The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
Characteristics, potentials, and challenges of transdisciplinary research
Open accessAbstract
Resolving the grand challenges and wicked problems of the Anthropocene will require skillfully combining a broad range of knowledge and understandings-both scientific and non-scientific-of Earth systems and human societies. One approach to this is transdisciplinary research, which has gained considerable interest over the last few decades, resulting in an extensive body of literature about transdisciplinarity. However, this has in turn led to the challenge that developing a good understanding of transdisciplinary research can require extensive effort. Here we provide a focused overview and perspective for disciplinary and interdisciplinary researchers who are interested in efficiently obtaining a solid understanding of transdisciplinarity. We describe definitions, characteristics, schools of thought, and an exemplary three-phase model of transdisciplinary research. We also discuss three key challenges that transdisciplinary research faces in the context of addressing the broader challenges of the Anthropocene, and we consider approaches to dealing with these specific challenges, based especially on our experiences with building up transdisciplinary research projects at the Institute for Advanced Sustainability Studies.
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Cites
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Cited by
More sustainable artificial intelligence systems through stakeholder involvement?
Kunkel, S., Schmelzle, F., Niehoff, S., & Beier, G. (2023) · GAIA - Ecological Perspectives for Science and Society · doi:10.14512/gaia.32.s1.10 · Cited by 20
Metadata
- Authors
- Lawrence, M. G., Williams, S., Nanz, P., & Renn, O.
- Venue
- One Earth
- Publisher
- Elsevier BV
- Published
- 2022-01
- Volume
- 5
- Issue
- 1
- Pages
- 44-61
- ISSN
- 2590-3322 (ISSN-L)
- OpenAlex
- W4205673320
- Cited by
- 355
- References
- 79
- FWCI
- 58.95
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.