Final answer:
DSS systems like the NNDSS and SDSS gather data from organized historical records, current observations, and user contributions. The SDSS, in particular, used advanced technology to map the universe, entailing massive data analysis and public participation through citizen science projects like the Galaxy Zoo.
Step-by-step explanation:
Decision Support Systems (DSS) acquire their data from a multitude of sources, including historical records, current data feeds, and contributions from users. For example, the National Notifiable Diseases Surveillance System (NNDSS) relies on data for retrospection and prediction of disease trends by time and place. In the realm of astronomy, the Sloan Digital Sky Survey (SDSS) obtained data from an array of 30 charge-coupled devices (CCDs) over more than ten years, capturing over 500 million objects and spectra of 3 million, to create comprehensive three-dimensional maps of the universe. Projects like SDSS generate enormous datasets, in this case upwards of 15 terabytes of data, requiring the use of supercomputers and advanced algorithms for effective analysis. The SDSS also employed citizen science initiatives such as the Galaxy Zoo project, which involved the public in data classification tasks that are challenging for machines but suitable for the human eye's pattern recognition capabilities. These methods together with electronic, continuously updated access to datasets, have proven crucial in managing and utilizing large volumes of data.