# ROC: An Ontology for Country Responses towards COVID-19

arXiv: https://arxiv.org/abs/2104.07345 · HTML: https://mlsanity.com/paper/2104.07345/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 18 references that are in the map.
- First posted on arXiv 15 Apr 2021.

## Builds on (most cited first, 2 of 2)

- [CODO: An Ontology for Collection and Analysis of Covid-19 Data](https://mlsanity.com/paper/2009.01210/) (2020)
- [Learning the Semantics of Structured Data Sources](https://mlsanity.com/paper/1601.04105/) (2016)

## Abstract (arXiv)

The ROC ontology for country responses to COVID-19 provides a model for collecting, linking and sharing data on the COVID-19 pandemic. It follows semantic standardization (W3C standards RDF, OWL, SPARQL) for the representation of concepts and creation of vocabularies. ROC focuses on country measures and enables the integration of data from heterogeneous data sources. The proposed ontology is intended to facilitate statistical analysis to study and evaluate the effectiveness and side effects of government responses to COVID-19 in different countries. The ontology contains data collected by OxCGRT from publicly available information. This data has been compiled from information provided by ECDC for most countries, as well as from various repositories used to collect data on COVID-19.