Data · dataset · 2022
Extended MLIT dataset for the 2011 Great East Japan tsunami (Tōhoku region)
Listed in Teesside University Research Data Repository
Description
The dataset contains the additional explanatory variables used in the paper "Leveraging data driven approaches for enhanced tsunami damage modelling: insights from the 2011 Great East Japan event" (doi: 10.1016/j.envsoft.2022.105604) for developing an empirical, multi-variable tsunami damage model for buildings, based on machine-learning algorithms which leverage about 250.000 ex-post data surveyed by the Japanese Ministry of Land, Infrastructure and Transportation (MLIT) after the 2011 Great East Japan event in the Tōhoku region.
The present dataset includes only the new features computed in the mentioned study, while the original MLIT dataset is publicly available from the website of the Ministry of Land, Infrastructure, and Transportation of Japan mlit.go.jp/toshi/toshi-hukkou-arkaibu.html (and related webGIS (doi: 10.5638/thagis.21.87): fukkou.csis.u-tokyo.ac.jp/, for registered users). For the description of the explanatory variables contained in the present csv file, please refer to Table 1 of the main paper (doi: 10.1016/j.envsoft.2022.105604).
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[Coordinate reference system EPSG 2452 "JGD2000 / Japan Plane Rectangular CS X"]
Links
Where it is published
- DOI doi.org/10.17632/8mf9rtvkhk.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Machine learning · Social Science
- Inferred from text
- Tabular 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/8mf9rtvkhk.1 | 7 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:tabular | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |