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Predicting Seismic Damage and Loss for Residential Buildings using Data Science

2021 doctoral thesis by Samuel Roeslin at University of Auckland
CreativeWork doctoral_thesis Q112956561
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Summary

Predicting Seismic Damage and Loss for Residential Buildings using Data Science is a doctoral thesis[1].

Key Facts

  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science authored Samuel Roeslin[2].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's instance of is recorded as doctoral thesis[3].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science was published by ResearchSpace@Auckland[4].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's copyright license is recorded as Creative Commons Attribution-NonCommercial-ShareAlike 3.0 New Zealand[5].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's country of origin is recorded as New Zealand[6].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science was published on 2021[7].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's main subject is civil engineering studies[8].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's work available at URL is recorded as https://researchspace.auckland.ac.nz/handle/2292/57074[9].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's title is recorded as Predicting Seismic Damage and Loss for Residential Buildings using Data Science[10].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's copyright holder is recorded as Samuel Roeslin[11].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's thesis submitted to is recorded as University of Auckland[12].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's on focus list of Wikimedia project is recorded as NZThesisProject[13].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's copyright status is recorded as copyrighted[14].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's online access status is recorded as open access[15].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's thesis committee member is recorded as Quincy Ma[16].
  • Predicting Seismic Damage and Loss for Residential Buildings using Data Science's thesis submitted for degree is recorded as Doctor of Philosophy[17].

Body

Designation and Status

Predicting Seismic Damage and Loss for Residential Buildings using Data Science's instance of is recorded as doctoral thesis[3].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [3] ↑ . wikidata.org.
  2. [2] ↑ . wikidata.org.
  3. [4] ↑ . wikidata.org.
  4. [5] ↑ . wikidata.org.
  5. [6] ↑ . wikidata.org.
  6. [7] ↑ . wikidata.org.
  7. [8] ↑ . wikidata.org.
  8. [9] ↑ . wikidata.org.
  9. [10] ↑ . wikidata.org.
  10. [11] ↑ . wikidata.org.
  11. [12] ↑ . wikidata.org.
  12. [13] ↑ . wikidata.org.
  13. [14] ↑ . wikidata.org.
  14. [15] ↑ . wikidata.org.
  15. [16] ↑ . wikidata.org.
  16. [17] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Predicting Seismic Damage and Loss for Residential Buildings using Data Science. Retrieved May 3, 2026, from https://4ort.xyz/entity/predicting-seismic-damage-and-loss-for-residential-buildings-using-data-science
MLA “Predicting Seismic Damage and Loss for Residential Buildings using Data Science.” 4ort.xyz Knowledge Graph, 4ort.xyz, 3 May. 2026, https://4ort.xyz/entity/predicting-seismic-damage-and-loss-for-residential-buildings-using-data-science.
BibTeX @misc{4ortxyz_predicting-seismic-damage-and-loss-for-residential-buildings-using-data-science_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Predicting Seismic Damage and Loss for Residential Buildings using Data Science}}, year = {2026}, url = {https://4ort.xyz/entity/predicting-seismic-damage-and-loss-for-residential-buildings-using-data-science}, note = {Accessed: 2026-05-03}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Predicting Seismic Damage and Loss for Residential Buildings using Data Science — https://4ort.xyz/entity/predicting-seismic-damage-and-loss-for-residential-buildings-using-data-science (retrieved 2026-05-03)

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Edit History

Rolling log of changes to this entity's Wikidata record. Values shown reflect the current state of each edited property — follow the history link to see the precise diff for any edit.

  1. 6w ago · DrThneed · 2026-09-06 view diff on Wikidata ↗
    Thesis submitted for degree → Doctor of Philosophy
    Thesis submitted to → University of Auckland
    Handle id → 2292/57074
    Copyright status → copyrighted
    + 15 other properties edited (see Wikidata diff for full list)
    "/* wbeditentity-update:0| */ QuickStatements 3.0 [[:toollabs:qs-dev/batch/52366|batch #52366]]"
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