Scientific Cooperation Engineering

  • Sabina JeschkeEmail author
  • Wolfgang Bleck
  • Anja Richert
  • Günther Schuh
  • Wolfgang Schulz
  • Martina Ziefle
  • André Bräkling
  • André Calero Valdez
  • Kirsten Dahmen
  • Ulrich Jansen
  • Claudia Jooß
  • Sarah L. Müller
  • Ulrich Prahl
  • Anne Kathrin Schaar
  • Mamta Sharma
  • Thomas Thiele


Scientific Cooperation Engineering researches, fosters and supports scientific cooperation on all hierarchical levels and beyond scientific disciplines as a key resource for innovation in the Cluster of Excellence. State-of-the-art research methods—such as structural equation models, success models, or studies on success factors—that are frequently used in IS research are applied to create profound knowledge and insights in the contribution and optimal realization of scientific inter and trans-disciplinary communication and cooperation. A continuous formative evaluation is used to derive and explore insights into interdisciplinary collaboration and innovation processes from a management perspective. In addition, actor-based empirical studies are carried out to explore critical factors for interdisciplinary cooperation and intercultural diversity management. Based on these results, workflows, physical networking events and tailor-made training programs are created and iteratively optimized towards the cluster’s needs. As Scientific Cooperation Engineering aims to gain empirical and data-driven knowledge, a Scientific Cooperation Portal and a prototypic flowchart application are under development to support workflows and project management. Furthermore, data science methods are currently implemented to recognize synergetic patterns based on bibliometric information and topical proximity, which is analyzed via project terminologies.


Knowledge Management Interdisciplinary Research Critical Incident Diversity Management Interdisciplinary Collaboration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Aboelela SW, Larson E, Bakken S, Carrasquillo O, Formicola A, Glied SA, Haas J, Gebbie KM (2007) Defining interdisciplinary research: conclusions from a critical review of the literature. Health Serv Res 42(1p1):329–346. doi: 10.1111/j.1475-6773.2006.00621.x
  2. Aram JD (2004) Concepts of interdisciplinarity: configurations of knowledge and action. Hum Relat 57(4):379–412CrossRefGoogle Scholar
  3. Baer M, Niessen A, Ruenzi S (2007) The impact of work group diversity on performance: large sample evidence from the mutual fund industryGoogle Scholar
  4. Bantel KA, Jackson SE (1989) Top management and innovations in banking: does the composition of the top team make a difference? Strateg Manage J 10(S1):107–124CrossRefGoogle Scholar
  5. Bassett-Jones N (2005) The paradox of diversity management, creativity and innovation. Creativity Innov Manage 14(2):169–175CrossRefGoogle Scholar
  6. Bergmann M, Schramm E (eds) (2008) Transdisziplinäre Forschung: Integrative Forschungsprozesse verstehen und bewerten. Campus Verlag, Frankfurt, New YorkGoogle Scholar
  7. Blei DM, Ng AY, Jordan MI (2003) Latent dirichlet allocation. J. Mach. Learn. Res. 3:993–1022zbMATHGoogle Scholar
  8. Brooke J (1996) SUS—a quick and dirty usability scale. Usability evaluation in industry 189(194):4–7Google Scholar
  9. Bruns S, Calero Valdez A, Greven C, Ziefle M, Schroeder U (2015) What should I read next? A personalized visual publication recommender system. In: Human interface and the management of information. Information and knowledge in context. Springer, Berlin, pp 89–100Google Scholar
  10. Bullinger H-J, Bauer W, Kern P (2009) Innovationen der Arbeit: Zukunft für Menschen durch nachhaltige Arbeitskonzepte. In: Spath D (ed) Arbeits- und Dienstleistungsforschung als Innovationstreiber: [Bilanzen, Herausforderungen, Zukünfte; Fachtagung, 22. Mai 2009]. Fraunhofer-Verl., Stuttgart, pp 4–14Google Scholar
  11. Bundesministerium für Wirtschaft und Technologie (ed) (2008) Kompetenznetze initiieren und weiterentwickeln – Netzwerke als Instrument der Innovationsförderung, des Wirtschaftswachstums und Standortmarketings, 2nd edn., BerlinGoogle Scholar
  12. Calero Valdez A, Bruns S, Greven C, Schroeder U, Ziefle M (2015) What do my colleagues know? Dealing with cognitive complexity in organizations through visualizations. In: Learning and collaboration technologies. Springer, Berlin, pp 449–459Google Scholar
  13. Calero Valdez A, Schaar AK, Ziefle M, Holzinger A, Jeschke S, Brecher C (2014) Using mixed node publication network graphs for analyzing success in interdisciplinary teams. In: Automation, communication and cybernetics in science and engineering 2013/2014. Springer, Berlin, pp 737–749Google Scholar
  14. Caniëls M, Bakens R (2012) The effects of Project Information Systems in decision making in a multi project environment. Int J Project Manage 30:162–175Google Scholar
  15. Caye J-M, Teichmann C, Strack R, Haen P, Bird S, Frick G (2011) Hard-Wiring Diversity into Your Business. BCGGoogle Scholar
  16. Chakrabarti S, van den Berg M, Dom B (1999) Focused crawling: a new approach to topic-specific web resource discovery. Comput Netw 31:1623–1640CrossRefGoogle Scholar
  17. Cluster of Excellence (2012) Integrative production technology for high-wage countries: renewal proposal for a cluster of excellence—excellence initiative by the German Federal and State Governments to promote science and research at German Universities (Unpublished)Google Scholar
  18. Cox T (1994) Cultural diversity in organizations: theory, research and practice. Berrett-Koehler Publishers, OaklandGoogle Scholar
  19. Defila R, DiGiulio A (1998) Interdisziplinarität und Disziplinarität. In: Olbertz J-H (ed) Zwischen den Fächern - über den Dingen?: Universalisierung versus Spezialisierung akademischer Bildung. Leske + Budrich, Opladen, pp 111–137CrossRefGoogle Scholar
  20. Deinhammer R, Universität Salzburg Poverty Research Group, others (2003) Was heißt interdisziplinäres Arbeiten?: FWF (Austrian Science Fund): Research project Y 164. University of Salzburg/Poverty Research GroupGoogle Scholar
  21. DFG—Deutsche Forschungsgemeinschaft (ed) (2006) 1. Ausschreibung in der Exzellenzinitiative: Auswahl der Antragsteller, BonnGoogle Scholar
  22. Eppler MJ (2007) Managing information quality: increasing the value of information in knowledge-intensive products and processes, 2nd edn. Springer, Berlin, New YorkGoogle Scholar
  23. European Institute of Innovation and Technology Innovation Communities (2015). Accessed 9 Aug 2015
  24. Feldman R, Sanger J (2007) The text mining handbook: advanced approaches in analyzing unstructured data. Cambridge University Press, Cambridge, New YorkGoogle Scholar
  25. Flanagan JC (1954) The critical incident technique. Psychol Bull 51(4):327–358. doi: 10.1037/h0061470 CrossRefGoogle Scholar
  26. Gebert D (2004) Durch diversity zu mehr Team-innovativitat? Betriebswirtschaft-Stuttgart 64(4):412–430Google Scholar
  27. Gibbons M (1994) The new production of knowledge: the dynamics of science and research in contemporary societies. SAGE Publications, Thousand OaksGoogle Scholar
  28. Gratton L, Erickson TJ (2007) 8 ways to build collaborative teams. Harv Bus Rev 85(11):100Google Scholar
  29. Hoffman LR (1959) Homogeneity of member personality and its effect on group problem-solving. J Abnormal Social Psychol 58(1):27CrossRefGoogle Scholar
  30. Hoffman M, Bach FR, Blei DM (2010) Online learning for latent dirichlet allocation. In: Lafferty JD, Williams C, Shawe-Taylor J, Zemel RS, Culotta A (eds) Advances in neural information processing systems 23. Curran Associates, Inc, pp 856–864Google Scholar
  31. Holzinger A, Ofner B, Stocker C, Calero Valdez A, Schaar AK, Ziefle M, Dehmer M (2013) On graph entropy measures for knowledge discovery from publication network data. In: Availability, reliability, and security in information systems and HCI. Springer, Berlin, pp 354–362Google Scholar
  32. Hübenthal U (1991) Interdisziplinäres Denken: Versuch einer Bestandsaufnahme und Systematisierung. SteinerGoogle Scholar
  33. Jaafari A, Manivong K (1998) Towards a smart project management information system. Int J Project Manage 16:249–265Google Scholar
  34. Jaeger M (2008) Wie wirksam sind leistungsorientierte Budgetierungsverfahren an deutschen Hochschulen? Zeitschrift für HochschulentwicklungGoogle Scholar
  35. Jahn T (2008) Transdisziplinarität in der Forschungspraxis. In: Bergmann M, Schramm E (eds) Transdisziplinäre Forschung: Integrative Forschungsprozesse verstehen und bewerten. Campus Verlag, Frankfurt, New York, pp 21–37Google Scholar
  36. Jahn T, Bergmann M, Keil F (2012) Transdisciplinarity: between mainstreaming and marginalization. Ecol Econ 79:1–10. doi: 10.1016/j.ecolecon.2012.04.017 CrossRefGoogle Scholar
  37. Jansen U, Schulz W (2015) An interactive approach for fast and frugal decision making in innovative research cooperation. In: ICERI2015 proceedings. IATED, pp 7957–7963Google Scholar
  38. Jeners NU (2015) Unterstützung von Wissensarbeit durch Integration heterogener Kooperationswerkzeuge. Accessed 13 Nov 2015
  39. Jooß C (2014) Gestaltung von Kooperationsprozessen interdisziplinärer Forschungsnetzwerke, Zugl.: Aachen, Techn. HochschGoogle Scholar
  40. Jooß C, Welter F, Leisten I, Richert A, Schaar A-K, Calero Valdez A, Nick E-M, Prahl U, Jansen U, Schulz W, Ziefle M, Jeschke S (2012) Scientific Cooperation Engineering in the cluster of excellence integrative production technology for high-wage countries at RWTH Aachen University. In: Gómez Chova L, López Martínez A, Candel Torres I (eds) ICERI 2012: conference proceedings. International Association of Technology, Education and Development (IATED), Madrid, pp 3842–3846Google Scholar
  41. Jungert M, Romfeld E, Sukopp T, Voigt U (2013) Interdisziplinarität: Theorie. Praxis, ProblemeGoogle Scholar
  42. Kaplan RS, Norton DP (1992) The balanced scorecard–measures that drive performance. Harv Bus Rev 70(1):71–79Google Scholar
  43. Kaufmann A, Tödtling F (2001) Science–industry interaction in the process of innovation: The importance of boundary-crossing between systems. Res Policy 30(5):791–804. doi: 10.1016/S0048-7333(00)00118-9 CrossRefGoogle Scholar
  44. Kumar S (2015) Co-authorship networks: a review of the literature. Aslib J Inf Manage 67(1):55–73CrossRefGoogle Scholar
  45. Landauer TK (2014) LSA as a Theory of Meaning. In: Landauer TK, McNamara DS, Dennis S, Kintsch W (eds) Handbook of latent semantic analysis. Psychology Pr, pp 3–34Google Scholar
  46. Lattuca LR (2002) Learning interdisciplinarity: sociocultural perspectives on academic work. J High Educ 73(6):711–739CrossRefGoogle Scholar
  47. Leonardi PM (2014) Social Media, knowledge sharing, and innovation: toward a theory of communication visibility. Inf Syst Res 25(4):796–816CrossRefGoogle Scholar
  48. Leupold M (2010) Technologietransfer im Web 2.0: Wie das Wissen heute in die Welt kommen kann. Wissenschaftsmanagement 2010(1):20–25Google Scholar
  49. Lukosch H, Overschie M, de Vries P (2009) Microtraining as an effective way towards sustainability. In: Candel Torres I, Gómez Chova L, Martí Belenguer D (eds) EDULEARN09: Abstracts cd: International conference on education and new learning technologies, Barcelona (Spain), 6–8 July, 2009. International Association of Technology, Education and Development (IATED), Valencia, pp 31–38Google Scholar
  50. Lyall C, Bruce A, Tait J, Meagher L (2011) Interdisciplinary research journeys: practical strategies for capturing creativity. Bloomsbury Publishing, LondonGoogle Scholar
  51. Lyall C, Meagher LR (2012) A Masterclass in interdisciplinarity: research into practice in training the next generation of interdisciplinary researchers. Futures 44(6):608–617. doi: 10.1016/j.futures.2012.03.011 CrossRefGoogle Scholar
  52. Manning CD, Schütze H (2003) Foundations of statistical natural language processing. MIT Press, CambridgezbMATHGoogle Scholar
  53. Matthews T, Whittaker S, Badenes H, Smith BA, Muller M, Ehrlich K, Zhou MX, Lau T (2013) Community insights: helping community leaders enhance the value of enterprise online communities.In: Proceedings of the SIGCHI conference on human factors in computing systems, pp 513–522Google Scholar
  54. Mayring P (2013) Qualitative content analysis: theoretical foundation, basic procedures and software solution, KlagenfurtGoogle Scholar
  55. Melin G (2000) Pragmatism and self-organization. Res Policy 29(1):31–40. doi: 10.1016/S0048-7333(99)00031-1 CrossRefGoogle Scholar
  56. Millar MM (2013) Interdisciplinary research and the early career: the effect of interdisciplinary dissertation research on career placement and publication productivity of doctoral graduates in the sciences. Res Policy 42(5):1152–1164. doi: 10.1016/j.respol.2013.02.004 CrossRefGoogle Scholar
  57. Müller SL, Thiele T, Jooß C, Richert A, Isenhardt I, Jeschke S (2015) Managing interdisciplinary research clusters. In: Proceedings of the IEEE international conference on industrial engineering and engineering management (IEEM 2015) (in Press)Google Scholar
  58. National Academies U.S. (2005) Facilitating interdisciplinary research. National Academies, Washington D.CGoogle Scholar
  59. Nickerson J, Sakamoto Y (2010) Crowdsourcing creativity: Combining ideas in networks. In: Workshop on information in networksGoogle Scholar
  60. Nissani M (1997) Ten cheers for interdisciplinarity: the case for interdisciplinary knowledge and research. Social Sci J 34(2):201–216CrossRefGoogle Scholar
  61. Oskam IF (2009) T-shaped engineers for interdisciplinary innovation: an attractive perspective for young people as well as a must for innovative organisations. In: 37th Annual conference—attracting students in engineering, vol 14, Rotterdam, The NetherlandsGoogle Scholar
  62. Perianes-Rodriguez A, Olmeda-Gómez C, Moya-Anegón F (2010) Detecting, identifying and visualizing research groups in co-authorship networks. Scientometrics 82(2):307–319CrossRefGoogle Scholar
  63. Pu P, Chen L, Hu R (2011) A user-centric evaluation framework for recommender systems. In: Proceedings of the fifth ACM conference on recommender systems, pp 157–164Google Scholar
  64. Raasch C, Lee V, Spaeth S, Herstatt C (2013) The rise and fall of interdisciplinary research: the case of open source innovation. Res Policy 42(5):1138–1151. doi: 10.1016/j.respol.2013.01.010 CrossRefGoogle Scholar
  65. Raymond L, Bergeron F (2008a) Project management information systems: an empirical study of their impact on project managers and project success. Int J Project Manage 26:213–220Google Scholar
  66. Raymond L, Bergeron F (2008b) Project management information systems: an empirical study of their impact on project managers and project success. Int J Project Manage 26:213–220Google Scholar
  67. Reichheld FF (2003) The one number you need to grow. Harv Bus Rev 81(12):46–55Google Scholar
  68. Repko AF (2008) Interdisciplinary research: process and theory. Sage, LondonGoogle Scholar
  69. Repko AF, Szostak R, Buchberger MP (2013) Introduction to interdisciplinary studies. SAGE PublicationsGoogle Scholar
  70. Ruby S, Thomas D, Hansson DH (2013) Agile web development with rails 4. Pragmatic BookshelfGoogle Scholar
  71. Schuh G, Aghassi S (2013) Supporting technology transfer with communities and social software solutions. Int J Mech Aerospace Ind Mechatron Eng 7(11):1119–1127Google Scholar
  72. Schuh G, Aghassi S, Schneider B, Bartels P (2014) Influencing factors and requirements for designing customized technology transfer portals. IEEE international conference on management of innovation and technology (ICMIT), pp 105–110Google Scholar
  73. Schuh G, Bräkling A, Calero Valdez A, Schaar AK, Ziefle M (2016) Using liferay as an interdisciplinary scientific collaboration portal. A comparative usability study of version 6.1 and 6.2. In: 18th international conference on human-computer interaction (in press)Google Scholar
  74. Schuh G, Bräkling A, Drescher T (2015) Configuration Model for Focused Crawlers in Technology Intelligence. Proceedings of 24th International Association for Management of Technology (IAMOT):832–839Google Scholar
  75. Sundstrom E, de Meuse KP, Futrell D (1990) Work teams: applications and effectiveness. Am Psychol 45(2):120CrossRefGoogle Scholar
  76. Sydow J, Duschek S (2011) Management interorganisationaler Beziehungen: Netzwerke, Cluster, Allianzen edn. Management, Kohlhammer, StuttgartGoogle Scholar
  77. Sydow J, Zeichhardt R (2009) Bedeutung von Netzwerkservices für den Erfolg von Netzwerken. In: Bundesministerium für Wirtschaft und Technologie (ed) Innovative Netzwerkservices: Netzwerk- und Clusterentwicklung durch maßgeschneiderte Dienstleistungen, Berlin, pp 21–29Google Scholar
  78. Thiele T, Jooß C, Richert A, Jeschke S (2015) Terminology based visualization of interfaces in interdisciplinary research networks. In: Lindgaard G, Moore D (eds) The proceedings of the 19th Triennial Congress of the International Ergonomics Association, MelbourneGoogle Scholar
  79. Triandis HC, Hall ER, Ewen RB (1965) Member heterogeneity and dyadic creativity. Hum RelGoogle Scholar
  80. Triandis HC, Kurowski LL, Gelfand MJ (1994) Workplace diversityGoogle Scholar
  81. Tromp JW, Homan T (2015) How unplanned changes emerge while implementing a Project Management Information System (PMIS) in a complex multi project R&D environment. Proc Soc Behav Sci 194:211–220Google Scholar
  82. Vaegs T, Calero Valdez A, Schaar A-K, Bräkling A, Aghassi S, Jansen U, Thiele T, Welter F, Jooß C, Richert A, Schulz W, Schuh G, Ziefle M, Jeschke S (2014) Enhancing scientific cooperation of an interdisciplinary cluster of excellence via a scientific cooperation portal. In: Guralnick D (ed) Proceedings of the seventh international conference on e-learning in the workplace, New York, NY, USAGoogle Scholar
  83. Vaegs T, Zimmer I, Schröder S, Leisten I, Vossen R, Jeschke S (2013) Fostering interdisciplinary integration in engineering management. In: Proceedings of the IEEE international conference on industrial engineering and engineering management (IEEM 2013)Google Scholar
  84. Vossen R (2012) Ein Verfahren zur Ermittlung und Bewertung des intellektuellen Kapitals von wissenschaftlichen Exzellenzclustern, Zugl.: Aachen, Techn. HochschGoogle Scholar
  85. Welter F (2013) Regelung wissenschaftlicher Exzellenzcluster mittels scorecardbasierter Performancemessung, Zugl.: Aachen, Techn. HochschGoogle Scholar
  86. Welter F, Jooß C, Richert A, Jeschke S, Brecher C (2012) Organisation and management of integrative research. In: Brecher C (ed) Integrative production technology for high-wage countries. Springer, Berlin, pp 64–76Google Scholar
  87. Welter F, Thiele T, Pfeiffer O, Richert A, Jeschke S (2010) Knowledge management in vocational training: a case study of the EU project reload. Int J Adv Corp Learn (iJAC) 3(4):45–51Google Scholar
  88. Welter F, Vossen R, Richert A, Isenhardt I (2011) Network management for clusters of excellence—A balanced-scorecard approach as a performance measurement tool. In: Jeschke S, Isenhardt I, Henning K (eds) Automation, communication and cybernetics in science and engineering 2009/2010. Springer, Berlin, pp 195–207CrossRefGoogle Scholar
  89. White HD, Mccain KW (1998) Visualizing a discipline: an author co-citation analysis of information science. J Am Soc Inf SciGoogle Scholar
  90. Wiemer-Hastings P, Wiemer-Hastings K, Graesser A (2004) Latent semantic analysis. In: Proceedings of the 16th international joint conference on artificial intelligence, pp 1–14Google Scholar
  91. Wulf WA (2002) The importance of diversity in engineering. Divers Eng Manag Workforce Future 8–15Google Scholar
  92. Yao Y, Zeng Y, Zhong N, Huang X (2007) Knowledge retrieval (kr). In: IEEE/WIC/ACM international conference on web intelligence, pp 729–735Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Sabina Jeschke
    • 1
    Email author
  • Wolfgang Bleck
    • 2
  • Anja Richert
    • 1
  • Günther Schuh
    • 3
  • Wolfgang Schulz
    • 4
  • Martina Ziefle
    • 5
  • André Bräkling
    • 6
  • André Calero Valdez
    • 5
  • Kirsten Dahmen
    • 2
  • Ulrich Jansen
    • 4
  • Claudia Jooß
    • 1
  • Sarah L. Müller
    • 1
  • Ulrich Prahl
    • 2
  • Anne Kathrin Schaar
    • 5
  • Mamta Sharma
    • 2
  • Thomas Thiele
    • 1
  1. 1.Cybernetics Lab IMA/ZLW & IfURWTH Aachen UniversityAachenGermany
  2. 2.Department of Ferrous Metallurgy (IEHK), RWTH Aachen UniversityAachenGermany
  3. 3.Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen UniversityAachenGermany
  4. 4.Fraunhofer Institute for Laser Technology (ILT)AachenGermany
  5. 5.Human-Computer Interaction Center (HCIC), RWTH Aachen UniversityAachenGermany
  6. 6.Fraunhofer Institute for Production Technology (IPT)AachenGermany

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