Data · dataset · 2020
NigeriaCOVID-19
Listed in Teesside University Research Data Repository
The Coronavirus disease COVID-19 at this point of writing is a pandemic that has rampaged planet earth.
Description
It is regarded as a global threat and in some quarters an existential threat. Every possible effort should be made in the application of mathematical models, artificial intelligence, big data, and other resources to stem the spread of this disease.
In this dataset, the daily total number of COVID-19 cases in Nigeria from February 27, 2020, to April 5, 2020, were automatically mined every 24 hours from the official websites of NCDC and Wikipedia. The initial data is in raw Excel file format nigeria_covid19.csv. Data with regularly updated case numbers and prediction results from an ensemble of forecasting algorithms can be found in nigeria_covid19_updated.csv.
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These data are useful as they present facts that drive analytics on COVID-19 cases in Nigeria. It also represents an early reference that can be used in the future. Academic institutions, public health agencies, scientific communities, researchers, students, and self-explorers can use this data to explore, analyze, and develop reliable insights on COVID-19 cases in Nigeria and beyond.
The data with regular updates presented can be applied to drive analytics, policy development, and decision making in other countries where data is scarce.
Links
Where it is published
- DOI doi.org/10.17632/3xsb9nyfhp.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 · Machine learning · Mathematics & Statistics · Medicine & Health
- Inferred from text
- Disease 75%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/3xsb9nyfhp.1 | 9 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| 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:mathematics-statistics | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| 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 |