Sentence examples for reconciliation of data from inspiring English sources

The second one concerns the problem of semantic reconciliation of data sources.

Moreover, since the DW integrates the information provided by data sources, it is also crucial to take these sources into account throughout the development process to obtain a consistent reconciliation of data sources and information needs.

Our conclusions should be valuable for reconciliation of data obtained in earlier studies as well as for future meta-analyses utilizing estimates from both traditional methods and the animal model.

After de-duplication and reconciliation of data between the bulletins and the database, data were extracted and analyzed using Microsoft Excel 2010, version 10 (Microsoft Corporation).

Actually, GenoQuery is generic enough to be used straightforwardly in other relational genomic data warehouses where reconciliation of data is not fully achieved (redundant and divergent pieces of knowledge are allowed).

To provide accurate information, patients and isolates data were abstracted in the following two steps, (i) manual work through of laboratory records, and (ii) physician-assisted medical reconciliation of data.

This makes the reconciliation of the data hard and far from providing a gene expression atlas of the species.

This example exemplifies how the reconstruction process can drive the reconciliation of isolated data from different biological databases.

Since the reconciliation of the data is not mandatory, it is possible to examine the different points of view of the sources, without forcing the reconciliation of all the data.

The reconciliation of these data comes when allowance is made for the intracellular buffering which, as shown by previous studies [ 8], is highly nonlinear over the range of [Ca2+]i measured in this study (~75 2,000 nmol/L).

Finally, our study suggests a mild pandemic, characterised by case and infection severity ratios increasing between the two influenza waves, while the process of synthesis and reconciliation of the data available from different sources has highlighted the importance of transparent design of routine influenza surveillance to derive robust estimates of key measures of severity.