Data Interoperability and Equity Glossary

Overview

Explore a glossary of common terms related to data equity and interoperability. Then complete the knowledge check that follows. Click on the + sign below the glossary to learn about more general terms related to equity.

 

Data equity: captures a complex and multi-faceted set of ideas. It refers to the consideration, through an equity lens, of the ways in which data is collected, analyzed, interpreted, and distributed.

Data collection: the process of gathering and measuring information on targeted variables in an established, systematic fashion.

Data governance: the management of all available data to ensure that its usability, integrity, and security is maintained within an organization. This work is not about data itself, but rather the business processes, stakeholders, and decisions around data. It provides checks and balances to ensure data changes are implemented with appropriate oversight and in the best interests of all parties within an organization.

Data interoperability: the seamless, secure, and controlled exchange of data between applications.

Data power dynamics: examines the way in which power works and recognizes the relationship between various overlapping stakeholder groups that create, use, or own the data. It notes how power dynamics can negatively impact progress, decisions, or collection of the data or can produce more shared power and capacity to provide a more holistic, nuanced, and equitable outcome. 

Data quality: the condition of data in a database related to its completeness, consistency, uniqueness, and validity.Completeness: Are all data sets and data items recorded?
Consistency: Are all data sets and data items recorded the same?
Uniqueness: Is there a single view of the data set?
Validity: Does the data match the rules?
Equity stance: Is the data centering the voices and assets of historically and systematically excluded communities? Is data gathered from an anti-racist lens? Have the processes and ways the data is grouped been evaluated from this stance or are traditional methods continuing to be used without attention to implicit bias? Is data taking into account and measuring the whole child and their intersectionalities? 

Data security: privacy procedures that are applied to prevent unauthorized access to data, including printed information, hard drives, computers, databases, websites, and any other form of data. It also protects data from corruption.

Data steward: the person responsible for the management and fitness of data elements—both the content and metadata. He/she should have a deep understanding of the connection between the data and program needs. May be a data coordinator in a program office.

Data usability: the degree of ease with which data can be used to achieve required goals effectively and efficiently.

Data-related pain points: issues encountered when working with data.

Strategically sorting the data: the thoughtful process of disaggregating the data by race, gender, IEP category and status, home language, etc. Strategically sorting the data empowers stakeholders to recognize any existing outcomes, trends, and disparities.

System of record: The authoritative data source for a given data element or piece of information.

Use case: a concrete, discrete problem that can be solved by or benefit from connected education technology systems.