A Parallel World Framework for scenario analysis in knowledge graphs
- Submitting institution
-
University of Cambridge
- Unit of assessment
- 12 - Engineering
- Output identifier
- 10065
- Type
- D - Journal article
- DOI
-
10.1017/dce.2020.6
- Title of journal
- Data-Centric Engineering
- Article number
- e6
- First page
- -
- Volume
- 1
- Issue
- -
- ISSN
- 2632-6736
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
11
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a framework enabling scenario analysis of design options for complex multi-domain interacting systems, and led to invitations for MK to give invited talks (Plenary Talk: bit.ly/35Iq22D, Keynote Speaker: bit.ly/3e6ZnAq), and to join the editorial board of Energy & AI (bit.ly/3jJ1E6c). The work led to further funding of S$5m in a joint project between the University of Cambridge and ETH Zurich (cares.cam.ac.uk/research/cities) and funding as part of the C4T (S$80m) project at Cambridge CARES (cares.cam.ac.uk). It has led to a number of industry-sponsored studentships (RG73411, RG96475 and G108050). Related papers have both won awards (bit.ly/3koQHI0, bit.ly/2HuhB2F).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
