Sentence examples for data quality operational from inspiring English sources

Each panel member was asked to provide feedback on the appropriateness of the revised round one characteristic definitions and to rate the importance of all 28 characteristics for one of the three EFISS areas (i.e. data quality, operational, or practical characteristics of an injury surveillance system).

As a result, both the data quality and operational efficiency are improved.

There is essential work to be done training a core of people in very hard problems, like advanced statistics and software that ensures data quality and operational efficiency.

To address this problem, we constructed an automated software named MetaDP for 16S rRNA sequencing data analysis, including data quality control, operational taxonomic unit clustering, diversity analysis, and disease risk prediction modeling.

At the conclusion of the modified-Delphi study, the definitions of six data quality, two operational and one practical characteristic of an injury surveillance system were all rated as appropriate and were considered suitable for use in an EFISS (see Table 4).

The aim of this round was to reach consensus from a panel of experts on the suitability of 11 proposed characteristic definitions (ie. 6 data quality, 3 operational and 2 practical characteristics) for an injury surveillance system, the importance of these 11 characteristics for injury surveillance, and the practicality of assessing these 11 characteristics in an injury surveillance system.

All data quality characteristics, one operational (i.e. timeliness) and one practical (i.e. usefulness) characteristic were rated by the majority of the panel as ' very/extremely' appropriate in round 2 (Table 2).

The overall purpose of DMIP 2 was to test many distributed models forced by high quality operational data with a view towards meeting NWS operational forecasting needs.

The advantage of the data-centric architecture is that the data quality is controlled, effects of operational system are minimized, and few components need to be highly available.

This included all characteristics in the data quality group, all but one operational characteristic (ie. stability of the system), and just under half of the practical characteristics (Table 1).

This study aims to serve as guide of best practices for increasing life-cycle, operational availability and data quality of sensors specifically in cold climates.