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On the use of computer‐assistance to facilitate systematic mapping

Author

Listed:
  • Neal R. Haddaway
  • Max W. Callaghan
  • Alexandra M. Collins
  • William F. Lamb
  • Jan C. Minx
  • James Thomas
  • Denny John

Abstract

The volume of published academic research is growing rapidly and this new era of “big literature” poses new challenges to evidence synthesis, pushing traditional, manual methods of evidence synthesis to their limits. New technology developments, including machine learning, are likely to provide solutions to the problem of information overload and allow scaling of systematic maps to large and even vast literatures. In this paper, we outline how systematic maps lend themselves well to automation and computer‐assistance. We believe that it is a major priority to consolidate efforts to develop and validate efficient, rigorous and robust applications of these novel technologies, ensuring the challenges of big literature do not prevent the future production of systematic maps.

Suggested Citation

  • Neal R. Haddaway & Max W. Callaghan & Alexandra M. Collins & William F. Lamb & Jan C. Minx & James Thomas & Denny John, 2020. "On the use of computer‐assistance to facilitate systematic mapping," Campbell Systematic Reviews, John Wiley & Sons, vol. 16(4), December.
    • Handle: RePEc:wly:camsys:v:16:y:2020:i:4:n:e1129
    DOI: 10.1002/cl2.1129
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    References listed on IDEAS

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    1. Madeleine C. McKinnon & Samantha H. Cheng & Ruth Garside & Yuta J. Masuda & Daniel C. Miller, 2015. "Sustainability: Map the evidence," Nature, Nature, vol. 528(7581), pages 185-187, December.
    2. Lutz Bornmann & Rüdiger Mutz, 2015. "Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2215-2222, November.
    3. Snilstveit, Birte & Vojtkova, Martina & Bhavsar, Ami & Gaarder, Marie, 2013. "Evidence gap maps -- a tool for promoting evidence-informed policy and prioritizing future research," Policy Research Working Paper Series 6725, The World Bank.
    4. William F. Lamb & Felix Creutzig & Max W. Callaghan & Jan C. Minx, 2019. "Learning about urban climate solutions from case studies," Nature Climate Change, Nature, vol. 9(4), pages 279-287, April.
    5. Max W. Callaghan & Jan C. Minx & Piers M. Forster, 2020. "A topography of climate change research," Nature Climate Change, Nature, vol. 10(2), pages 118-123, February.
    6. Minx, Jan C. & Callaghan, Max & Lamb, William F. & Garard, Jennifer & Edenhofer, Ottmar, 2017. "Learning about climate change solutions in the IPCC and beyond," Environmental Science & Policy, Elsevier, vol. 77(C), pages 252-259.
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    Cited by:

    1. Ariel M. Aloe & Ruth Garside, 2021. "Editorial: Types of methods research papers in the journal Campbell Systematic Reviews," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(2), June.
    2. Vivian A. Welch, 2021. "Campbell Collaboration: Reflection on growth and cultivation from 2017 to 2021," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(4), December.
    3. Zhang, Qian & Webster, Natasha A. & Han, Shengnan & Ayele, Workneh Yilma, 2023. "Contextualizing the rural in digital studies: A computational literature review of rural-digital relations," Technology in Society, Elsevier, vol. 75(C).

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