The goal of the Forum Data Model Task Force was to produce a conceptual data model that is both comprehensive and useful. Most K-12 education agencies in the United States utilize data models embedded in the various purchased software applications at the school, LEA, or state level. The Education Data Model provides information to make all purchasers of such software and systems informed consumers, and to facilitate productive conversations between users and software developers in discussing accurate data system features and functionalities. The Data Model is a blueprint for identifying information needs and establishing expectations between educators, administrators, and software developers. This chapter discusses how educators, vendors, and researchers might use the tools described in Chapter 3 to utilize the Data Model.
Following are three vignettes that illustrate how the Data Model can be used by educators, vendors, and researchers. In addition to the vignettes below, the Data Model website contains "use case scenarios" that explain in more detail the steps a user could take in applying the Data Model to a specific usage scenario.
Educator Vignette
Challenge
An LEA wants to evaluate a proposed education software system to see if it will contain the range of data needed to perform its stated function.
The LEA also wants to ensure that data definitions in the proposed software are consistent with definitions in other software systems already used by the LEA and in reports the LEA is required to generate.
Solution
Use the Data Model to identify requirements.
An LEA staff person goes to the Data Model Search tool that is part of the Data Model website and runs a query. For example, if the proposed system is a special education system, the query term might be "program." A query for the term "program" limited to entity names and class names containing that term would produce the following results:
The staff person also uses the navigation bar to find entities of interest, for example "gradingAssignment."
The staff person follows the relationship links listed for each entity to find other entities that the staff member judges to be related to the requirements of the software system.
From all of the entities found, the staff person compiles a shorter list of entities that are directly related to the software system. This list is the "Information Requirements" for the system.
Perform a gap analysis.
The staff member, or the vendor, maps the information in the proposed system to the Data Model Information Requirements.
The staff member compares the Information Requirements to the proposed software system. This is done by using the entity descriptions and attributes for each entity in the Data Model Information Requirements.
The staff member summarizes the results in a gap analysis document.
Use the Data Model as a canonical conceptual model.
Since the LEA has adopted the Data Model as a standard, all software systems have been mapped to the Data Model; thus, the Data Model is a canonical or standard conceptual model that all physical data models (software designs) refer to.
An LEA staff member maps the proposed software system to the Data Model.
During the mapping process, the staff member discovers whether the proposed system data definitions are consistent with other software systems used by the LEA. This is possible because the Data Model data definitions represent the definitions used in the LEA.
Vendor Vignette
Challenge
A vendor wants to ensure that a new education software system that the vendor is building has all the "Information Requirements" needed to fulfill the purpose of the software.
Solution
Use the Data Model to identify requirements.
Using the content domain and the education processes addressed by the new software system, the vendor develops a set of search terms for the Data Model.
The vendor goes to the Data Model Search tool that is part of the Data Model website and runs a series of queries.
The vendor compiles a list of entities that are relevant to the functions of the new software.
The vendor follows the relationship links listed for each entity to find other entities that the vendor judges to be related to the functions of the new software system.
The vendor compiles a complete list of entities that are related to the software system. This list is the "Information Requirements" for the system.
Extract a software-specific conceptual model.
Using the entity descriptions, relationships, and attributes for each entity in the Data Model Information Requirements, the vendor builds a conceptual model specific to the new software system.
Build logical and physical models.
Using the software-specific conceptual model, the vendor builds a logical model for the software.
Using the logical model, the vendor builds a physical model for the software.
A gap analysis is performed between the software-specific conceptual model and the physical model to ensure that the physical model has addressed all Information Requirements.
Researcher Vignette
Challenge
A researcher or a state department program director is creating a research project that will use data available in a state- or district-wide data system. The researcher wants to know what data elements exist now and are expected to exist in the future.
Solution
Use the Data Model to identify requirements.
Using the content domain and the theoretical framework of the research project, the researcher develops a set of search terms for the Data Model.
The researcher goes to the Data Model Search tool that is part of the Data Model website and runs a series of queries.
The researcher compiles a list of entities that are relevant to the research.
The researcher follows the relationship links listed for each entity to find other entities that are related to the research project.
The researcher compiles a complete list of entities that are related to the research. This list is the "Information Requirements" for the research project.
Attributes for each entity that are relevant to the research project are also listed.
Prepare a research design.
The researcher can now use the Information Requirements to prepare a proposed research design.
The Information Requirements in the research design are investigated for availability, or a plan for collecting the data is developed.
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