High-quality data are fundamental to OSEP’s vision for Results-Driven Accountability (RDA), which focuses on using data to improve results for infants, toddlers, children, and youth with disabilities. RDA represents a shift from an accountability system concerned primarily with compliance to one that puts greater emphasis on improving educational results and functional outcomes for children with disabilities and supporting their families. Having high-quality data systems for Part C and Part B 619 programs will improve states’ capacity to collect, analyze, report, and use high-quality data required under the Individuals with Disabilities Education Act (IDEA).

Data-informed decision-making is at the heart of improving the operation of programs and provision of evidence-based practices and supports and, ultimately, of improving results for all children and families, especially those who have been historically underserved. A fundamental assumption reflected throughout the DaSy framework is that Part C and Part B 619 state staff will use data regularly to administer the program and make improvements. High-quality data are instrumental in answering key policy and programmatic questions including those related to equity (see discussion below in section on Cross-Cutting Themes). For example, data are an important tool to ensure that children have equitable access, services and supports, and outcomes. However, this has often not been the case for Black, Indigenous, Hispanic and/or Latino and other children of color, as well as children from low-income households and isolated communities. Thus, it is important that data are collected, analyzed, and used intentionally to examine equity for underserved groups and communities.

The use of the term data system is conceptualized broadly in the DaSy framework. It refers to the hardware, software, and other applications and processes that enable Part C and Part B 619 programs to collect data about children, families, workforce, and/or program characteristics (e.g., program quality), as well as the analysis, reporting, and data use practices associated with those data. We use the more narrowly defined term of database application to refer to the computer software programs used to enter, store, organize, and retrieve data or information from a computerized database. Database applications allow multiple users to access and use the data, while also securing the data by permitting access by only authorized personnel who can perform various functions with the data, such as entering, querying, updating, and creating data reports.

The DaSy framework was intentionally written to set a high bar for state data systems; a state that has addressed the entire contents of the DaSy Framework will indeed have a high-quality data system. The DaSy framework also was designed to be comprehensive and aspirational. Everything necessary for a high-quality data system is addressed; although we recognize that most states have not yet achieved the entire range of characteristics described in the DaSy framework. A question repeatedly asked during DaSy framework development was, “What does high quality look like?” This question was asked about all facets of the DaSy framework’s broad conceptualization of data systems, including the kinds of data collected, the uses of data, the process and structures for governing the data, and the processes for developing or enhancing the technology.

The phases of developing a new data system or enhancing an existing one are commonly viewed as a life cycle (Figure 2), and the DaSy framework subcomponents reflect this. The life cycle model is a high-level view of the major sequential stages a data system goes through. The cycle begins with planning and initiation that reflects the intended Purpose and Vision subcomponent. Next, having a process to identify the need for a new database application or changes to an existing application — for example, user needs for enhancing reporting capability or the need to address a new federal reporting requirement — is addressed in the Sustainability subcomponent. The Data Governance and Management subcomponent addresses the approval to move forward with the change to the data system, the first step in initiating a new system or an enhancement. The phases and processes related to the development of a new system or the enhancement are covered in the System Design and Development subcomponent. The ongoing development and implementation of policies and procedures to manage the data system are part of the Data Governance and Management subcomponent, with the evaluation of how well the system is meeting user needs and recommendation for changes covered in the Sustainability subcomponent.

Each of the DaSy framework’s five subcomponents contains one or more quality indicators (QIs) and multiple elements of quality (Figure 3). Quality indicators are broad statements about actions or activities that state agency staff undertake or the policies, procedures, or documents that the state needs to have in place to support a high-quality data system. Each quality indicator has a corresponding set of elements of quality that operationalize the implementation of the quality indicator. The elements of quality describe various aspects of the quality indicator. In short, quality indicators describe what quality is in a data system, and the elements describe how quality is achieved.

Second, stakeholder engagement is another critical theme because key stakeholders should contribute to each of the subcomponents in certain ways. Members of stakeholder groups may differ depending on the data system topic. Many topics such as the purpose of the data system and uses of the data require input from a broad representation of stakeholders. Other more technical topics such as the development of the business requirements or security features require input from a more limited group of stakeholders. For topics requiring broad stakeholder input, it is essential that the stakeholders fully represent all families, providers, and others, especially those who have been historically underserved and have an interest in the role of data in contributing to a high-quality state system.

Third, an important and aspirational feature of the data system DaSy framework is the emphasis on the integration of the Part C and Part B 619 data with each other and data from other programs serving young children in the state through collaborative data initiatives such as Statewide Longitudinal Data Systems (SLDS) and Early Childhood Integrated Data Systems (ECIDS) (see additional information on pages 6−7). Therefore, elements in several of the subcomponents address the need for states to build early childhood integrated data systems and for Part C and Part B 619 to be a part of these efforts.

Fourth, the 2022 revision includes equity as a cross-cutting theme. Data systems should be designed—and the data collected, analyzed, reported, and used to support equity—to identify disparities with regard to access, services and supports, and outcomes of children and families served in Part C and Part B 619 programs. Equity considerations are embedded throughout the data system framework. For example, the purpose of the data system needs to address key policy and program questions about equitable access, services and supports, and outcomes (see Purpose and Vision subcomponent). Similarly, equity considerations require the use of best practices for identifying and displaying/labeling data by subgroups of race, ethnicity, disability characteristics, gender, immigration status, home language, geography, socioeconomic status and their intersections (e.g., gender and disability characteristics) (see Data Use and Analysis subcomponent).

During this time a work group of DaSy staff members and consultants began developing the quality indicators and elements for each subcomponent with a review of the literature. The work group also developed a set of questions to gather information about the current status of that subcomponent in each partner state. Drawing on the literature and the information collected from the states, the workgroup drafted preliminary quality indicators and elements of quality. These were reviewed by other DaSy staff and revised, shared with the partner states during the all-state and individual state calls, and further revised based on additional input. The face-to-face meetings provided the DaSy staff and partners with the opportunity to engage in more in-depth discussion and refine the DaSy framework content. In the spring of 2014, DaSy staff conducted a series of conference calls with a group of external reviewers (see Acknowledgments) to further refine the content. Final revisions to the first DaSy framework occurred during summer 2014 and included an overall review by OSEP. The framework was released in 2014.

An additional focus of the revision was to strengthen the framework’s treatment of centering equity in the data systems. A presidential Executive Order in 2021 defines equity as “the consistent and systematic fair, just, and impartial treatment of all individuals including individuals who belong to underserved communities that have been denied such treatment…”1. The Executive Order goes on to note how the federal government’s inability to disaggregate data by race, ethnicity, gender, disability, income and other variables has impeded efforts to measure and advance equity. Data can be used to drive improvement and uncover systemic problems with service delivery but also can and has been used to cause harm to historically underserved groups. Using data to do good and avoid harm requires acknowledging that data are never neutral and that each individual brings their own life experiences and biases to any data activity.

The revision team recognized that equity is a cross-cutting issue that needs to be addressed in different ways and to different degrees in many quality indicators and elements. The earlier version of the framework did not address equity explicitly, which meant that a state data system could be considered high quality when it did not reflect equitable data practices. The framework was revised to make it more explicit that a high-quality data system must address equity. The challenge was that equity is cross-cutting, and it did not seem appropriate or useful to insert data equity concepts into all of the applicable indicators and elements. Rather, the revision calls out equity in key areas where it is especially most relevant/germane. The overall goal was to be intentional about equity and build data systems that support the identification and correction of inequities in access, service delivery, and outcomes. Framework users are encouraged to reflect on the role of data systems in contributing to equity and working against inequity in each of the subcomponents.

As noted above, the importance of stakeholder engagement is woven throughout the revised framework. The makeup of the stakeholder groups is a key equity consideration, and that makeup will differ depending on the specific task addressed in the subcomponent. Regardless of task, for elements addressing stakeholder involvement to be considered to fully implemented, the stakeholders must represent the diversity of individuals with a vested interest in the issue. Stakeholder groups involving families, must include family representatives of the range of demographic characteristics of the state. Likewise, stakeholder groups of users involved in reporting data must be representative of those users. To have a high-quality data system, a state must seek out and incorporate input from diverse voices for the many different decisions presented across the subcomponents.

Because DaSy was tasked with developing a framework for data systems, the two centers agreed that the DaSy data system framework would serve as the Data Systems component in the ECTA framework. Accordingly, the DaSy framework follows the same organizational structure as the ECTA framework (i.e., component, subcomponent, quality indicator, element) to facilitate use by Part C and Part B 619 state staff. The two centers worked closely throughout the initial development of both frameworks to ensure that the DaSy framework was compatible with the other components of the ECTA system framework. Because the DaSy framework was developed on its own in addition to being a component in the ECTA system framework, it has considerably more subcomponents, quality indicators, and elements than the other five components in the ECTA system framework.

In 2019, ECTA began work on revising the ECTA framework. DaSy coordinated with ECTA to revise the DaSy framework, with both centers following the same guidelines. When the revision process was well underway, equity emerged as a critical issue. Both ECTA and DaSy decided to look at the drafts of the revised frameworks through an equity lens and make additional revisions. The equity revision process also was coordinated across the two Centers so the two frameworks would address equity in similar ways.

DaSy also coordinated with the federal technical assistance project working with states on developing SLDS and ECIDS. Funded by the U.S. Department of Education, in 2012 the SLDS Grant Program State Support Team (SST) worked with states to develop a Toolkit for use when building and implementing an ECIDS. The contents of the Toolkit were organized around the seven components of the SST’s Framework for Data Systems. As the DaSy Center was beginning the development of the DaSy framework, the SST was undertaking development of the Toolkit resources. Recognizing that state staff could be using the DaSy framework to improve their Part C or Part B 619 data system while also using the ECIDS materials to participate in broader collaborative data system initiatives, DaSy committed to making its framework compatible with the ECIDS Toolkit. After discussion with the partner states, DaSy decided to use the same components (e.g., Purpose and Vision, Data Governance) as the SDLS framework. As the work on the DaSy framework progressed, DaSy staff found that the SLDS component Planning and Management was not a good fit with the DaSy framework; management-related topics became part of the Data Governance and Management subcomponent, and planning-related topics became part of the Sustainability subcomponent in the DaSy framework. DaSy and SLDS State Support Team staff compared the contents of each ECIDS component with the comparable DaSy framework subcomponent and identified many similarities and some differences that were deemed necessary given the different purposes of the two frameworks.

In 2020 and early 2021, SLDS State Support Team is also revising their materials associated with ECIDS (for the same purposes described for the DaSy framework revision). DaSy staff have continued to collaborate with SLDS State Support Team staff to ensure the two frameworks are compatible and do not contradict guidance provided to states on similar aspects of high-quality data system development, implementation, maintenance, and enhancement.

1. What is quality? The operating assumptions for the DaSy framework are as follows:

• A state that has fully implemented all of a quality indicator’s elements has that quality indicator in place.
• A state that has all the quality indicators in the subcomponent in place has high quality in the subcomponent.
• A state that has all the subcomponents in place has a high-quality data system.

Fully implementing an element means that the element is (1) in place and (2) of high quality. For the sake of brevity and because of the extensive variation across states, the DaSy framework does not provide much detail on what constitutes quality implementation for each element. For instance, one of the elements speaks to the need for a state to develop data governance policies with input from stakeholders. The element does not describe what constitutes high- or low-quality stakeholder participation. DaSy has been compiling and developing additional resources for states to further clarify quality at the element level; these resources can be found on the DaSy Center website.

2. Who are Part C and Part B 619 state staff or other state staff? To the extent possible, the quality indicators were written to identify who is expected to carry out the action described in the statement while also being sensitive to the variations in Part C and Part B 619 organization and administration across the states. Therefore, the actors identified in quality indicators and elements are somewhat open ended. When an indicator or element stipulates “Part C/619 state staff” or includes “other staff,” it refers to staff with knowledge of the program and generally refers to the state coordinators or other individuals in the state program office. When an action needs to be carried out specifically by state Part C/619 coordinators, they are identified specifically. When an action is carried out by state leadership this refers to state staff who have authority to make decisions and could include the Part C/619 coordinators, agency leadership, or other leaders.

3. What database applications are included? States have multiple database applications (i.e., a computer software program used to enter, store, organize, and retrieve data or information from a computerized database). States collect multiple types of data related to the implementation of IDEA, and these data may reside in different database applications (Derrington et al., 2013). For example, in many states, data on children reside in one database application whereas information about the personnel who work with them is in another. The information in the DaSy framework applies to every state dataset or application that contain data related to the implementation of IDEA Part C and Part B 619 programs. The phrase “data system” appears many times throughout the DaSy framework. In the interest of succinct communication, the DaSy framework uses “data system” rather than “data systems” or “data system(s).”

4. What are state Part C and Part B 619 data? State Part C/619 data are data related to the implementation of IDEA and encompass different types of data such as data about the children, their families, their services, the providers, and the programs, including the fiscal support for the programs, that serve the children and their families. Included are all the data required for IDEA reporting in the state performance plan/annual performance reports (SPP/APR), the data collections authorized under Section 618 of the IDEA, and other data the state collects about the program. As noted above, some of these data reside in different datasets or databases. Once data are included in the state Part C/619 data system, they are considered part of the Part C/619 state dataset and within the oversight of the state Part C or Part B 619 program, regardless of their origin (e.g., from the local programs or districts).

5. Does the framework apply to local data systems? The DaSy framework was written to identify the components of a high-quality state data system. It is intended to be used by states to examine their state data systems. Many of the quality indicators and elements could apply equally well at the local level, but they were not written or reviewed with local data systems in mind. Local programs are addressed explicitly in the Data Analysis and Use subcomponent because quality data are an essential feature of a good data system, and when data are used by those who provide the data, the quality of the data improves. In addition, the return on investment in collecting the data is maximized when data are used at multiple levels. Also as reflected in the Data Analysis and Use subcomponent, the DaSy framework sees the state as having an important role in supporting programs and districts to use data.

6. Does the framework apply to contractors or vendors? Many of the framework quality indicators and elements are directly applicable to vendors contracted to work with the Part C or Part B 619 program to design, develop, deploy, and/or maintain the database application and other data system functions. However, the framework does not address other important content between the program and vendor typically addressed in a signed contract (e.g., code ownership, transference of data from one vendor to another).