"Big data" are increasingly discussed in academic venues and elsewhere as an unquestioned good.
Thus, evidence from studies using routinely accumulated clinical data are increasingly valued.
Meanwhile, efforts to calibrate the existing taxonomy with phylogenetic anchors and genomic data are increasingly robust.
High-dimensional data are increasingly encountered in other applications of statistics, e.g. in biological and financial studies26,27.
In this respect, biomonitoring data are increasingly becoming a primary basis for hazard identification as well as dose-response assessment.
Large volumes of geospatial data are increasingly made available through dynamic networks, such as ad hoc networks.
Satellite data are increasingly used to provide observation-based estimates of the effects of aerosols on climate.
Further, these patterns must somehow reflect environmental conditions, and such data are increasingly available in the four-dimensions of latitude, longitude, depth, and time14,15.
But the move also reflected deepening unease in Europe over the way personal data are increasingly used by companies and by governments.
Security and privacy of user, application, device, and network resources and data are increasingly important areas of network architecture and design.
Neuroimaging data are increasingly being used to predict potential outcomes or groupings, such as clinical severity, drug dose response, and transitional illness states.
