A study on the quality of novel coronavirus (COVID-19) official datasets-Reference-Cited by-同舟云学术

A study on the quality of novel coronavirus (COVID-19) official datasets

Published:2020-06-09 Issue:2 Volume:36 Page:291-301
ISSN:1874-7655
Container-title:Statistical Journal of the IAOS
language:
Short-container-title:SJI

Author:

Ashofteh Afshin¹,Bravo Jorge M.¹²³⁴

Affiliation:

1. NOVA Information Management School, Portugal

2. Université Paris-Dauphine PSL, Paris, France

3. MagIC

4. CEFAGE-UE

Publisher

IOS Press

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Management Information Systems

Reference5 articles.

1. The risk and consequences of clinical miscoding due to inadequate medical documentation: A case study of the impact on health services funding;Cheng;Health Inf Manag,2009

2. A Review of data quality assessment methods for public health information systems;Chen;Int J Environ Res Public Health,2014

3. Four key challenges in infectious disease modelling using data from multiple sources;De Angelis;Epidemics,2015

4. United Nations, Department of economic and social affairs, Population division. World population prospects 2019, Online edition. Rev. 1.

Cited by 31 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Review of Big Data and Machine Learning Operations in Official Statistics: MLOps and Feature Store Adoption;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

2. Data quality model for assessing public COVID-19 big datasets;The Journal of Supercomputing;2023-05-31

3. Characteristics and specifications of dashboards developed for the COVID-19 pandemic: a scoping review;Journal of Public Health;2023-02-02

4. A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment;Studies in Classification, Data Analysis, and Knowledge Organization;2023

5. Teaching Note—Data Science Training for Finance and Risk Analysis: A Pedagogical Approach with Integrating Online Platforms;Springer Proceedings in Mathematics & Statistics;2023