Futures Research as an Opportunity for Innovation in Verification Technologies

  • Joachim SchulzeEmail author
  • Matthias Grüne
  • Marcus John
  • Ulrik Neupert
  • Dirk Thorleuchter


Over the last 40 years, the verification of compliance with disarmament treaties for Weapons of Mass Destruction has steadily evolved using several technological solutions. Today’s technological progress promises a variety of possible future and emerging technologies that may contribute to even better verification techniques. However, the latter might originate from technology areas far away from those usually monitored by the verification community. Scientifically-based futures research offers several validated approaches and methodologies that can provide orientation in this complex technology landscape and help to carve out the most probable technological future developments. We suggest to include a futures-research approach in the verification debate, complementing the expert community’s findings and improving the awareness of technology-based opportunities and threats. Four different methodological approaches are described, which require specialized futurists to be exercised. The classical approach to technology foresight systematically studies appropriate scientific literature, looking for “known” and “unknown unknowns” and considering the interdependencies of the “technology complex”. Bibliometrics can, although inherently retrospective, be used to characterise and forecast research topics and scientific networks. Modern text-mining tools can be used to extract unexpected information from the internet (“web mining”), potentially uncovering “unknown unknowns”. Solution assessment by serious gaming can help to structure multi-perspective discussions.


  1. 1.
    Conference on Disarmament, Geneva. Accessed 28 Feb 2019
  2. 2.
    Avenhaus R, Kyriakopoulos N, Richard M, Stein G (eds.) (2006) Verifying Treaty Compliance. Limiting Weapons of Mass Destruction and Monitoring Kyoto Protocol Provisions. Springer, BerlinGoogle Scholar
  3. 3.
    Agar J (2009) On the origin of technology. Nature 461(7262):349. CrossRefGoogle Scholar
  4. 4.
    Bower J L, Christensen C M (1995) Disruptive Technologies: Catching the Wave. Harvard Business Review 73(1):43–53. Accessed 28 Feb 2019Google Scholar
  5. 5.
    Campbell V (2004) How RAND Invented the Postwar World. Satellites, Systems Analysis, Computing, the Internet – Almost All the Defining Features of the Information Age Were Shaped in Part at the RAND Corporation. Invention and Technology, Summer:50–59.Google Scholar
  6. 6.
    Zweck A, Holtmannspötter D (2002) Monitoring of technology forecasting activities in Europe. ESTO project report; working document. Dusseldorf (Zukünftige Technologien / Future Technologies, 37).Google Scholar
  7. 7.
    Martin B R (2010) The origins of the concept of ‘foresight’ in science and technology: An insider’s perspective. Technol. Forecast. Soc. Change 77(9):1438–1447. CrossRefGoogle Scholar
  8. 8.
    Miles I (2010) The development of technology foresight: A review. Technol. Forecast. Soc. Change 77(9):1448–1456. CrossRefGoogle Scholar
  9. 9.
    Masini E (2006) Rethinking futures studies. Futures 38(10):1158–1168. CrossRefGoogle Scholar
  10. 10.
    Jouvenel B (1965) Futuribles. RAND Corp., RAND Paper P-3045. Accessed 28 Feb 2019
  11. 11.
    Steinmüller K (2012) Zukunftsforschung in Deutschland. Versuch eines historischen Abrisses (Teil 1). Zeitschrift für Zukunftsforschung 1(1):6–19. urn:nbn:de:0009-32-34116 Google Scholar
  12. 12.
    Technology Futures Analysis Methods Working Group (2004): Technology futures analysis: Toward integration of the field and new methods. Technol. Forecast. Soc. Change 71(3):287–303. CrossRefGoogle Scholar
  13. 13.
    Grunwald A (2013) Wissenschaftliche Validität als Qualitätsmerkmal der Zukunftsforschung. Zeitschrift für Zukunftsforschung 2(1):22–33. urn.nbn:de:0009-32-36941 Google Scholar
  14. 14.
    Kerwin A (1993) None Too Solid: Medical Ignorance. Knowledge: Creation, Diffusion. Utilization 15(2):166–185. Google Scholar
  15. 15.
    Grüne M (2013) Technologiefrühaufklärung im Verteidigungsbereich. in: Popp R, Zweck A (eds): Zukunftsforschung im Praxistest. Springer Fachmedien Wiesbaden (Zukunft und Forschung 3):195–230.
  16. 16.
    Burbiel J, Schietke R (2014) ETCETERA - Evaluation of Critical and Emerging Security Technologies for the Elaboration of a Strategic Research Agenda. Final Report. Fraunhofer INT, Euskirchen. Accessed 13 Apr 2016 and Accessed 12 Nov 2019
  17. 17.
    Geschka H, Hahnenwald H (2013) Scenario-Based Exploratory Technology Roadmaps - A Method for the Exploration of Technical Trends. In: Moehrle MG., Isenmann R, Phaal R (eds): Technology Roadmapping for Strategy and Innovation. Springer Berlin Heidelberg, pp 123–136. CrossRefGoogle Scholar
  18. 18.
    Von der Gracht H, Bañuls VA, Turoff M, Skulimowski AMJ, Gordon TJ (2015) Foresight support systems: The future role of ICT for foresight. Technological Forecasting and Social Change 97:1–6. CrossRefGoogle Scholar
  19. 19.
    Keller J, Von der Gracht H (2014) The influence of information and communication technology (ICT) on future foresight processes – Results from a Delphi survey. Technol. Forecast. Soc. Change 85:81–92. CrossRefGoogle Scholar
  20. 20.
    Zhang Y, Porter AL, Hu Z, Guo Y, Newman NC (2014) Term clumping for technical intelligence: A case study on dye-sensitized solar cells. Technol. Forecast. Soc. Change 85:26–39. CrossRefGoogle Scholar
  21. 21.
    Schiebel E, Hoerlesberger M, Roche I, François C, Besagni D (2010) An advanced diffusion model to identify emergent research issues: the case of optoelectronic devices. Scientometrics 83(3):765–781. CrossRefGoogle Scholar
  22. 22.
    Chen C (2006) CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology 57(3): 359–377. CrossRefGoogle Scholar
  23. 23.
    Wepner B, Huppertz G (2014) Report on the Comparative Analysis of Three Methods to Assess Emerging Technologies. EU FP7 SEC project ETCETERA, deliverable 4.2. Accessed 13 Apr 2016
  24. 24.
    John M, Fritsche F (2013) Bibliometric classification of emerging topics. in: Hinze S, Lottmann A (eds.) Translational twists and turns: Science as a socio-economic endeavor, iFQ-Working Paper, iFQ, Berlin, pp 181–184. Accessed 12 Nov 2019
  25. 25.
    John M, Fritsche F (2013) Fullerene and cold fusion: Bibliometric discrimination between normal and pathological science. In: Gorraiz J, Schiebel E, Gumpenberger C, Hörlesberger M, Moed HF(eds.) Proceedings of ISSI 2013 Vienna, AIT - Austrian Inst. of Technology, Vienna, pp 1989–1991. Accessed 12 Nov 2019
  26. 26.
    Bettencourt LMA, Kaiser DI, Kaur J (2009) Scientific discovery and topological transitions in collaboration networks. Journal of Informetrics 3(3):210–221. CrossRefGoogle Scholar
  27. 27.
    Kostoff RN, Shlesinger MF (2005) Cab: Citation-assisted background. Scientometrics 62(2):199–212. CrossRefGoogle Scholar
  28. 28.
    Mayr P, Schaer P, Scharnhorst A, Larsen B, Mutschke P (eds.) (2014) Proceedings of the First Workshop on Bibliometric-enhanced Information Retrieval, CEURWorkshop Proceedings, vol. 1143. urn:nbn:de:0074-1143-7 Google Scholar
  29. 29.
    Abebe M, Angriawan A, Tran H (2010). Chief executive external network ties and environmental scanning activities: An empirical examination. Strategic Management Review 4(1):30–43Google Scholar
  30. 30.
    Ansoff IH (1975) Managing strategic surprise by response to weak signals. California Management Review 18(2):21–33CrossRefGoogle Scholar
  31. 31.
    Kosala R, Blockeel H (2000) Web research: A survey. ACM SIGKDD Explorations Newsletter 2(1)Google Scholar
  32. 32.
    Jiang J, Berry MW, Donato JM, Ostrouchov G, Grady NW (1999) Mining consumer product data via latent semantic indexing. Intelligent Data Analysis 3(5):377–398Google Scholar
  33. 33.
    Thorleuchter D, Van den Poel D (2013) Weak signal identification with semantic web mining. Expert Systems with Applications, 40(12):4978–4985CrossRefGoogle Scholar
  34. 34.
    NATO (2010) Assessment of Possible Disruptive Technologies for Defence and Security. Report RTO-TR-SAS-062 (NATO unclassified)Google Scholar
  35. 35.
    NATO (2012) Disruptive Technology Assessment Game - Evolution and Validation. Report RTO-TR-SAS-082 (NATO unclassified)Google Scholar
  36. 36.
    Neupert U, Römer S, Wiemken U, Rademaker JGM (2009) Assessment of potentially disruptive technologies for defence and security, Fraunhofer Symposium Future Security, 4th Security Research Conference, Karlsruhe, GermanyGoogle Scholar
  37. 37.
    EU FP7 SEC ETCETERA project homepage. Accessed 13 Apr 2016
  38. 38.
    Tucker JB (1996) Monitoring and verification in a noncooperative environment: Lessons from the U.N. experience in Iraq, The Nonproliferation Review 3(3).

Copyright information

© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020

Authors and Affiliations

  • Joachim Schulze
    • 1
    Email author
  • Matthias Grüne
    • 2
  • Marcus John
    • 2
  • Ulrik Neupert
    • 2
  • Dirk Thorleuchter
    • 2
  1. 1.ConsultantBad Neuenahr-AhrweilerGermany
  2. 2.Fraunhofer Institute for Technological Trend Analysis INTEuskirchenGermany

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