Sentence examples for incorporating data sources from inspiring English sources

That was the first showcase of Dapper's newly added support for incorporating data sources that require login and it's just plain useful.

To overcome these limitations, many informal platforms, defined as surveillance incorporating data sources outside of government and clinical systems, have been developed in the last two decades.

11 Incorporating data sources external to the malaria program, and even the health system, into the malaria elimination information system will improve decision making.

Identifying which traits to incorporate, data sources for model parameterization, and determining the extent of a species adaptability remains challenging [56], [57].

We recommend that, in those systematic reviews where reviewers incorporate data sources in which citations do not have a direct one-to-one relationship with studies, reviewers make this relationship transparent at some point in a study selection diagram.

Documents from the industry day note that the system should be able to handle both classified and unclassified information, and incorporate data sources both on the ground and in space.

This operation was performed by means of machine-learning and by incorporating data from other sources, including Wikipedia.

This review provided evidence-based estimates of the full incubation period distribution for each of these diseases, incorporating data from primary sources identified through the review.

This can only be achieved by incorporating data from multiple sources, such as localization (see above) and interaction studies (e.g., two hybrid studies, analyses of immunoisolated protein complexes), metabolite interactions, and microarray expression analyses.

But what do I know?" Google had done a better job than Apple in mapping Japan, incorporating various data sources and putting its software engineers to work to tailor its map app to meet local needs and tastes.

In order of frequency, they are: retail, which wants better customer understanding; security threats and fraud detection; gaining efficiency in the operation of information technology; analyzing information from other networked machines, like sensors on electricity grids; and incorporating new data sources, like Twitter, into existing databases.