DANS is an institute of KNAW and NWOData Archiving and Networked ServicesData Archiving and Networked ServicesKnowledge – ...
Andrea Scharnhorst – CV•Head of eResearch at DANS and scientific coordinator of the Computational Humanitiesprogramme at t...
Ilya PrigogineEugene GarfieldWerner Ebeling
Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the whole...
BibliometricsScientometricsInformetricsLibrariesScience policyGeneralinformationsciences
Derek de Solla PriceExponential growth of sciencePrice, D. de Solla 1963, Little Science, Big Science, Columbia Univ. Pres...
Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the whole...
Alfred James LotkaScientific productivityA.J. Lotka, The frequency distribution of scientific productivity, J. Wash. Acad....
Samuel C. BradfordLaw of scatteringBRADFORD, S. C. (1934) Sources of information on specific subjects. Engineering, 137, 8...
CommunicationText Actorswords journals references authors institutions countries…Co-word mapsSemantic maps(Callon, Rip,Whi...
www.research-acumen.eu
The Matthew effect for countries
Physics and scientometrics2010
Multipartite networks• Researcher– Has co-authors– Has an affiliation– Has publications– Has citations– Has Age• Researche...
Landscape ideaKnowledge production as search in an unknown landscapeA. Scharnhorst, W. Ebeling (2005): Evolutionary Search...
Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the whole...
Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the whole...
Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the whole...
Visualizing knowldge spaces and landscapes – landscapesbased on networks: Katy Börner, Chaomei Chen, & Kevin Boyack: Visua...
BibliometricsVisualizationSemantic analysisOn-line: http://ella.slis.indiana.edu/%7Ekaty/paper/arist02.pdf
Paul Otlet, Mundaneum, http://www.mundaneum.be/“Alle Kennis van de Wereld” http://www.archive.org/details/paulotletCourtes...
Knowledge Space LabAlmila Akdag Sahal, Cheng Gao, Krzysztof Suchecki,Andrea ScharnhorstDifferent knowledge representations
Dynamic PhenomenatimetimeHow do changes inclassification influencerelational data ?How do changes inrelations changethe cl...
Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the whole...
Evolution of the Wikipediacategory level –top topical levelhttp://arxiv.org/abs/1203.0788Advances in Complex Systems
! !Complexity insights as pointers where to look !
Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the whole...
ANALYZING THE DYNAMICS OF INFORMATIONAND KNOWLEDGE LANDSCAPESPossible use-casesBrowse a collectionor a databaseMap size, s...
Informa on Professionals/Informa on Scien stsSocial Scien stsComputer Scien stsPhysics/Mathema csDigital Humani esInformat...
NARCIS
www.knowescape.org TD1201Chair: A. ScharnhorstViceChair: S. FortunatoWG 1: PhenomenologyA.Slavic/S. ThurnerWG 2: TheoryP. ...
Pointers• LinkedIn• Academia.edu• ResearchGate• Mendeley -> KnowEscape• Arxiv.org• Slideshare• www.knowescape.org• www.eas...
eResearch DANSThank you for your attention!For more information please contactAndrea.scharnhorst@dans.knaw.nlLeen BreureEn...
Knowledge – dynamics – landscape - navigation – what have interfaces to digital libraries to do with physics?
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Knowledge – dynamics – landscape - navigation – what have interfaces to digital libraries to do with physics?

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When we google, search Wikipedia, and share information on Mendeley, we obviously deal with complex networks of information. But also traditional information spaces – the collections of libraries for instance – and their classification systems are evolving complex systems. This talk explores the possibilities to use concepts and methods from statistical physics to analyze information dynamics. We depart from information dynamics in scholarly communication, and point to current encounters between physics and scientometrics. We discuss more in-depth the evolution of category systems in libraries (Universal Decimal Classification) in comparison to on-line spaces (Wikipedia). The talk closes with an introduction into a new European network – the COST Action KnowEscape – in which information professionals, sociologists, computer scientists, physicists and digital humanities scholars in an unique alliance seek for knowledge maps to better navigate through large information spaces.

Talk on June 11, 2013 by Andrea Scharnhorst at the IMT in Lucca, Italy.

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Knowledge – dynamics – landscape - navigation – what have interfaces to digital libraries to do with physics?

  1. 1. DANS is an institute of KNAW and NWOData Archiving and Networked ServicesData Archiving and Networked ServicesKnowledge – dynamics –landscape - navigation – whathave interfaces to digitallibraries to do with physics?Andrea ScharnhorstJune 11, 2013IMT Lucca, Italy
  2. 2. Andrea Scharnhorst – CV•Head of eResearch at DANS and scientific coordinator of the Computational Humanitiesprogramme at the eHumanities group of the Royal Netherlands Academy of Arts andSciences (KNAW) – DANS=Data Archiving and Networked Services Institute (DANS)Analyzing the dynamics of information and knowledge landscapes
  3. 3. Ilya PrigogineEugene GarfieldWerner Ebeling
  4. 4. Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the wholeslide. For all other information please use the slide withpreset style!Scientific development based on competition between scientific fieldsand fieldmobility of scientistsSystem-Umwelt-GrenzeTeilsystem 1 Teilsystem iTeilsystem j0Di0Di1Ai0Aij0, MijAij1x1 xixjAi1CijBijPhysicsEconomicsDataScienceEducationScientificschoolsRetirementFieldmobilityEbeling, W., Scharnhorst, A. (1986) Selforganization Models for Field Mobility of Physicists. Czechoslovak Journal of Physics B36 , pp. 43-46.Bruckner, E., Ebeling, W., Scharnhorst, A. (1990) The Application of Evolution Models in Scientometrics. Scientometrics 18 (1-2), pp. 21-41
  5. 5. BibliometricsScientometricsInformetricsLibrariesScience policyGeneralinformationsciences
  6. 6. Derek de Solla PriceExponential growth of sciencePrice, D. de Solla 1963, Little Science, Big Science, Columbia Univ. Press, New York.For an introduction into Scientometrics see: W. Glänzel, Scientometrics as a researchfield, http://www.norslis.net/2004/Bib_Module_KUL.pdfand F. Havemann (2009) Einführung in die Bibliometrie(http://www.wissenschaftsforschung.de/Havemann2009Bibliometrie.pdf)
  7. 7. Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the wholeslide. For all other information please use the slide withpreset style!
  8. 8. Alfred James LotkaScientific productivityA.J. Lotka, The frequency distribution of scientific productivity, J. Wash. Acad. Sci., 16, 317 (1926).Figure taken fromPiotr Fronczak, Agata Fronczak, Janusz A. Holyst (2006) Publish or perish: analysis of scientific productivity using maximum entropy principle andfluctuation-dissipation theorem. arXiv:physics/0606190v1
  9. 9. Samuel C. BradfordLaw of scatteringBRADFORD, S. C. (1934) Sources of information on specific subjects. Engineering, 137, 85-86. BRADFORD, S. C. (1948) Documentation,London, Lockwood.Figure from Eugen Garfield, Essays of an Information Scientist, Vol:4, p.476-483, 1979-80/ Current Contents, #19, p.5-12, May 12, 1980:Bradford’s Law and Related Statistical Patterns.http://www.garfield.library.upenn.edu/essays/v4p476y1979-80.pdfhttp://en.wikipedia.org/wiki/Bradford%27s_law“if scientific journals are arranged in order ofdecreasing productivity on a givensubject, they may be divided into a nucleus ofjournals more particularly devoted to thesubject and several groups or zonescontaining the same number of articles as thenucleus when the numbers of periodicals inthe nucleus and the succeeding zones willbe as 1: n : n² …”2284 articles in 374 journalsCore C = 40 journals (1024 articles)Bradford’s paradox -> Delineation of fields
  10. 10. CommunicationText Actorswords journals references authors institutions countries…Co-word mapsSemantic maps(Callon, Rip,White)Citation environmentsof journals(Leydesdorff)Maps of science(Boyack, Börner, Klavans;Leydesdorff, Rafols)Bibliographic couplingCitation networksCo-citation networks(Marshokova, Small/Griffith)Productivity(Lotka)Coauthorship(…..)Disciplinary profilesPerformanceImpact(…..)Internationalcollaboration(…..)What is a topic?What is a paradigm?What are fields anddisciplines?What are the hot areas andresearch fronts?What are the knowledge flows?Core and peripheryof knowledge exchange ina globalized economyBiographies, key player,Individual vs group dynamicsKey players, evaluationMeaning of a citation, deeper understanding of knwoledge flowsSentiment of citations Small, Thelwall, Boyack…
  11. 11. www.research-acumen.eu
  12. 12. The Matthew effect for countries
  13. 13. Physics and scientometrics2010
  14. 14. Multipartite networks• Researcher– Has co-authors– Has an affiliation– Has publications– Has citations– Has Age• Researcher/InstitutionsAgent-based-modelling• Epistemic landscape –Weisbuch/Payette – DATA• Research practices– Peers and journals– Time allocation– Careers (building up whiletravelling around)FUTURE RESEARCH
  15. 15. Landscape ideaKnowledge production as search in an unknown landscapeA. Scharnhorst, W. Ebeling (2005): Evolutionary Search Agents in Complex Landscapes. A New Model for the Role of Competence andMeta-competence (EVOLINO and other simulation tools). arxiv.org/abs/physics/0511232W. Ebeling, L. Schimansky-Geier, A. Neiman, A. Scharnhorst (2005) Stochastic dynamics of Active Agents in External Fields. Fluctuationand Noise Letters 5(2), L185-L192
  16. 16. Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the wholeslide. For all other information please use the slide withpreset style!Occupation, observationFitness, valueevaluationSee: Scharnhorst, A. (2001) Constructing Knowledge Landscapes within the Framework of Geometrically Oriented Evolutionary Theories. In: Integrative SystemsApproaches to Natural and Social Sciences. Ed. by M. Matthies, H. Malchow, J. Kriz. Springer, Berlin, pp. 505-515
  17. 17. Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the wholeslide. For all other information please use the slide withpreset style!18),();(),(),( tqMxxqwtqxtqxtCharacteristicsOccupation densityfunctionValuation or Evaluation-landscapeMutation operatorComparison DiffusionMathematical apparatusFeistel, R. Ebeling, W. (1990) Evolution of complex systems.
  18. 18. Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the wholeslide. For all other information please use the slide withpreset style!Source: Places and Spaces – scimaps.org – Klavans/Boyack
  19. 19. Visualizing knowldge spaces and landscapes – landscapesbased on networks: Katy Börner, Chaomei Chen, & Kevin Boyack: VisualizingKnowledge Domains. In Blaise Cronin (Ed.), Annual Review of Information Science &Technology, Volume 37, Medford, NJ: Information Today, Inc./American Society forInformation Science and Technology, chapter 5, pp. 179-255, 2003.
  20. 20. BibliometricsVisualizationSemantic analysisOn-line: http://ella.slis.indiana.edu/%7Ekaty/paper/arist02.pdf
  21. 21. Paul Otlet, Mundaneum, http://www.mundaneum.be/“Alle Kennis van de Wereld” http://www.archive.org/details/paulotletCourtesy of Charles van den HeuvelEpistemic spaces and libraries
  22. 22. Knowledge Space LabAlmila Akdag Sahal, Cheng Gao, Krzysztof Suchecki,Andrea ScharnhorstDifferent knowledge representations
  23. 23. Dynamic PhenomenatimetimeHow do changes inclassification influencerelational data ?How do changes inrelations changethe classification?Courtesy K. Suchecki
  24. 24. Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the wholeslide. For all other information please use the slide withpreset style!Almila Akdag Sahal, Cheng Gao, Krzysztof Suckecki, Andrea Scharnhorst;Places and Spaces, 7th Iteration, see http://www.scimaps.org/flat/exhibit_info/#7
  25. 25. Evolution of the Wikipediacategory level –top topical levelhttp://arxiv.org/abs/1203.0788Advances in Complex Systems
  26. 26. ! !Complexity insights as pointers where to look !
  27. 27. Only use this slide to present a screenshot of an application.As no style is applied, the screenshot can take up the wholeslide. For all other information please use the slide withpreset style!Lambiotte, Ausloos, 2005!, PhysRefE, Physics World
  28. 28. ANALYZING THE DYNAMICS OF INFORMATIONAND KNOWLEDGE LANDSCAPESPossible use-casesBrowse a collectionor a databaseMap size, structure, compositionand evolution of the collectionLocate your search on such aninteractive knowledge map• Domain overview for students, interdisciplinaryteams, lay experts and funding agencies• Tools for scholars of history and philosophy ofscience and bibliometrics• Overview of BigData collections (incl. social media)Given the explosion of information how to navigate to find what isneeded?
  29. 29. Informa on Professionals/Informa on Scien stsSocial Scien stsComputer Scien stsPhysics/Mathema csDigital Humani esInformation professionals• Collections, Information retrieval• WG 1 Phenomenology of knowledgespaces• WG 4 Data curation & navigationSocial scientists• Simulating user behavior• WG 2 Theory of knowledgespaces• WG 4 Data curation &navigationComputer scientists• Semantic web, data models• WG 1 Phenomenology of Knowledge Spaces• WG 4 Data curation &navigationPhysicists, mathematiciansDigital humanities scholars•Collections, interactive design•WG 3 Visual analytics – knowledge maps•WG 4 Data curation & navigationParticipating communities• Structure & evolution ofcomplex knowledgespaces, big data mining• WG 2 Theory ofknowledge spaces• WG 3 Visual analytics –knowledge maps
  30. 30. NARCIS
  31. 31. www.knowescape.org TD1201Chair: A. ScharnhorstViceChair: S. FortunatoWG 1: PhenomenologyA.Slavic/S. ThurnerWG 2: TheoryP. Ahrweiler/P. RichmondWG 3: Visual analyticsA. Akdag/R. LambiotteWG 4: Data curationC. Gueret/P.Mutschke
  32. 32. Pointers• LinkedIn• Academia.edu• ResearchGate• Mendeley -> KnowEscape• Arxiv.org• Slideshare• www.knowescape.org• www.easy.dans.nl -> wikipedia link networks
  33. 33. eResearch DANSThank you for your attention!For more information please contactAndrea.scharnhorst@dans.knaw.nlLeen BreureEnhanced publications,eHistoryDirk RoordaQueries as annotations,CLARIN, Circulation ofknowledgePeter DoorneHistory, Clarin, Dariah,ClariahDirector of DANSRene van HorikSustainability andpermanence, multi-mediasources, APARSEN, NEDIMAHFrank van der MostScientific careers and culturesof data sharing, ACUMENAlbert Moroño PeñuelaSemantic web, CEDARLinda ReijnhoudtNARCIS, VisualizationsKaty BörnerIndiana UniversityVisiting fellow DANS-KNAWChristophe GuéretSemantic web,complex networksCEDAR,PI: WikiRegAshkan AskpourHistory, information sciences,IISHCEDARCristian DinuWikiRegMarat CharlaganovWikiReg

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