Objectives: To examine the current status and utilization of government health and welfare open data in Taiwan. Methods: Characteristic information from datasets released by the Ministry of Health and Welfare and related Institutions available at data.gov.tw were extracted for descriptive analyses. Results: On December 31 2015, 890 health and welfare datasets were available at data.gov.tw. The numbers of datasets released by the National Health Insurance Administration, Center for Disease Control, Health Promotion Administration, and Food and Drug Administration were 249, 193, 178, and 158, respectively. More than seventy percent of the datasets were ranked as third star or above (good quality) according to the W3C (World Wide Web Consortium) classification. The ten most frequently browsed datasets were cause of death statistics, hospital beds statistics, basic information about pharmacies, the daily number of confirmed dengue fever cases, the PIC/S GMP (Pharmaceutical Inspection Convention and Pharmaceutical Inspection Co-operation Scheme Guide to Good Manufacturing Practice for Medicinal Products) pharmaceutical manufactures, the list of shelters for disaster victims, the list of foods which did not meet government standards, the list of cancer treatment centers, the list of food materials for human use, and the list of drugs reimbursed by the National Health Insurance. Fifty-two applications were registered at data.gov.tw and 25 of these used government health and welfare open data. Conclusions: Although the number of datasets released by health institutions was lower than that of other sectors, the number of applications using government health and welfare open data was relatively high. Some of the datasets were divided into too many small datasets by some health institutions however, and this did not follow the primacy principle. We suggest that the quality and quantity of value-added analyses should be improved and that feedback be provided to the institutions releasing the datasets in order to establish a good valueadded analyses ecosystem.
All Science Journal Classification (ASJC) codes