The term "complementary data sources" is a correct and usable phrase in written English.
It usually refers to multiple data sources which, when taken together, provide an enhanced and more comprehensive understanding of a particular subject. For example, you might use a survey and focus group interviews as complementary data sources when studying customer attitudes.
The addition of complementary data sources may improve the accuracy and usefulness of data from any one source.
That is, the company went from offering dashboards to offering insights by adding complementary data sources and enabling online-to-offline attribution and engagement in physical locations.
We employ a number of complementary data sources, some covering the entire country and some being based on subsets of cantons.
Our findings highlight emergent synergies between complementary data sources that foster the generation of new information products for forest resources management decision support.
Such agricultural modelling and simulations need access to elaborated geolocated genetic-trait information as well as complementary data sources coming from geospatial data providers and geospatial data hubs, e.g. soil moisture data, climate data.
To investigate our premise, we conduct comprehensive surveys and interviews with 33 founding entrepreneurs, comparatively analyzing their experiences against complementary data sources to develop personal profiles of critical attributes and behavioral characteristics.
In site specific or single landslide investigations the PS data can represent a very useful complementary data source with respect to the information acquired through ground based observations and in situ surveying.
Possibly, the added value of users' design feedback as a complementary data source may be reduced in evaluations of interactive systems for the general public; here, the users' design feedback may not add much to what is already identified through interaction data or usability experts' findings.
Further validation of these Internet search data has the potential to provide a valuable complementary data source for measuring the effects of health policies.
Further validation of these methods has the potential to produce a timely, complementary data source for studying the effects of health policies.
Due to their significant advantages in timeliness, efficiency, and transparency, search data have the potential, with adequate validation, to become an important complementary data source for researchers and decision-makers studying the effects of public health policies in local and international settings.
