily explore and understand large amounts of information. However the field of information visualization currently lacks sufficient theoretical foundations. This article addresses foundational questions connecting information visualization with computing and philosophy studies. The idea of multiscale information granulation is described based on two fundamental concepts: information (structure) and computation (process). A new information processing paradigm of Granular Computing enables stepwise increase of granulation/aggregation of information on different levels of resolution; which makes possible dynamical viewing of data. Information produced by Google Earth is an illustration of visualization based on clustering (granulation) of information on a succession of layers. Depending on level; specific emergent properties become visible as a result of different ways of aggregation of data/information. As information visualization ultimately aims at amplifying cognition; we discuss the process of simulation and emulation in relation to cognition; and in particular visual cognition.
[Bar02] BARGIELA A. PEDRYCZ W.: Granular Computing: An Introduction. Kluwer; 2002. 2
[Bar09] BARBEROUSSE A. FRANCESCHELLI S. I. C.: Computer simulations as experiments. Synthese 169; 3 (2009); 557–574. 5
[Bur05] BURGIN M.: Super-Recursive Algorithms. Springer Monographs in Computer Science; 2005. 2
[Bur10] BURGIN M.: Information and Computation. World Scientific Publishing Co. Series in Information Studies; 2010; ch. Information Dynamics in a Categorical Setting. 2
[Cha07] CHAITIN G.: Computation; Information; Cognition. The Nexus and The Liminal. Cambridge Scholars Publishing; 2007; ch. Epistemology as Information Theory„ pp. 2–18. 2
[Che10] CHEN C.: Information visualization. Wiley Interdisciplinary Review: Computational Statistics 2; 4 (2010); 387–403. 1; 5
[Con25] CONGER G.: The doctrine of levels. The Journal of Philosophy 22 (1925); 309–321. 2
[Cor95] CORNING P.: Synergy and self-organization in the evolution of complex systems. Systems Research 12; 2 (1995); 89–121. 3
[Cra72] CRAIK F.I.M. LOCKHART R.: Levels of processing: a framework for memory research. Journal of Verbal Learning and Verbal Behavior 11 (1972); 671–684. 3
[DC06] DODIG-CRNKOVIC G.: Investigations into information semantics and ethics of computing; 2006. 2
[DC08] DODIG-CRNKOVIC G.: Knowledge generation as natural computation. Journal of Systemics; Cybernetics and Informatics 6 (2008). 3
[DC10] DODIG-CRNKOVIC G.: The cybersemiotics and infocomputationalist research programmes as platforms for knowledge production in organisms and machines. Entropy 12 (2010); 878–901. 2
[Dia07] DIAMANT E.: Modeling visual information processing in brain: A computer vision point of view and approach. Advances in Brain; Vision; and Artificial Intelligence; Lecture Notes in Computer Science 4729 (2007); 62–71. 4
[Dur10] DURÁN J. M.: Thinking machines and the philosophy of computer science: Concepts and principles; Information Science Reference. IGI Global; 2010; ch. Computer simulations and traditional experimentation: from a material point of view; pp. 294– 310. 4
[Flo08a] FLORIDI L.: A defence of informational structural realism. Synthese 161; 2 (2008); 219–253. 1
[Flo08b] FLORIDI L.: The method of levels of abstraction. Minds and Machines 18; 3 (2008); 303–329. 3
[Fri08] FRIENDLY M.: Milestones in the history of thematic cartography; statistical graphics; and data visualization; 2008. 5
[Gie09] GIERE R.: Is computer simulation changing the face of experimentation? Philosophical Studies 143 (2009); 59–62. 5
[GM95] GELL-MANN M.: The Quark and the Jaguar: Adventures
in the Simple and the Complex. Owl Books; 1995. 3
[Goe93] GOERTZEL B.: The Evolving Mind. 1993. 3
[Gol99] GOLDSTEIN J.: Emergence as a construct: History and issues. Emergence: Complexity and Organization 1; 1 (1999); 49–72. 3
[Gua02] GUALA F.: Model-Based Reasoning: Science; Technology. Kluwer; 2002; ch. Models; simulations; and experiments; pp. 59–74. 5
[Har96] HARTMANN S.: Simulation and Modelling in the Social Sciences from the Philosophy of Science Point of View. Kluwer; 1996; ch. The world as a Process: Simulations in the natural and social science; pp. 77–100. 4
[Hof09] HOFFMAN D.: Object Categorization: Computer and Human Perspectives. Cambridge University Press; 2009; ch. The Interface Theory of Perception: Natural Selection Drives True Perception to Swift Extinction. 3
[Hum90] HUMPHREYS P.: Computer simulations. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association (1990); 497–506. 4
[Lam08] LAM H.: A framework of interaction costs in information visualization. IEEE Trans Vis Comput Graph 14 (2008); 1149–1156. 1
[Llo06] LLOYD S.: Programming the Universe: A Quantum Computer Scientist Takes On the Cosmos. Knopf; 2006. 1
[Mac04] MACLENNAN B.: Natural computation and non-turing models of computation. Theoretical Computer Science 317 (2004); 115–145. 2
[Mar82] MARR D.: Vision: a computational investigation into the human representation and processing of visual information. W. H. Freeman; 1982. 4
[McN10] MCNAUGHTONA B. L.: Cortical hierarchies; sleep; and the extraction of knowledge from memory. Artificial Intelligence 174; 2 (2010); 205–214. 3
[Mil56] MILLER G. A.: The magical number seven; plus or minus two: some limits on our capacity for processing information. Psychological Review 63 (1956); 81–97. 3
[Min10] MINSKY M.: Information and Computation. World Scientific Publishing Co. Series in Information Studies; 2010; ch. Interior Grounding; Reflection; and Self-Consciousness. 3; 4
[Mor05] MORGAN M.: Experiments versus models: New phenomena; inference and surprise. Journal of Economic Methodology 12; 2 (2005); 317–329. 5
[Mor09] MORRISON M.: Models; measurement and computer simulation: the changing face of experimentation. Philosophical Studies 143 (2009); 33–47. 5
[Mue10] MUELLER G. D.-C. V.: Information and Computation. World Scientific Publishing Co. Series in Information Studies2; 2010; ch. A Dialogue Concerning Two World Systems: Info- Computational vs. Mechanistic. 2
[Nee43] NEEDHAM J.: Herbert Spencer Lecture. Time; the refreshing river. 1943. 3
[New82] NEWELL A.: The knowledge level. Artificial Intelligence 18; 1 (1982). 4
[Nor07] NORTH A. K. J. S. J. F. C.: Workshop report: informationvisualization—human-centered issues in visual representation; interaction; and evaluation. Inf Vis 6 (2007); 189–196. 1
[Par09] PARKER W.: Does matter really matter? computer simulations; experiments; and materiality. Synthese 169; 3 (2009); 483–496. 5
[San04] SANDERS L. F. J. W.: Yearbook of the artificial—nature; culture and technology; models in contemporary sciences. Peter Lang; 2004; ch. The method of abstraction; pp. 177–220. 2
[Sta08] STASKO Z. L. N. N. J.: Distributed cognition as a theoretical framework for information visualization. IEEE Trans Vis Comput Graph 14 (2008); 1173–1180. 1; 6
[Stj97] STJERNFELT E. C. S. K. F.: Explaining emergence: Towards and ontology of levels. Journal for General Philosophy of Science 28 (1997); 83–119. 3
[Ull06] ULLMAN S.: Object recognition and segmentation by a fragment-based hierarchy. Trends in Cognitive Sciences 11 (2006); 58–64. 3
[Ved10] VEDRAL V.: Decoding Reality: The Universe as QuantumInformation. Oxford University Press; 2010. 1
[Win09] WINSBERG E.: A tale of two methods. Synthese 169; 3; (2009); 575–590. 5
[Yao09] YAO Y.: Human-Centric Information Processing Through Granular Modelling. Springer-Verlang; 2009; ch. Integrative Levels of Granularity; pp. 31–47. 2; 3
[Zad98] ZADEH L. A.: Some reflections on soft computing; granular computing and their roles in the conception; design and utilization of information/intelligent systems. Soft Computing 2 (1998); 23–25. 2
[Zei05] ZEILINGER A.: The message of the quantum. Nature (2005); 438–743. 1