SIF AssociationCCSSO

News & Updates

"The NEDM project has been very helpful in the ongoing expansion of the eScholar Complete Data Warehouse. By leveraging the work of the NEDM in finding commonality among education data attributes across disparate systems and organizations, we are able to more quickly deliver broadly applicable enhancements."
-Shawn Bay
 Founder/CEO, eScholar LLC

“What I’ve found helpful about working with NEDM is that it provides us with a starting point for our work to expand our data system. In New Jersey, we have multiple, fragmented data collections that grew over the years as independent entities. Our challenge is to build out our SLDS to incorporate what we’ve been collecting but also focus on what we may not have been collecting. NEDM is a fabulous tool to help us establish our priorities for which data elements and collections should be incorporated first and also to provide the more global guidance of what the data values and formats should be for each new data element.”
-Bari Anhalt Erlichson PhD
 Director Office of Research and Evaluation, New Jersey Department of Education

Examples of How to Use 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, this web page has links to documents containing “use case scenarios” that explain in more detail the steps that one could take in applying the Data Model in a specific usage scenario.

Educator

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 in the LEA and in reports the LEA is required to generate.

Solution

1.    Use the Data Model to identify requirements

  • An LEA staff person goes to the Data Model Browser 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.”
  • The staff person also uses the navigation bar to find the entity: supplemental programs.
  • 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.

2.   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.

3.  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. So the Data Model is a canonical or standard conceptual model that all physical data models (software designs) refer to.
  • A 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 in the LEA. This is possible because the Data Model data definitions represent the definitions used in LEA.

Vendor

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

1.  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 Browser 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 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.

2.  Extract a software-specific conceptual model

  • Using the entity descriptions, relations and attributes for each entity in the Data Model Information Requirements, the vendor builds a conceptual model specific to the new software system.

3.  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 all Information Requirements have been addressed by the physical model.

Researcher

Challenge

A researcher or a state department program director is creating a research project that will use data available in the schools. The researcher wants to know what data elements are expected to exist now and in the future in school-based software systems.

Solution

1.  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 Browser 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.

2.  Prepare a research design

  • The research 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.

Use Case Scenarios

The documents below contain use case scenarios. Each document takes a specific situation or scenario and builds a use case or example of usage for the Data Model.

Evaluating a Student Information: Download, view and print the Guide as a pdf file. PDF File (26 KB)

Using the Data Model to Answer Important Education Questions: Download, view and print the Guide as a pdf file. PDF File (25 KB)