Data Curation: Improving Environmental Health Data Quality.
With the growing recognition of the influence of climate change on human health, scientists' attention to analyzing the relationship between meteorological factors and adverse health effects. However, the paucity of high quality integrated data is one of the great challenges, especially when scientific studies rely on data-intensive computing. This paper aims to design an appropriate curation process to address this problem. We present a data curation workflow that: (i) follows the guidance of DCC Curation Lifecycle Model; (ii) combines manual curation with automatic curation; (iii) and solves environmental health data curation problem. The workflow was applied to a medical knowledge service system and showed that it was capable of improving work efficiency and data quality.
Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Beijing, China.
Lin
L
Yang
Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Beijing, China.
Jiao
J
Li
Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Beijing, China.
Li
L
Hou
Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Beijing, China.
Qing
Q
Qian
D000068598:Data Accuracy; D066289:Data Curation / Q000379:methods*; D016208:Databases, Factual; D004782:Environmental Health / Q000706:statistics & numerical data*; D004784:Environmental Monitoring / Q000706:statistics & numerical data*; D016247:Information Storage and Retrieval / Q000379:methods*; D058996:Quality Improvement