Abstract
Collaborative eScience research teams are impeded by difficulties defining problems that provide research opportunities for all participants. Problem formulation occurs early in the collaboration process when the demand for ideas is high. However, cross-disciplinary linkages and integrated conceptual frameworks from which strong interdisciplinary ideas emerge do not evolve until later. The process of co-creating interdisciplinary research ideas is fundamentally a learning problem; participants from different disciplines must learn enough about each other’s research interests to construct an integrated conceptual framework from which joint problems of interest can be created. However, participants rarely have the conceptual background needed to easily understand research topics in other disciplines; hence methods for enabling rapid learning in these situations are needed. Team interactions that more effectively generate interdisciplinary ideas can be enabled based on a better understanding the process of cross-disciplinary, collaborative learning. This article postulates several models of collaborative learning in these settings and discusses the implications for orchestrating team activities to achieve better outcomes.
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References
Abrahamsson P, Salo O, Ronkainen J, Warsta J (2002) Agile Software Development Methods: Review and Analysis. VTT Publications, Finland. Available online at: http://www.pss-europe.com/P478.pdf
Argyris C, Schon DA (1996) Organizational learning II: theory, method, and practice. Addison Wesley, Reading
Barnett, B (1989) Reflection: The cornerstone of learning from experience. Presentation at the Annual Convention University Council for Educational Adminstrators, Scottsdale, AZ, October 1989
Beaulieu A, Wouters P (2009) E-research as intervention. In: Jankowski N (ed) e-Research: transformations in scholarly practice. Routledge, New York, pp 54–69
Bos N, Zimmerman A et al (2007) From shared databases to communities of practice: a taxonomy of collaboratories. J Comput Mediat Commun 12:652–672
Cash DW, Clark WC, Alcock F, Disckson NM, Eckley N, Guston DH, Jager J, Mitchell RB (2003) Knowledge systems for sustainable development. PNAS 100(14):8086–8091
Cook SDN, Brown JS (1999) Bridging epistemologies: the generative dance between organizational knowledge and organizational knowing. Organ Sci 10(4):381–400
Cottingham K (2002) Tackling biocomplexity: the role of people, tools, and scale. Bioscience 52(9):793–799
Cummings JN, Kiesler S (2005) Collaborative research across disciplinary and organizational boundaries. Soc Stud Sci 35(5):703–722
Darch P, Turilli M, Lloyd S, Jirotka M, de la Flor G (2010) Communication and Collaboration in e-Science Projects. Technical Report, Oxford e-Research Centre, Oxford University
De Roure D, Goble C (2009) Software design for empowering scientists. IEEE Softw 26(1):88–95, ISSN 0740-7459
Drach-Zahavy A, Somech A (2001) Understanding team innovation: the role of team processes and structures. Group Dynam: Theory, Res Practice 5(20):111–123
Finholt TA, Olson GM (1997) From laboratories to collaboratories: a new organizational form for scientific collaboration. Psychol Sci 8(1):28–36
Fischer G, Guaccardi E, Eden H, Sugimoto M, Ye YW (2005) Beyond binary choices: integrating individual and social creativity. Int J Hum Comput Stud 63:482–512
Giere RN (2002) Models as parts of distributed cognitive systems. In: Magnani L, Nersessian N (eds) Model based reasoning: science, technology, values. Kluwer, Dordrecht
Goel V (1992) Ill-structured representations for ill-structured problems. Proceedings of the 14th Annual Conference of the Cognitive Science Society. Hillsdale: Erlbaum
Golde C, Gallagher H (1999) The challenges of conducting interdisciplinary research in traditional doctoral programs. Ecosystems 2:281–285
Guimera R, Uzzi B, Spiro J, Amaral LAN (2005) Team assembly mechanisms determine collaboration network structure and team performance. Science 308:697–702
Hall KL, Stokols D, Moser RP, Taylor BK, Thornquist MD, Nebeling LC, Ehret CC et al. (2008) The collaboration readiness of transdiciplinary research teams and centers: Findings from the National Cancer Institute's TREC Year-One Evaluation Study. American Journal Of Preventive Medicine, 35(2S):S161–S172
Hartswood M, Jirotka M, Procter R, Slack R, Voss A, Lloyd S (2005) Working IT out in e-Science: experiences of requirements capture in a HealthGrid project. Stud Health Technol Inform 112:198–209
Horridge H, Knublauch H, Rector A, Stevens R, Wroe C (2004) A practical guide to building OWL Ontologies Using the Protégé-OWL Plugin and CO-ODE tools, Edition 1.0. Cooperative Ontologies Program tutorial, pp. 118, Available at http://www.coode.org/resources/tutorials/ProtegeOWLTutorial.pdf
Hutchins E (1995) Cognition in the wild. MIT Press
Jeffrey P (2003) Smoothing the waters: observations on the process of cross-disciplinary research collaboration. Soc Stud Sci 33(4):539–562
Jonassen DH (1997) Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educ Technol R&D 45(1):65–94
Kirschner PA (2002) Cognitive load theory: implications of cognitive load theory on the design of learning. Learn Instr 12:1–10
Kolb DA (1984) Experiential learning: experience as the source of learning and development. Prentice-Hall, Englewood Cliffs
Lawrence KA (2006) Walking the tightrope: the balancing acts of a large e-research project. Comput Supported Coop Work 15:385–411
Lele S, Norgaard RB (2005) Practicing interdisciplinarity. Bioscience 55(11):967–975
Levin SA (1998) Ecosystems and the biosphere as complex adaptive systems. Ecosystems 1:431–436
Levina N, Vaast E (2005) The emergence of boundary spanning competence in practice: implications for implementation and use of information systems. MIS Quarterly 29(2):335–363
Levine JM, Moreland RL (2004) Collaboration: the social context of theory development. Pers Soc Psychol Rev 8(20):164–172
Likens G (1998) Limitations to intellectual progress in ecosystem science. In: Pace M, Groffman P (eds) Successes, limitations and frontiers in ecosystem science. Springer, New York, pp 247–271
Magnus PD (2007) Distributed cognition and the task of science. Soc Stud Sci 37(2):297–310
Marr D (1982) Vision: a computational investigation into the human representation and processing of visual information. Freeman
Martin RC (2003) Agile software development: principles, patterns, and practices. Prentice Hall PTR, Upper Saddle River
Muller MJ, Kuhn S (1993) Participatory design. Commun. ACM 36, 6 (June 1993), 24-28. doi:10.1145/153571.255960 http://doi.acm.org/10.1145/153571.255960
Newell B, Crumley CL, Hassan N, Lambin EF, Pahl-Wostl C, Underdal A (2005) A conceptual template for integrative human-environment research. Glob Environ Change 15:299–307
Olson JS, Hofer EC, Bos N, Zimmerman A, Olson GM, Cooney D, Faniel I (2008) A theory of remote scientific collaboration. In: Olson GM, Zimmerman A, Bos N (eds) Scientific collaboration on the internet, pp 73-99
Olson GM, Olson JS (2000) Distance matters. Hum-Comput Interact 15(2–3):139–178
Paas F, Renkl A, Sweller J (2003) Cognitive load theory and instructional design: recent developments. Educ Psychol 38(1):1–4
Pennington D (unpublished) Bridging the Cross-Disciplinary Divide: Co-Creating Research Ideas. Unpublished manuscript in review
Pennington D (2008) Cross-disciplinary collaboration and learning. Ecol Soc 13(2):8 [online] URL: http://www.ecologyandsociety.org/vol13/iss2/art8/
Pennington D (2010) The dynamics of material artifacts in collaborative research teams. Comput Support Coop Work 19(2):175-199. doi:10.1007/s10606-010-9108-9. Available online at url: http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s10606-010-9108-9
Pennington D, Athanasiadis IN, Bowers S, Krivov S, Madin J, Schildhauer M, Villa F (2008a) Indirectly-driven knowledge modeling in ecology. Int J Metadata Semant Ontol 3(3):210–225
Pennington DD, Michener WK, Katz S, Downey L, Schildhauer M (2008b) Transforming scientists through technical education: a view from the trenches. Comput Sci Eng 10(5):28–33, Special Issue on High Performance Computing Education
Pickett STA, Burch WR Jr, Grove JM (1999) Interdisciplinary research: maintaining the constructive impulse in a culture of criticism. Ecosystems 2:302–307
Pinheiro da Silva P, Velasco A, Kosheleva O, Kreinovich V (2010) How AI-type uncertainty ideas can improve inter-disciplinary collaboration and education: lessons from a case study. J Adv Comput Intell Intell Informat 14(6):700–707
Porac JF, Wade JB et al (2004) Human capital heterogeneity, collaborative relationships, and publication patterns in a multidisciplinary scientific alliance: a comparative case study of two scientific teams. Res Policy 33:661–678
Redman CL (1999) Human dimensions of ecosystem studies. Ecosystems 2:296–298
Reid SE, de Brentani U (2004) The fuzzy front end of new product development for discontinuous innovations: a theoretical model. J Prod Innov Manage 21:170–184
Rhoten D (2003) Final report: a multi-method analysis of the social and technical conditions for interdisciplinary collaboration. San Francisco, CA, The Hybrid Vigor Institute, 82 pp
Ribes D, Bowker GC (2008) Organizing for multidisciplinary collaboration: the case of GEON. In: Olson GM, Olson JS, Zimmerman A (eds) Science on the Internet. MIT Press, Cambridge
Rogers EM (2003) Diffusion of innovations, 5th edn. Free Press, New York
Saab DJ (2009) A conceptual investigation of the ontological commensurability of spatial data infrastructures among different cultures. Earth Sci Inform 2:283–297
Schon DA (1990) The design process. In: Howard VA (ed) Varieties of thinking: essays from Harvard’s philosophy of education center. Routhledge, New York, pp 110–141
Sidlauskas B, Ganapathy G, Hazkani-Covo E, Jenkins KP, Lapp H, McCall LW, Price S, Scherle R, Spaeth PA, Kidd DM (2009) Linking big: the continuing promise of evolutionary synthesis. Evolution 64–4:871–880
Spencer B, Butler R, Ricker K, Marcusiu D, Finholt T, Foster I, Kesselman C, Birnholtz J (2008) NEESgrid: lessons learned for future cyberinfrastructure development. In: Olson G, Bos N, Zimmerman A (eds) Scientific collaboration on the internet. MIT Press, Boston, pp 331–348
Star SL, Griesemer JR (1989) Institutional ecology, 'translations' and boundary objects: amateurs and professionals in Berkeley's Museum of Vertebrate Zoology, 1907-39. Soc Stud Sci 19:387–420
Stokols D, Misra S, Moser RP, Hall KL, Taylor BK (2008) The ecology of team science: understanding contextual influences on transdisciplinary collaboration. Am J Prev Med 35(2S):S96–S115
Sun H, Zhang P (2006) The role of moderating factors in user technology acceptance. Int J Hum Comput Stud 64:53–78
Vera D, Crossan M (2005) Improvisation and innovative performance in teams. Organ Sci 16(3):203–224
Warr A, Lloyd S, Jirotka M, de la Flor G, Schroeder R, Rahman M (2007) Project management in e-Science, Technical Report. Oxford e-Research Centre, Oxford University
Wear DN (1999) Challenges to interdisciplinary discourse. Ecosystems 2:299–301
Wenger E (2000) Communities of practice and social learning systems. Organization 7(2):225–246
Wenger EC, Snyder WM (1994) Communities of practice: the organizational frontier. Harvard Business Review on Organizational Learning, pp 139-145
Williams P (2002) The competent boundary spanner. Public Adm 80(1):103–124
Zimmerman A, Finholt TA (2007) Growing an infrastructure: the role of gateway organizations in cultivating new communities of users. ACM Proceedings of Group’07, November 4-7, 2007, Sanibel Island, Florida
Acknowledgements
This work was supported by National Science Foundation grant numbers OCI-0636317 and OCI-0753336 for the CI-Team Demonstration and Implementation Projects: Advancing Cyber-infrastructure Based Science Through Education, Training, and Mentoring of Science Communities. The author gratefully acknowledges her many collaborators within and outside of these projects who stimulated and enabled development of these concepts.
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Communicated by H. A. Babaie
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Pennington, D.D. Collaborative, cross-disciplinary learning and co-emergent innovation in eScience teams. Earth Sci Inform 4, 55–68 (2011). https://doi.org/10.1007/s12145-011-0077-4
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DOI: https://doi.org/10.1007/s12145-011-0077-4