sgpData is a database that provides students’ growth data in the form of percentiles, allowing teachers and parents to easily view student progress over time. The percentiles can also be used as a tool to identify giftedness, or to monitor the performance of a student with disabilities or special needs. In addition to providing students’ growth information, sgpData provides a number of additional features that make it easy for educators to analyze student data.
The sgpData database contains data from students who took tests at various schools and in different years. The first column of each record (ID) provides a unique student identifier. The next five columns (SS_2013, SS_2014, SS_2015, SS_2016, and SS_2017) provide the scale scores associated with the student’s test record for each year. For students who did not have a scale score for all 5 years of testing, sgpData records a missing value (NA).
Student growth percentiles are derived by comparing a student’s assessment results from one year to the test results from the same or similar assessment in previous years. Although calculating student growth percentages is complex, it provides valuable information about the performance of a student over time. Moreover, percentile scores are familiar to teachers and parents, making them easy for them to interpret and understand.
The SGP project began in 2015, with the goal of assembling or generating multi-proxy sedimentary geochemical data (iron, carbon, sulfur, major and trace metal abundances, and their isotopes) from multiple regions worldwide for each Paleozoic epoch. This required a major effort to collect the data, and to reprocess and reformat it for use in the SGP system.
SGP’s second goal was to develop a framework for the long-term preservation and dissemination of these data. To do this, SGP established a working group of geochemical experts who have collaborated to define a series of standards for data storage, processing, and publication. The SGP working group has also identified potential partners for implementing these standards.
While research consortia and large community databases (Genbank, EarthChem, etc.) both aggregate data, they have very different approaches and goals. Research consortia are focused on answering specific research questions, while large community databases are designed to store and make accessible essentially all data. Both types of aggregation have their strengths and weaknesses, but the fundamental difference is that research consortia have a clear purpose that drives their data collection and sharing decisions. This purpose allows researchers to focus their efforts on exciting projects, which in turn attracts funding and other resources to the research effort. It also provides incentives for individuals to contribute data and metadata to the project. This is why the SGP project was created in the first place – to assemble and share data for answering compelling research questions. SGP members are currently pursuing many exciting research topics in this way. They have contributed or are preparing to contribute a significant amount of data and metadata.