Back to Apply Breadcrumb Home Apply Goal #6: Strengthen Data Systems Essential Questions The E-W Framework can help you establish priorities for data collection and use - that is, what do you want your data system to help you accomplish? Refer to our Essential Questions Guide for support. Example California’s Cradle-to-Career Data System exemplifies an equity-centered approach to designing and developing a new E-W data system. The new data system will inform six critical areas of inquiry identified by the California Cradle-to-Career Data System Act, answering key questions for policymakers, families, and students. Indicators Once you've identified your key questions, you can use the E-W Framework to identify what data to collect, and understand how to strengthen data practices to guide action. You might choose to:Strengthen data systems by tracking and reporting well-established indicators. Refer to our Indicator Readiness Brief for more information on which indicators and metrics are most well-established and ready for adoption in existing state and local data systems.Map existing data to the framework’s recommended indicators and metrics. Download our E-W Framework indicators and metrics spreadsheet tool and use it as a checklist to identify which indicators and metrics your organization is already collecting. Example The District of Columbia’s Office of Education Through Employment Pathways used the E-W Framework as a resource to initiate and guide discussions about what types of data are possible to collect, thinking beyond common accountability-focused outcome indicators to more expansive indicators of neighborhood context and system supports. Disaggregates When collecting and reporting data, be sure to disaggregate data to understand how trends and patterns differ by group. Refer to the framework's recommended Disaggregates for guidance. Example ImpactTulsa partnered with Tulsa Public Schools to build a data visualization tool for exploring how environmental conditions vary across neighborhoods and their relationships to academic outcomes. Users can explore data by race/ethnicity, gender, homeless status, and more. Example Equitable Data Practices As appropriate, securely share data with partners to reduce the burden of duplicate data collection (Data Equity Principle 1).Communicate data privacy and security processes when collecting data. Seek informed consent even if not required. Only collect data that are necessary and have been approved (Data Equity Principle 2).Work with community members to determine which characteristics to measure during data collection or to link into the data (if available), and how to label these characteristics in data collection and reporting (for example, Hispanic, Latino/a, Latinx) (Data Equity Principle 3).Establish inclusive data governance structures to develop guidelines and protocols for data collection, linking, and use (Data Equity Principle 8). External ResourcesDeciding what to measure and how to measure it is only part of the puzzle, and there are many partners in the field who offer additional tools to help you with data modernization efforts. Explore the resources below for guidance on how to develop infrastructure (such as state longitudinal data systems) or understand legal requirements (such as data sharing agreements).Data Integration Support Center. Developed by WestEd, this collection of resources provides a variety of quick reads, videos, and in-depth resources to support education-to-workforce (also known as P20W+) data integration efforts.State Information Request: Establishing a Statewide Longitudinal Data System. Developed by the Education Commission of the States, this resource contains an overview of how states establish their statewide longitudinal data systems and examples of how these systems can be effectively used.Getting the Facts Straight About Statewide Longitudinal Data Systems (SLDS). Developed by the Data Quality Campaign (DQC), this resource explores common myths about linking data within SLDSs. Explore DQC’s Resources page for additional tools—such as fact sheets, research reports, and infographics—for advancing the effective use of education data.Statewide Longitudinal Data Systems (SLDS) Grant Program Publications. The National Center for Education Statistics’ SLDS team produces various types of products to capture best practices from the field and meet the evolving needs of the community. This page includes best practices, guides, issue briefs, state spotlights, and target team publications. States can also request customized technical assistance from the SLDS State Support Team.Community of Innovation (COI) Map. Developed by the P20W+ COI, this map seeks to support anyone stewarding and advancing critical data systems from early childhood through workforce. Resources are organized by role and by type of work (such as planning, governance, infrastructure, privacy, and data use) to help you along your path.