Sentence examples for data exploration and visualization from inspiring English sources
Here, we discuss several data exploration and visualization projects enabled by the GPIES database.
WeSpace has been developed for a population of scientists who frequently meet in small groups for data exploration and visualization.
The ever-growing datasets in observational astronomy have challenged scientists in many aspects, including an efficient and interactive data exploration and visualization.
Students with particular proficiencies are highly valued: familiarity with either qualitative or quantitative information-gathering approaches about student experience (asking questions, doing surveys), as well as cutting-edge data science tools for data exploration and visualization.
Frequently, it is data exploration and visualization that allow Big Data to unleash its true impact.
Moreover, IDA provides a web-based user interface for data exploration and visualization.
National Sleep Research Resource : A web-based data portal that aggregates, harmonizes, and organizes sleep and clinical data from thousands of individuals studied as part of cohort studies or clinical trials and provides the user a suite of tools to facilitate data exploration and data visualization.
Although most network visualization tools are standalone applications, they guarantee efficient data exploration and the manipulation of visualization with mouse-hovering supporting actions.
Knowledge Discovery Process: Data pre-processing for data mining, including data cleaning, selection, efficient sampling, and data reduction methods; evaluating, consolidating, and explaining discovered knowledge; data and knowledge visualization; interactive data exploration and discovery.
She has methodological expertise in the use of qualitative, mixed-methods, trajectory science and visualization methodologies for complex data exploration, and intervention development and testing.
On future exascale platforms, the datasets are expected to be too large to be efficiently stored and transferred across networks to analysis and visualization workstations, thus impeding data exploration and knowledge discovery.
