Open Data Plan Annual Update 2026

The Department prioritizes high-value public data assets based on public value, demand, release readiness, and applicable legal considerations. Initial priorities include foreign assistance and financial data, along with information supporting public understanding of departmental programs and services. The Department intends to expand and refine its inventory as additional data assets are validated and prepared for release. Potential performance measures include the number of qualifying public data assets published, the proportion of validated assets made accessible, and public usage of published datasets. These measures are inferred and are not established targets in the source.

The Department completed development and validation of EMS 2.0 in FY 2026, aligning departmental metadata requirements with DCAT-US 3.0. EMS 2.0 defines metadata fields, controlled vocabularies, and documentation requirements for data assets cataloged in the Enterprise Data Catalog. The Department is developing governance processes, policies, guidance, and training to support consistent application of open format standards. The Enterprise Data Catalog is intended to support automated metadata management, data steward workflows, and direct publication pipelines to Data.gov. The Department also seeks to standardize procurement terms and conditions to support the acquisition, collection, and submission of data in open formats. Potential performance measures include the proportion of published assets conforming to EMS 2.0 and DCAT-US 3.0, the number of assets with documented terms of use, and the proportion of applicable publication processes using standardized workflows. These are inferred measures, not source commitments.

The Department designs data collection mechanisms created after January 14, 2019, to collect data in open and machine-readable formats to the greatest extent practicable. Data.State and AI.State use open or industry-standard formats to support interoperability, reuse, and public dissemination. The Department prioritizes systems supporting open, non-proprietary data formats to improve portability, interoperability, and independence from individual vendors. Procurement terms and conditions are being standardized to require data collection, submission, and acquisition in formats supporting open data, consistent with federal acquisition regulations. The source distinguishes publicly available data from open data. Public availability alone does not necessarily establish unrestricted reuse rights. Potential performance measures include the percentage of qualifying public data assets available in machine-readable formats and the percentage available in open, non-proprietary formats. These measures are inferred rather than specified targets. Potential relationship to GSA's U.S. Strategy Data Fellowship: The Fellowship offers an opportunity to extend the Department's commitment to open, machine-readable formats to strategic plans and performance reports. StratML Part 1 (ISO 17469-1) and Part 2 (ANSI/AIIM 22:2017) could support interoperable publication and reuse of planning and performance information alongside other departmental data assets. https://stratml.us/docs/USSDF.xml Submitter's Note: Consistent with the good practice set forth in section 10 of the GPRA Modernization Act, plans like this should be published in an open, standard, machine-readable format like Strategy Markup Language, Part 1, Strategic Plans (ISO 17469-1).

The Department monitors non-government usage through the General Services Administration's Digital Analytics Program and supplements those observations with platform-level metrics. During the first nine months of FY 2026: • travel.state.gov received more than 184 million visits. • The monthly Visa Bulletin was downloaded more than 470,000 times. • Monthly immigrant visa issuance statistics reports were downloaded tens of thousands of times. • history.state.gov received more than 26 million visits. • allowances.state.gov received more than two million visits. The Department also disseminates financial data through USASpending.gov and the Federal Procurement Data System. These figures are approximate because of analytics sampling. Website visits and document downloads represent different measures and should not be combined as though they were equivalent. The Department will continue publishing updated usage information at least annually on https://www.state.gov/data. Usage patterns and public feedback received through Open.Data@state.gov will inform prioritization of future data asset releases. The historical usage figures provide potential baselines for a StratML Part 2 performance report, subject to verification of their measurement periods and definitions.

In FY 2026, the Department completed development and validation of Enterprise Metadata Schema (EMS 2.0), aligned with Data Catalog Vocabulary Version 3.0 (DCAT-US 3.0). EMS 2.0 establishes metadata fields, controlled vocabularies, and documentation requirements for data assets cataloged in the Enterprise Data Catalog. The schema supports interoperability with federal data infrastructure, including Data.gov. The Department has begun deploying Enterprise Data Catalog processes to streamline publication to Data.gov. The Department continues establishing and refining governance processes, policies, guidance, and training for consistent application of open format standards. Potential performance measures include the percentage of cataloged data assets conforming to EMS 2.0, the percentage with complete required metadata, and the number of validated assets published through automated catalog workflows. These are inferred measures, not formally stated targets.

The Department established Open.Data@state.gov as its primary public point of contact for data quality concerns, suggestions, and requests in FY 2026. Public feedback is considered alongside usage information when prioritizing future data asset releases. The Department engages external stakeholders through Data.gov, FA.gov, USASpending.gov, interagency working groups, and federal data communities. The source does not specify service-level targets for responding to inquiries or quantitative targets for stakeholder participation. Potential performance measures include the number of inquiries received, the percentage receiving responses, response times, and the number of publication priorities influenced by public feedback. These measures are inferred.

The Department is working with program offices to identify, validate, and catalog high-value datasets for public release. Priority data domains were selected based on concentrations of high-value, already-public assets and significant public interest. The source identifies foreign assistance, consular services, and financial transparency as areas of particular relevance. Data.State and AI.State provide enterprise data, analytics, and artificial intelligence capabilities supporting departmental data use. The Department intends to expand and refine its inventory as enterprise cataloging capabilities mature and additional assets are validated for release. Potential performance measures include the number of datasets reused across organizational boundaries, the number of departmental programs using shared data assets, and documented external applications of departmental open data. These measures are inferred. Potential relationship to StratML: Machine-readable goals and objectives could provide additional context for discovering data assets relevant to organizational priorities. Linking open data catalogs with StratML plans and performance reports could support discovery and matching of stakeholders pursuing related objectives. This is an inferred opportunity, not a commitment in the Department's source plan. https://stratml.us/docs/USSDF.xml Potential relationship to GSA's U.S. Strategy Data Fellowship: The Department could collaborate with the Fellowship and other participating agencies to demonstrate how open data assets can be linked to machine-readable goals, objectives, stakeholders, and performance indicators. Such demonstrations could facilitate cross-agency discovery, comparison, coordination, and reuse of data in support of shared objectives. Potential international extension: The Department of State could engage allied and partner governments in extending GSA's U.S. Strategy Data Fellowship initiative to support international interoperability of strategic plans and performance reports. Voluntary adoption of StratML could facilitate discovery of shared objectives, identification of prospective collaborators, coordination of activities, and comparison of reported results across national boundaries. This is an inferred opportunity, not a commitment in the Department's source plan.

The Department's stated commitment encompasses strategic, operational, and foreign policy decisions. The Department has validated an inventory of high-value public data assets across four priority data domains and established a framework for prioritizing open data releases. The source does not identify specific foreign policy decisions or operational outcomes attributable to use of these assets. Potential performance measures include the number of strategies and operational decisions supported by documented data analysis. This measure is inferred, not an established target. Potential relationship to StratML: Associating evidence sources with documented strategic objectives could improve traceability between information, decisions, and intended results. Potential relationship to GSA's U.S. Strategy Data Fellowship: The Fellowship offers an opportunity to demonstrate how data-informed policymaking can be supported by machine-readable strategic plans and performance reports. https://stratml.us/docs/USSDF.xml Linking departmental data assets and analytical evidence to explicit objectives and reported results could improve transparency, accountability, and evaluation of policy effectiveness. This opportunity is inferred and is not a commitment documented in the Department's source plan. Submitter's Note: Consistent with the good practice set forth in section 10 of the GPRA Modernization Act, strategic plans and performance reports should be published in an open, standard, machine-readable format like StratML. Moreover, a case can be made that we have far too much "policy" in unstructured, narrative formats and far too few performance plans in open, standard, machine-readable format.

Data.State and AI.State provide enterprise data, analytics, and artificial intelligence capabilities.The Department is investing in infrastructure, training, staffing, and procurement practices to advance open data goals. Training and technical support for data stewards include catalog entry, metadata standards, and open data designation criteria.The source does not specify decision-support adoption targets or quantified improvements in decision quality. Potential performance measures include personnel trained in relevant data practices and documented improvements in decision processes. These measures are inferred. Potential relationship to StratML: Published machine-readable plans and performance reports could help decision-makers discover relevant objectives, data assets, responsible stakeholders, and reported results.

The Department commits to protecting sensitive information while expanding access to qualifying public data assets. The plan identifies national security and individual privacy as considerations that must be balanced against transparency and public access. The source does not prescribe particular technical safeguards, review procedures, or quantitative compliance thresholds for this objective. Potential performance measures include the percentage of applicable data assets receiving documented security and privacy reviews before publication and the number of identified vulnerabilities or disclosure concerns resolved. These measures are inferred. Potential relationship to StratML: Machine-readable performance plans could document responsibilities and measurable objectives for safeguarding information. Public reporting should avoid exposing protected information, security-sensitive procedures, or details that could increase disclosure risks. This is an inferred opportunity rather than a stated Department commitment.

The Department will continue assessing opportunities to enhance data disclosure practices, including exploring risk-based approaches. The Department prioritizes public data assets for review based on public value, demand, release readiness, and applicable legal considerations. In FY 2026, the Department reviewed its existing public data inventory to assess the currency and accuracy of previously listed assets. The Department is rebuilding its catalog using validated, high-quality entries and intends to expand the inventory as additional assets are prepared for release. The source does not establish a specific risk assessment methodology, risk tolerance, or implementation deadline for enhanced disclosure practices. Potential performance measures include the number of data assets assessed for release, the percentage of assessed assets approved for publication, and the number of additional assets made available following appropriate risk mitigation. These measures are inferred. Potential relationship to StratML: Documenting disclosure policies, objectives, responsibilities, and performance measures in machine-readable formats could improve accountability and support comparisons of practices across federal agencies. This is an inferred opportunity, not a commitment made in the Department's plan.