Source: https://imerg.info By Dr Seuss (with obvious modifications by Ashley Barnett contextualization by Eva Méndez (@evamen)
This page has been developed by Eva Méndez, RDA EU Ambassador for Interdisciplinary Research
When it comes to solving global problems (COVID-19 crisis, SDG / Sustainable Development Goals) a single domain, a single discipline, is not enough… we need multidisciplinary, cross-disciplinary, interdisciplinary, transdisciplinary or even super-disciplinary research. All of these prefix (multi-, cross, inter-, trans-) imply the concurrence (at some point) of disciplines or different domains in a scientific process and research. Shared use of data goes beyond one discipline, expanding the scope of research and diversifying perspectives. It also allows for creation of new knowledge or meta-knowledge and the discovery by serendipity.
- Multidisciplinarity means people from different disciplines working together, each drawing on their disciplinary knowledge.
- Cross-disciplinarity is the view of one discipline from the perspective of another.
- Interdisciplinarity implies the integration of knowledge, methods and DATA from different disciplines, using a real synthesis of approaches.
- Transdisciplinarity means building a unity of intellectual frameworks beyond the disciplinary perspectives. Disciplines involved in transdisciplinary research transcend their own domains to create a new holistic approach.
The ex-ERC president coined the super-disciplinary research to define the evolution of scientific discovery and how new fields of knowledge come into existence.
The Research Data Alliance can contribute to all this labeled scientific research that spans more than one discipline. But particularly interdisciplinary research that might integrate different methods and data from different domains to address a complex problem. In interdisciplinary research we assume the combination of data from two or more disciplines to a new level of integration, based on the data re-use, in the assumption that each discipline (its methods and data) would affect the research outcomes of the other.
Speaking about interdisciplinary research in the context of research data means thinking on data as an output, but also as an input for research. But it especially means INTEROPERABILITY among data, metadata, vocabularies and best practices, so RDA can help a lot in this perspective. Interoperability but not only at technical or semantic level, but also at legal and even political level.
RDA Working Groups and Interest Groups
RDA supporting outputs and recommendations
We can find all this RDA Outputs and Recommendations for “domain-agnostic” research. But there are particularly interesting for INTERDISCIPLINARY RESEARCH these ones: