Longitudinal data systems (LDS) come in many different shapes and sizes. While all basic systems should share a number of fundamental characteristics, the specific features and the paths taken to implement them will differ among states and districts. LDSs are often conceived and built over time, in a piecemeal fashion, with the consequence that "real" systems are not always "ideal." When possible, therefore, the system should be planned carefully from the outset, with an overarching design intended to meet specific state or local needs and goals. The best approach is to use the organization's questions and desired functionalities to drive LDS design, and the system's various components and functions should be seen as means to desired ends, not ends in and of themselves.
This chapter presents the spectrum of LDS features, including core components and characteristics a well-designed LDS must have ("basic"), as well as attributes that can transform a basic system into a high performance one ("expanded"). While the "basics" will meet the common, core goals of a P–20 LDS, the "expanded" components provide greater efficiencies and capabilities. Attaining all of these characteristics may be challenging technologically, politically, and financially—but well worth the effort in terms of functionality and benefit to stakeholders. As time passes, components once viewed as "extra" or "nice-to-have" (for example, linkages between P–12 and postsecondary and workforce data systems) become the norm as agencies advance in their LDS development efforts.
Many of the features listed in table 1 were drawn from the Data Quality Campaign (DQC), which has been a leader in encouraging LDS implementation; however, many others agree that these are key features and capacities.