Data SGP, Singapore’s data-driven approach to urban planning, is helping transform Singapore into a sustainable and efficient Smart City. By consolidating data from multiple sources and applying analytics on it, Data SGP allows urban planners to predict problems before they arise and create more livable, resilient cities.
Normative Growth is a statistical technique used to gauge student performance by comparing it with that of their academic peers. An SGP score measures where an individual stands among peers across content areas based on up to two years’ of MCAS assessment results; average SGP for Reading, Math and Science grades or any combination thereof can be determined using quantile regression as part of this calculation process and placed on a normative scale.
What are my options for accessing Data SGP? The Data SGP initiative aims to assemble a dataset designed to address Earth history questions; however, its scope remains relatively small in comparison with other geochemical data sets (see Why is this project important). More specifically, its focus lies on one geological time interval at a time and predominantly covers shale geochemical information.
This project brings together data from various organizations and agencies in order to make it more useful for scientists. Researchers now have one central source for all geologic time periods that they study, eliminating both time and expense associated with collecting their own information.
Additionally, Data SGP allows them to compare their data with that of other organizations and agencies to identify patterns that could help answer scientific questions. It aims to streamline how data is handled through sharing of metadata associated with datasets as well as standardizing formats in order to facilitate further analysis.
Data SGP seeks to establish a permanent digital repository of research data so it may be used for future studies, following a national initiative to make research data freely available to the public.
Singapore has long been at the forefront of urban planning, and relies heavily on Data SGP to make better decisions regarding housing, transportation, sustainability and disaster risk reduction. Real-time traffic data can be collected via sensors and cameras and analyzed to optimize traffic light systems and control congestion. Environment data is also collected via IoT devices and satellites, and analyzed to inform policies that reduce air pollution and optimize water usage. Urban planners utilize Data SGP’s simulation tools such as digital twins to simulate planned projects’ impacts on surrounding communities – this allows them to predict how new infrastructure may impact traffic, as well as ensure new buildings and parks are built with sustainability in mind.