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Understanding the Data Model

Core Concepts

The following are the key concepts and terms in the National Education Data Model.

Data Model Top-Level Classes

In the Data Model Browser, the Data Model content is arranged in a tree-type structure. There are ten top-level classes (or branches) of the tree. On the Data Model Browser screen, the list on the left of the allows the user to “drill down” into the subclasses that are below each top-level class.

1.Class

A class is, “A set, collection, group, or configuration containing members regarded as having certain attributes or traits in common; a kind or category.” To distinguish between entities and classes the Data Model uses a capital first letter in the names of classes while entity names begin with a lower-case letter. For example a Person is a class while a staffMember is an entity. The figure below illustrates the relationships between the concepts. Entities, which identify what needs to be tracked by education systems, are organized into classes and sub-classes. Each entity may have attributes, which represent the measures are used to track the entity. In the Data Model, entities may relate to other entities.

class

2. Entity

An entity is the basic building block of the Data Model. Entities are the constructs that need to be tracked, measured, and described by software systems in order to support education processes. Entities can be:

  • Persons such as students, parents, or staff members.
  • Capital Assets such as schools, school busses, or buildings
  • Events such as test administrations, class meetings, or discipline incidents
  • Tools such as books, networks, computers, lessons, or assessments
  • Concepts such as perceptions or skills

entity

3. Attribute

An attribute is information about an entity that you can measure, classify, or describe. An attribute is not a calculation or statistic, and it generally does not contain counts. Attributes in the Data Model are generally not generic measures or data elements that can connect to a number of entities. In the Data Model, each attribute is designed to be unique to the entity that it measures. Common Attributes are an exception to this rule.

Some examples of attributes include:

  • A measurement, current state, or a trait of an entity
  • A person’s name, phone number, or IM address
  • An education institution’s name, location, or size
  • The date of a test administration, the value of an assessment score
  • Lesson’s topic, grade level, or student’s learning style
  • A teacher’s self efficacy with respect to classroom management

4. Common Attributes

Attributes are usually specific to each entity. However, a small set of attributes exist that apply to multiple entities. These attributes are referred to as common attributes and are arranged into a taxonomy below. This taxonomy of common attributes should not be confused with the Data Model taxonomy of entities.

This limited set of Common Attributes are included for the sake of consistency of definition and to promote uniformity in the specification of attributes. The common attributes are expected to change as the Data Model continues to be updated with the most up-to-date set of descriptors. Items lower in the hierarchy are more specific than those above. Items at any level in the hierarchy may be associated with an entity.

Name

  • Alias
  • First Name
  • Former Legal Name
  • Generation Code/Suffix
  • Last/Surname
  • Last/Surname at Birth
  • Middle Name
  • Nickname

Locus

  • Location
  • Physical Location
    • Physical Address
    • Latitude/Longitude
    • GPS Coordinates
  • Virtual Location
    • IP Address
    • URI
    • Postal Address
  • Connection Id
    • e-mail Address
    • Phone Number
    • Screen Name
    • IM address
  • Schedule
    • Day/Date/Time
    • Periodicity
    • Length

Person Characteristic

  • Demographic
    • Ethnicity
    • Sex
  • Role
  • Physical Characteristic
    • Weight
    • Picture/Likeness
  • Status

Document Metadata

  • IEEE LOM
  • Dublin Core
  • SIF
  • RDF

Evaluation

  • Resources Consumed
    • Financial Resources
    • Time Resources
    • Human Resources
    • Curricular Resources
    • Instructional Materials
      • New Technology Resources Used
      • Equipment Used
      • Supplies Used
    • Facilities Resources
      • Number of Buildings
      • Square Feet
  • Measurable Goals and Outcomes
    • Academic Goals
      • Academic Achievement
      • Skills Acquisition
      • Skill Certification
    • Non-Academic Goals
      • Health Effects
        • Physical
        • Emotional
        • Developmental
      • Social Effects
        • Community Service
      • Participation Effects
        • Retention
        • Enrollment
        • Completion
    • Goal-Based Outcomes
  • Target/Served Population
    • Size
    • Demographics
    • Program Baselines
    • Method of Identification
    • Population Characteristics
  • Methodology
    • Measurement
    • Analysis
  • Characteristics
    • Program Availability
      • Geographic
      • Calendar
      • Length of Program
      • Periodicity of Service
      • Length of Services
    • NCES Program Type
    • Delivery Methodology
      • Constructivism
      • Inquiry Based
      • Directed Instruction
      • Virtual
      • Groupings

5. Relation

In addition to the taxonomy structure (based on entity characteristics), the Data Model contains natural relationships among the entities. For example, in the Data Model taxonomy, the Student entity is not close to the Class entity, but the Data Model stores and reflects the relationships between them. The figure below shows examples of the types of relations contained in the Data Model.

The relationship descriptors include verbs or short verb phrases that connect the subject with the object. For example, student (subject) receives services from (relation) teacher (object). This information within the Data Model allows for intelligent searching and for creation of subparts of a model.

examples of possible relationship descriptors include:

  • Provides
  • Supports
  • Delivers
  • Participates in
  • Disrupts
  • Enhances

Types of Relationships in the Education Data Model.

relation

6. Taxonomy

The entities, classes and attributes in the Data Model are organized into a taxonomy. As illustrated below, entities (marked with E) are organized into classes and subclasses (marked with C). Each entity has its own set of attributes (marked with A). Entities are grouped together based upon common characteristics.

Taxonomies arrange items into categories based on like characteristics. For example, lesson plan and unit plan are both types of academic plans in the Data Model, but lesson plan and unit plan differ based upon the scope and purpose of the plan. The “is a type of” organization scheme ensures, with few exceptions, that each entity has one, and only one, place in the arrangement.

For example, in the Data Model, a portfolio is a type of formative assessment is a type of assessment is a type of instruction artifact.

Just like in the Linnaean taxonomy of living things, a homo sapien is a type of hominidae is a type of primate is a type of mammal is a type of chordate is a type of animal.

There are exceptions and hard-to-classify cases, similar to the duck-billed platypus in the taxonomy of living things, which, as a mammal that lays eggs, defies a clean classification. The Data Model taxonomy is similar in form and function to other well-known taxonomies, such as the Linnaean taxonomy of living things discussed above or historically used classification systems such as the Dewey Decimal system. As one becomes familiar with the structure of the taxonomy, locating a particular entity becomes easy. In addition, the provided tools for using the Data Model have search features that provide convenient means for locating items in the taxonomy.

Taxonomy of Classes, Entities, and Attributes

taxanomy

7. Concept Map

The Concept Map describes the structure of the Education Data Model. It represents a logical and finite set of relationships among classes, sub-classes, and entities, thereby striving to depict the entire domain of education information. It adds multiple simultaneous relationships among the entities to the taxonomy. The relationships among entities are designed to be mutually exclusive but may sometimes overlap in meaning or usage. To feature the relationships among the entities presented previously in figure B, figure G turns the taxonomy inward.

Concept Map

concept map

Data Model Top-Level Classes

In the Data Model the content is arranged in a tree-type structure. There are ten top-level classes (or branches) of the tree. On the Data Model screen, the list on the left allows the user to “drill down” into the subclasses that are below each top-level class.

Association - Functional associations among individuals, organizations, events, and programs.

Education Leadership Artifact - Artifacts are related to the leadership of teaching and learning processes.

Event - The Event entities represent any event within the education organization.

Information Exchange - The Information Exchange entities represent information being communicated.

Instruction Artifact - These entities represent any piece of information related to a student’s learning or the general learning process.

Operations Artifact - These entities relate to the administrative or operational side of the organization.

Organization - These entities represent the grouping of resources and people in order to reach a particular goal.

Person - Individuals within the education setting.

Place - These entities represent the locality or area within the education environment.

Program - A plan of activities and procedures to accomplish a set of objectives.

x_Extensions - This class is not a regular part of the Data Model. It is a category that contains extensions to the Data Model. For example, the category could hold Education Data Exchange Network (EDEN) input file definitions or fact table definitions for a data warehouse. This category allows concepts that are not allowed in the Data Model, such as aggregate statistics or report definitions, to be linked to entities and relationships in the Data Model.

Locating information in the Data Model

Rather than present long lists of entity items, entities are presented in a hierarchy or taxonomy. Each entity is classified according to one or more levels of class. The classes serve to group entities based upon like characteristics or function. This is similar to the Library of Congress or the Dewey Decimal system in which books are organized by subject. If you know a little about the characteristics of the book you are looking for, even if you do not know its name, you have a good chance of easily finding the book.

However, grouping based upon similar characteristics do not always place things that have a strong relation to each other in close proximity. For example a book about Abraham Lincoln’s presidential policy successes and failures might be in a political science section while a book about the civil war would be in the history section even though they are very closely related when one wants to know more about the context within which Lincoln made his most important decisions.

Similarly, an education entity such as lesson, or lesson plan might not be located near a teacher in the taxonomy. Though the design of lesson plans and the delivery by teachers of lessons to students are important process scenarios that show a strong relation among the lesson, lesson plan, teacher, and student entities, this relationship is not reflected in the taxonomy. The Data Model does have a mechanism that allows important relationships among entities to be contained within the Data Model. The Relationships section of each Entity page shows the important relationships of each entity to other entities.



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National Center for Education Statistics - http://nces.ed.gov
U.S. Department of Education