The purpose of this agreement is for SSA to verify the SSNs and other identifying information, and confirm citizenship information to the Defense Manpower Data Center (DMDC) of the Department of Defense. DMDC will use the data provided by SSA to validate the identity of individuals entering or serving in the Armed Forces and to identify potential enlistees and members of the military who are aliens or non-citizens.

This document is the Project Charter for the Federated Data Search Pilot Project between the Treasury Board of Canada Secretariat and the Government of Alberta’s Open Government Program. It acts as both a guiding document in terms of the expectations and responsibilities for each member of the Project Team as well as a reference document for the project and the Canada Open Government Working Group

DCAT is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web. This document defines the schema and provides examples for its use.

DCAT enables a publisher to describe datasets and data services in a catalog using a standard model and vocabulary that facilitates the consumption and aggregation of metadata from multiple catalogs. This can increase the discoverability of datasets and data services. It also makes it possible to have a decentralized approach to publishing data catalogs and makes federated search for datasets across catalogs in multiple sites possible using the same query mechanism and structure. Aggregated DCAT metadata can serve as a manifest file as part of the digital preservation process.

• Homepage: https://www.w3.org/TR/vocab-dcat-2
• Namespace: http://www.w3.org/ns/dcat# (alias dcat)
• Version: 2.0

This dataset includes information about state agencies publishing data on the CT Open Data Portal, including number of datasets, maps, external datasets (href), federated datasets (federated href), and data stories. It also includes a summary of the freshness of the data and the completeness of the metadata by agency.

The FederGob extension for CKAN facilitates the federation of CKAN-based data portals with Datos.gob.es, the official data catalog of Spain. Primarily designed to adapt CKAN's metadata output to meet the specific requirements for federation outlined by Datos.gob.es, FederGob streamlines the integration process, thereby ensuring compliance with the Norma Técnica de Interoperabilidad de Reutilización de Recursos de Información (NTI). This extension uses RDF as its metadata representation format. Key Features: RDF Metadata Transformation: Adapts CKAN's default DCAT RDF/XML metadata output to match the requirements specified in Annex I of the Federador user manual for Datos.gob.es. Portal Metadata Generation: Creates metadata specifically for the CKAN portal itself, which is essential for completing the federation process with Datos.gob.es. Automated Metadata Generation: Includes scripts to automate the periodic generation of metadata, helping to keep the federated data consistent and up-to-date. Uses cron to automatically update on a daily basis. Configuration Script: Provides a config.py script to easily set configurations like URL for datasets, catalog language settings, catalog title, detailed descriptions, and the date the catalog was created. Allows easy setup for creating metadata that will be transferred. Compatibility: Compatible with CKAN 2.0 and above. Technical Integration: FederGob operates by modifying the RDF/XML metadata generated by CKAN, adjusting it to fit the specifications of the Datos.gob.es federation process. The extension requires configuration within the CKAN environment, setting parameters for the catalog URL, dataset URL, language, title, description, issued date, publisher URL, and license URL. It also depends on cron for scheduling updates. Prerequisites:

The federated-index extension for CKAN allows the creation of a lightweight data aggregator by enabling the indexing of datasets from remote CKAN portals. It does this by storing relevant dataset metadata locally, enabling search functionality, and then redirecting users to the original CKAN instance when accessing the dataset details. This approach permits users to discover and access data from multiple CKAN instances from a single point without replicating the datasets themselves locally. Key Features: Federated Indexing: Indexes remote datasets, making them searchable within the local CKAN instance, but avoids creating local copies of the entire dataset. It creates references to the remote datasets within the local CKAN instance. Profile-Based Configuration: Manages remote CKAN portal configurations using profiles that define the remote portal URL, optional API key, and other relevant settings, allowing for easy management of multiple federated data sources. Redirection to Source: Redirects users to the original portal's dataset page when they click on a federated dataset, ensuring they access the most up-to-date information and related resources hosted on the source portal. Metadata Schema Alignment: Offers options to align the metadata schema of indexed datasets with the local CKAN instance, either by dropping fields or by allowing custom modifications via the IFederatedIndex interface. Incremental Updates: Supports fetching only the datasets that have been updated since the last synchronization, optimizing the indexing process for large and frequently updated remote portals with the since_last_refresh flag in federated_index_profile_refresh action. Customizable Search Payloads: Allows customization of the package_search API calls used to fetch data from remote portals, enabling filtering and pagination of datasets based on specific criteria through Search payloads. Multiple Data Storage Options: Supports various storage backends for storing remote dataset metadata, including a database table (default), the filesystem, Redis, and SQLite allowing users to select the most suitable option based on their needs and infrastructure. Configuration Options: Provides configuration options for redirection behavior, index URL field, the index profile field, and request timeout for remote portal requests. Also, options to remove fields from a dataset not defined in a local schema or redirect the user to the original dataset URL. Technical Integration: The federated-index extension integrates with CKAN via plugins and configuration settings. Profiles are configured in the CKAN configuration file, defining parameters such as the remote portal URL and API key. The extension introduces a new CKAN API action, federated_index_profile_refresh, to trigger the indexing process. The IFederatedIndex interface allows developers to hook into the indexing process and modify dataset dictionaries before they are indexed. Benefits & Impact: The federated-index extension offers a simple way to aggregate metadata from multiple CKAN instances without the overhead of replicating entire datasets. It simplifies the discovery of data across different portals and can reduce the storage requirements of aggregator CKAN instances. By redirecting users to the original data sources, it helps to maintain data integrity and ensures that users always access the most current information.

Shoreline of the Federated States of Micronesia

Data.public.lu provides all its metadata in the DCAT and DCAT-AP formats, i.e. all data about the data stored or referenced on data.public.lu. DCAT (Data Catalog Vocabulary) is a specification designed to facilitate interoperability between data catalogs published on the Web. This specification has been extended via the DCAT-AP (DCAT Application Profile for data portals in Europe) standard, specifically for data portals in Europe. The serialisation of those vocabularies is mainly done in RDF (Resource Description Framework). The implementation of data.public.lu is based on the one of the open source udata platform. This API enables the federation of multiple Data portals together, for example, all the datasets published on data.public.lu are also published on data.europa.eu. The DCAT API from data.public.lu is used by the european data portal to federate its metadata. The DCAT standard is thus very important to guarantee the interoperability between all data portals in Europe. Usage Full catalog You can find here a few examples using the curl command line tool: To get all the metadata from the whole catalog hosted on data.public.lu curl https://data.public.lu/catalog.rdf Metadata for an organization To get the metadata of a specific organization, you need first to find its ID. The ID of an organization is the last part of its URL. For the organization "Open data Lëtzebuerg" its URL is https://data.public.lu/fr/organizations/open-data-letzebuerg/ and its ID is open-data-letzebuerg. To get all the metadata for a given organization, we need to call the following URL, where {id} has been replaced by the correct ID: https://data.public.lu/api/1/organizations/{id}/catalog.rdf Example: curl https://data.public.lu/api/1/organizations/open-data-letzebuerg/catalog.rdf Metadata for a dataset To get the metadata of a specific dataset, you need first to find its ID. The ID of dataset is the last part of its URL. For the dataset "Digital accessibility monitoring report - 2020-2021" its URL is https://data.public.lu/fr/datasets/digital-accessibility-monitoring-report-2020-2021/ and its ID is digital-accessibility-monitoring-report-2020-2021. To get all the metadata for a given dataset, we need to call the following URL, where {id} has been replaced by the correct ID: https://data.public.lu/api/1/datasets/{id}/rdf Example: curl https://data.public.lu/api/1/datasets/digital-accessibility-monitoring-report-2020-2021/rdf Compatibility with DCAT-AP 2.1.1 The DCAT-AP standard is in constant evolution, so the compatibility of the implementation should be regularly compared with the standard and adapted accordingly. In May 2023, we have done this comparison, and the result is available in the resources below (see document named 'udata 6 dcat-ap implementation status"). In the DCAT-AP model, classes and properties have a priority level which should be respected in every implementation: mandatory, recommended and optional. Our goal is to implement all mandatory classes and properties, and if possible implement all recommended classes and properties which make sense in the context of our open data portal.

Vegetation of the Federated States of Micronesia, compiled from individual files for Chuuk, Kosrae, Pohnpei and Yap.

Areas of Biological Significance in the Federated States of Micronesia

Reef Conservation Target Areas in the Federated States of Micronesia

Soil cores were collected in mangrove forests across Pohnpei, Federated States of Micronesia to understand spatial variation in accretion rates. Cores were dated using lead-210 and processed for bulk density and organic matter percent through loss-on-ignition analysis. A total of 30 cores were successfully dated across seven regions around the island.

Protected and managed areas of the Federated States of Micronesia.

Almendralejo City Council Data Catalog in RDF/XML format based on the DCAT Vocabulary (http://www.w3.org/ns/dcat#), developed by the World Wide Web Consortium (W3C) and which allows standardization in the definition of document catalogs and Information resources. A catalog of documents and information resources is represented by instances of the dcat:Catalog class and includes a collection of dcat:Dataset information resource sets. Using the download URL (http://datos.almendralejo.albasmart.es/dcat) you can federate the catalogue in the Open Data initiative of the Government of Spain (http://datos.gob.es/) and through it in the European Data Portal (https://www.europeandataportal.eu/)

Surface elevation of the mangrove forest is important for understanding current and future vulnerability to sea-level rise. Due to the lack of LiDAR data and insufficient accuracy of space-borne synthetic aperture radar-derived elevation models, we leveraged data from differential leveling surveys to generate a digital elevation model (DEM) for the mangrove forest of Pohnpei. We created a general slope model with a shore-normal transect of elevation and a general additive model (GAM) spine. To create a continuous DEM, the GAM spline was then stretched across a grid representing the width of mangrove, created using digitized boundaries of the seaward and interior mangrove edge. This simplified approach assumes that the relationship between slope and width of the mangrove forest is constant. This DEM should be considered an intermediate product until a higher quality DEM is made available.

Platform hosting datasets for public administration and private enterprises, providing a single point of access to regional data. The catalog is federated with national and European portals. Most datasets are licensed under CC-BY and reusable even for commercial purposes. About 1400 datasets published.

Mangrove species dominance on Pohnpei island, Federated States of Micronesia was modeled with two geospatial model types: k-nearest neighbor (KNN) and random forest (RF) and a common set of predictors. Dominant mangroves were defined as species comprising the largest basal area per field plot. The KNN model produced one map, which shows all species' dominance locations in one raster layer. The KNN model results were the best based on field data and in field knowledge of the area. The KNN RStudio model and resulting map are shared here.

Center for Mental Health Services (CMHS) Uniform Reporting System (URS) Output Tables for 2012. The Uniform Reporting System (URS) is a state and national reporting system collected annually to support the Community Mental Health Services Block Grant program. State Mental Health Authorities report on National Outcome Measures (NOMS), evidence based practices, and utilization measures providing an overview of state mental health delivery systems.

Landslides hazards pose a serious threat to people and infrastructure in the Federated States of Micronesia (FSM). To develop a comprehensive understanding of the landslides hazards in FSM, the USGS-USAID Landslide Disaster Assistance Team (LDAT) has put together landslide inventories for each state using satellite imagery. Mapping was done using RGB satellite imagery from Maxar, Planet Labs, and Google Earth. This inventory is for Kosrae state and covers all available imagery between January 2005 and October 2023. Landslides are dated by a window of occurrence based on the last images before and first image after the occurrence of the landslide. Each event was mapped using a point at the center of the headscarp (points_Kos), and, when possible, affected area polygons (area_Kos), runout lines (runout_Kos), and headscarp lines (headscarp_Kos). Due to the dense vegetation, frequent cloud cover, and poor spatial and temporal resolution of available imagery, it was difficult to map headscarps and runouts for every event. However, headscarp width and runout distance are mapped where possible. The attribute table for points_Kos, contains a visual-based classification of the land use and vegetation, as well as if the event affected streams, buildings, or utilities (for example, roads). Each event is also labeled with a level of confidence for occurrence and _location. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

State boundaries of the Federated States of Micronesia (FSM), delimiting the states of Yap, Chuuk, and Kosrae. These are approximated from the map image on Wikipedia at: http://en.wikipedia.org/wiki/File:Map_of_the_Federated_States_of_Micronesia_CIA.jpg