AndreaBozzo/ceres-open-data-index huggingface dataset:
Top 25 Ports by Dry Bulk Tonnage

The Top 25 Ports by Dry Bulk Tonnage section highlights the critical hubs for moving non-liquid, unpackaged commodities like grain, coal, iron ore, and fertilizer.

Unlike container ports, which are dominated by the West and East Coasts, dry bulk tonnage is heavily concentrated in the Gulf Coast and Great Lakes regions, where the U.S. interior connects to global markets.

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### 🔗 Related Datasets

- [Top 10 Containerized Export Non-Durable Commodities in Short Tons by Coast, 2023](https://odgavaprod.ogopendata.com//dataset/fd1ab7d5-9a34-499f-84a0-a6122c7187e6) — *U.S Department of Transportation*
- [Top 10 Containerized Non-Durable Import Commodities by Value and Coast 2023](https://odgavaprod.ogopendata.com//dataset/ced2319b-97ce-45d8-afcc-e19953e61ee4) — *U.S Department of Transportation*
- [Top 10 Containerized Export Commodities in Short Tons by Coast, 2023](https://odgavaprod.ogopendata.com//dataset/97704209-1b13-40cb-ab4e-e9b645234fe7) — *U.S Department of Transportation*
- [Top 10 Containerized Export Commodities by Value and Coast 2023](https://odgavaprod.ogopendata.com//dataset/fd3ddbb4-382c-4fb7-8ee0-0153512b8446) — *U.S Department of Transportation*
- [Top 10 Containerized Import Commodities by Shipping Weight (short tons) and Coast 2023](https://odgavaprod.ogopendata.com//dataset/137ef502-266b-4850-8d40-ce23364ea69c) — *U.S Department of Transportation*

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Product Data for Newly Reported Drugs in the Medicaid Drug Rebate Program 06-08-2026 to 06-14-2026

The data below contains newly reported, active covered outpatient drugs which were reported by participating drug manufacturers since the last quarterly update of the Drug Products in the Medicaid Drug Rebate Program (MDRP) database.

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### 🔗 Related Datasets

- [Product Data for Newly Reported Drugs in the Medicaid Drug Rebate Program 06-01-2026 to 06-07-2026](https://odgavaprod.ogopendata.com//dataset/c19cca9e-e6fd-4524-aeaf-544ff7a4024c) — *HealthData.Gov*
- [Product Data for Newly Reported Drugs in the Medicaid Drug Rebate Program 04-06-2026 to 04-12-2026](https://odgavaprod.ogopendata.com//dataset/afa0b5b1-ea30-4b36-948a-e5bb445044d2) — *HealthData.Gov*
- [Product Data for Newly Reported Drugs in the Medicaid Drug Rebate Program 05-18-2026 to 05-24-2026](https://odgavaprod.ogopendata.com//dataset/60cf4bf6-5b0d-4d40-8af9-2d924d2bfd46) — *HealthData.Gov*
- [Product Data for Newly Reported Drugs in the Medicaid Drug Rebate Program 01-05-2026-to-01-11-2026](https://odgavaprod.ogopendata.com//dataset/a6124dcb-cffa-4a72-ba2f-6000817d8831) — *HealthData.Gov*
- [Product Data for Newly Reported Drugs in the Medicaid Drug Rebate Program 03-30-2026 to 04-05-2026](https://odgavaprod.ogopendata.com//dataset/6dbe1228-54d0-4a98-ad3a-d24fa65c709c) — *HealthData.Gov*

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CDC Text Corpora for Learners: HTML Mirrors of MMWR, EID, and PCD

The attached ZIP archives are part of the <a href="https://github.com/cmheilig/harvest-cdc-journals">CDC Text Corpora for Learners</a> program. This version, comprised of 33,567 articles, was constructed on 2024-03-01 using source content retrieved on 2024-01-09. 

The attached three ZIP archives contain the 33,567  articles in 33,576 compiled HTML mirrors of the MMWR <a href="https://www.cdc.gov/mmwr/">Morbidity and Mortality Weekly Report</a> including its series: <i>Weekly Reports</i>, <i>Recommendations and Reports</i>, <i>Surveillance Summaries</i>, <i>Supplements</i>, and <i>Notifiable Diseases</i>, a subset of <i>Weekly Reports</i>, constructed ad hoc; EID <a href="https://www.cdc.gov/eid/">Emerging Infectious Diseases</a>; and PCD <a href="https://www.cdc.gov/pcd/">Preventing Chronic Disease</a>.There is one archive per series. The archive attachments are located in the <i>About this Dataset</i> section of this landing page. In that section when you click Show More, the attachments are located in the section <i>Attachments</i>.

The retrieval and organization of the files included making as few changes to raw sources as possible, to support as many downstream uses as possible.
BTS ATRI Freight Mobility Initiative: County-to-county truck travel times (2019) - Experimental

Experimental estimates of the travel times experienced by a sample of freight trucks observed moving between all county pairs in the United States over the course of calendar year 2019.

Estimated by parsing GPS pings collected from a sample of approximately 300,000 trucks as part of the BTS ATRI Freight Mobility Initiative, these travel times were estimated (1) using the amount of elapsed time between the times that a truck was observed sequentially departing and arriving in each named county pair and (2) calculating 25th, 50th, and 75th travel times for all trucks observed moving between those counties over the course of 2019.
Jan_Mar_2022_Part234

January - March 2022

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### 🔗 Related Datasets

- [World](https://odgavaprod.ogopendata.com//dataset/ba0d030b-380e-479c-a4a5-705982eaa6e1) — *U.S Department of Transportation*
- [NS](https://odgavaprod.ogopendata.com//dataset/9386fd64-40e3-419c-a4d9-b4b83b4badad) — *U.S Department of Transportation*
- [UP](https://odgavaprod.ogopendata.com//dataset/af056953-9c1c-44ff-8630-8f2927f199f7) — *U.S Department of Transportation*
- [2020 PM](https://odgavaprod.ogopendata.com//dataset/f56cc51f-86da-4543-83cf-5e5cdc0203e5) — *U.S Department of Transportation*
- [Continent](https://odgavaprod.ogopendata.com//dataset/99413688-420d-49d9-a96a-f91af9608f8a) — *U.S Department of Transportation*

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Monthly TEU Data

2022 Monthly TEU Data

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### 🔗 Related Datasets

- [Product Data for Newly Reported Drugs in the Medicaid Drug Rebate Program 11-17-2025-to-11-23-2025](https://odgavaprod.ogopendata.com//dataset/af137106-8b73-482e-a532-a46bb0963d18) — *HealthData.Gov*

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CDC Text Corpora for Learners: MMWR, EID, and PCD Article Metadata

This landing page is part of the <a href="https://github.com/cmheilig/harvest-cdc-journals">CDC Text Corpora for Learners</a> program; this includes the compiled 33,576 CDC Text for Learners <a href="https://data.cdc.gov/National-Center-for-State-Tribal-Local-and-Territo/CDC-Text-Corpora-for-Learners-HTML-Mirrors-of-MMWR/ut5n-bmc3/about_data">HTML mirrors</a> of the MMWR <a href="https://www.cdc.gov/mmwr/">Morbidity and Mortality Weekly Report</a> including its series: <i>Weekly Reports</i>, <i>Recommendations and Reports</i>, <i>Surveillance Summaries</i>, <i>Supplements</i>, and <i>Notifiable Diseases</i>, a subset of <i>Weekly Reports</i>, constructed ad hoc; EID <a href="https://www.cdc.gov/eid/">Emerging Infectious Diseases</a>; and PCD <a href="https://www.cdc.gov/pcd/">Preventing Chronic Disease</a>

The data represented here is the tabulated <a href="https://github.com/cmheilig/harvest-cdc-journals/blob/main/README.md#metadata-fields">metadata</a> of the combined 33,567 articles of the  <a href="https://github.com/cmheilig/harvest-cdc-journals?tab=readme-ov-file#collections">MMWR, EID, and PCD collections</a> whose contents are organized into three ZIP archived JSON files per collection. The JSON value output formats include UTF-8 HTML, UTF-8 markdown, and ASCII plain text.

The <a href="https://github.com/cmheilig/harvest-cdc-journals?tab=readme-ov-file#collections">JSON files</a> are located in the <a href="https://github.com/cmheilig/harvest-cdc-journals">program's repository.</a> This version was constructed on 2024-03-01 using source content retrieved on 2024-01-09.
Weekly Number of Container Ships Awaiting to Dock at All U.S. Ports: July 2021 to September 2023

This metric represents the "queue" or "waiting room" for U.S. trade. The Weekly Number of Container Ships Awaiting to Dock is a primary indicator of supply chain health and port congestion.

From July 2021 to September 2023, the U.S. experienced a dramatic arc: moving from historic backlogs that gripped the global economy to a near-total clearing of the queues by late 2023.

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### 🔗 Related Datasets

- [Monthly Average Container Vessel Dwell Times at the Top 25 U.S. Container Ports January 2019 to June 2023](https://odgavaprod.ogopendata.com//dataset/dfa52701-ab25-460f-b3db-01f3520a77d5) — *U.S Department of Transportation*
- [Monthly TEU Capacity of Container Ships Calling at U.S. Ports January 2020 to September 2023](https://odgavaprod.ogopendata.com//dataset/ddc67e15-defc-406b-b992-3c7d4df24bda) — *U.S Department of Transportation*

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Annual Passenger Border Crossings with Michigan & New York

This data is reported by each respective bridge crossing management authority for a combined total of both directions of travel for border crossings to Canada from Michigan and New York.

<!-- SIMILAR_DATASETS_START -->
---
### 🔗 Related Datasets

- [Product Data for Newly Reported Drugs in the Medicaid Drug Rebate Program 11-17-2025-to-11-23-2025](https://odgavaprod.ogopendata.com//dataset/af137106-8b73-482e-a532-a46bb0963d18) — *HealthData.Gov*

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BTS ATRI Freight Mobility Initiative: County-to-county truck travel times (2020) - Experimental

Experimental estimates of the travel times experienced by a sample of freight trucks observed moving between all county pairs in the United States over the course of calendar year 2020.

Estimated by parsing GPS pings collected from a sample of approximately 300,000 trucks as part of the BTS ATRI Freight Mobility Initiative, these travel times were estimated (1) using the amount of elapsed time between the times that a truck was observed sequentially departing and arriving in each named county pair and (2) calculating 25th, 50th, and 75th travel times for all trucks observed moving between those counties over the course of 2020.
BTS ATRI Freight Mobility Initiative: County-to-county truck travel times (2018) - Experimental

Experimental estimates of the travel times experienced by a sample of freight trucks observed moving between all county pairs in the United States between October and December 2018 (three months).

Estimated by parsing GPS pings collected from a sample of approximately 300,000 trucks as part of the BTS ATRI Freight Mobility Initiative, these travel times were estimated (1) using the amount of elapsed time between the times that a truck was observed sequentially departing and arriving in each named county pair and (2) calculating 25th, 50th, and 75th travel times for all trucks observed moving between those counties over the last three months of 2018 (October to December).
NHCCI

The National Highway Construction Cost Index (NHCCI) is a price index that can be used both to track price changes associated with highway construction costs, and to convert current dollar expenditures on highway construction to real or constant dollar expenditures. This dataset contains the quarterly NHCCI estimates as well as the Seasonally Adjusted NHCCI and Component Contributions to Changes in NHCCI.

Visit https://www.fhwa.dot.gov/policy/otps/nhcci/ for more information regarding the NHCCI.
BTS ATRI Freight Mobility Initiative: County-to-county truck travel time (2022) - Experimental

Experimental estimates of the travel times experienced by a sample of freight trucks observed moving between all county pairs in the United States over the course of calendar year 2022.

Estimated by parsing GPS pings collected from a sample of approximately 300,000 trucks as part of the BTS ATRI Freight Mobility Initiative, these travel times were estimated (1) using the amount of elapsed time between the times that a truck was observed sequentially departing and arriving in each named county pair and (2) calculating 25th, 50th, and 75th travel times for all trucks observed moving between those counties over the course of 2022.
Coastal Avian Protection Zones (CAPZ)

The CAPZ (Coastal Avian Protection Zones) layer was created to allow small renewable energy project applicants to identify areas that are critically important to coastal avian resources.  Utilized in concert with guidance documents for solar and wind projects, CAPZ can help guide pre-construction field surveys and aid in the development of mitigation plans designed to offset significant adverse impacts to wildlife in these sensitive areas.: https://gaia.vcu.edu/GemsMap/
VWP SSWD Boundaries

<p>Work impacting state surface waters may require a VWP permit in accordance with VWP program regulations and State Water Control Law. A complete application for a VWP permit requires a State Surface Waters Determination (SSWD) that maps the location of state surface waters within a project site as approved by DEQ through the SSWD process. This layer represents the boundaries of active VWP State Surface Waters Determinations (SSWDs) issued across the state.</p><p><br /></p><p><a href='https://gisdata.deq.virginia.gov/mapper_ext/DataFactSheets/Water_Permitting/SSWDPolygons_VWP_DEQFactSheet.pdf' target='_blank' rel='nofollow ugc noopener noreferrer'>Data Fact Sheet</a></p>
Estuarine Waters / Estuaries

This is a reference dataset for the Virginia Water Quality Standards for the tidal waters, represented as polygons, within the Virginia state boundary. See section 9VAC-25-260 of the Virginia Administrative Code for specific standards descriptions.<div><br /></div><div><a href='https://gisdata.deq.virginia.gov/mapper_ext/DataFactSheets/Water_Watersheds/DEQFactSheetV1_WQSestuaries.pdf' target='_blank' rel='nofollow ugc noopener noreferrer'>Click Here</a> to view Data Fact Sheet. </div>
Sec 130 Development Atlas

<p><span style='font-family:&quot;Segoe UI&quot;, Arial, sans-serif; font-size:16px;'>The Virginia Renewable Energy Development Atlas (REDA) is planning-level spatial data locating the Commonwealth's renewable energy permit locations. This dataset contains point addresses for renewable energy Section 130 de minimis permit sites authorized by DEQ. All actively permitted renewable energy permits, including facilities that have not been constructed and facilities that have not commenced commercial operation are included. Dataset updated intermittently on an as needed basis. </span></p><p><span style='font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:16px;'>Data contained within the Renewable Energy Development Atlas is not reflective of existing or future land disturbance. An up-to-date review of existing land disturbance as a result of utility-scale solar development across the Commonwealth can be viewed </span><a href='https://energy.virginia.gov/renewable-energy/documents/Re-Evaluating%20Land%20Use%20Impacts%20of%20Utility-Scale%20Solar%20-%20FINAL.pdf' style='color:rgb(0, 97, 155); text-decoration-line:none; font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:16px;' target='_blank' rel='nofollow ugc noopener noreferrer'>here</a><span style='font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:16px;'>.</span></p><p><a href='https://gisdata.deq.virginia.gov/mapper_ext/DataFactSheets/Renewable_Energy/DEQFactSheetV2_REDA.pdf' target='_blank' rel='nofollow ugc noopener noreferrer'>DEQ Data Fact Sheet</a></p>
2018 Final WQA Monitoring Stations

Sites within Virginia where DEQ or other data providers have collected water column, sediment, fish tissue or benthic macroinvertebrate samples within the given assessment data window (2018). Attributes assigned to each station are summarized based on samples collected per station ID. QA/QC checks are performed on the database to verify attribute and spatial accuracy, however errors may still occur.  Please direct any questions about attribute accuracy to the Data Distributor. The geospatial product is maintained and updated by VA DEQ each assessment cycle (biennially) using the most current data provided. Stations not monitored within the given data window may be included for clarification of assessment unit ID status but have no data within the parameter columns. See the Comments fields for those instances. Please see dateset Fact Sheet (on DEQ's Environmental Data Hub: https://geohub-vadeq.hub.arcgis.com/pages/water-datasets ) for metadata including contact information, process steps, attribute descriptions, and distribution information.<div><br /></div><div><a href='https://gisdata.deq.virginia.gov/mapper_ext/DataFactSheets/Water_Watersheds/2018_IR_AssessmentStations.docx' target='_blank' rel='nofollow ugc noopener noreferrer'>Click Here</a> to view Data Fact Sheet. </div>
Low Income Communities

<p>This dataset represents the geospatial extent as polygons and the corresponding attribution for census block groups that meet the definition of low-income communities according to the Virginia 2020 Environmental Justice Act: “Low-income community” definition: “’Low-income community’ means any census block group in which 30 percent or more of the population is composed of people with low income.” The referenced “low income” definition is also provided below: “Low income” definition: “’Low income’ means having an annual household income equal to or less than the greater of (i) an amount equal to 80 percent of the median income of the area in which the household is located, as reported by the Department of Housing and Urban Development, and (ii) 200 percent of the Federal Poverty Level.”</p><p><a target='_blank' href='https://gisdata.deq.virginia.gov/mapper_ext/DataFactSheets/Environmental_Justice/DEQFactSheet_EJ_Low_Income_Communities.pdf' rel='nofollow ugc noopener noreferrer'>Click Here</a>&nbsp;to view Data Fact Sheet.&nbsp;</p>
Renewable Energy Development Atlas

<p><span style='font-family:&quot;Segoe UI&quot;; font-size:12pt;'><span style='background-attachment:initial; background-clip:initial; background-image:initial; background-origin:initial; background-position:initial; background-repeat:initial; background-size:initial;'>The Virginia Renewable Energy Development Atlas (REDA) is planning-level spatial data locating the Commonwealth's renewable energy permit boundaries. This dataset contains polygons for renewable energy sites, excluding section 130 de minimis permits, authorized by DEQ or a Certificate of Public Convenience and Necessity (CPCN) issued by the </span></span><a href='https://www.scc.virginia.gov/docketsearch' target='_blank' rel='nofollow ugc noopener noreferrer'><span style='font-family:&quot;Avenir Next&quot;; font-size:11.25pt;'><span style='background-attachment:initial; background-clip:initial; background-image:initial; background-origin:initial; background-position:initial; background-repeat:initial; background-size:initial;'>Virginia State Corporation Commission (SCC)</span></span></a><span style='font-family:&quot;Segoe UI&quot;; font-size:12pt;'><span style='background-attachment:initial; background-clip:initial; background-image:initial; background-origin:initial; background-position:initial; background-repeat:initial; background-size:initial;'>. REDA includes all actively permitted renewable energy permits, <span style='background-color:rgb(255, 255, 255);'>including </span>facilities that have not been constructed and facilities that have not commenced commercial operation. Dataset updated intermittently on an as needed basis. </span></span></p><p>Data contained within the Renewable Energy Development Atlas is not reflective of existing or future land disturbance. An up-to-date review of existing land disturbance as a result of utility-scale solar development across the Commonwealth can be viewed <a href='https://energy.virginia.gov/renewable-energy/documents/Re-Evaluating%20Land%20Use%20Impacts%20of%20Utility-Scale%20Solar%20-%20FINAL.pdf' target='_blank' rel='nofollow ugc noopener noreferrer'>here</a>.</p><p><span style='font-family:&quot;Segoe UI&quot;; font-size:12pt;'><span style='background-attachment:initial; background-clip:initial; background-image:initial; background-origin:initial; background-position:initial; background-repeat:initial; background-size:initial;'><br /></span></span></p><p><a href='https://gisdata.deq.virginia.gov/mapper_ext/DataFactSheets/Renewable_Energy/DEQFactSheetV2_REDA.pdf' style='color:rgb(0, 94, 149); font-family:&quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size:16px;' target='_blank' rel='nofollow ugc noopener noreferrer'>DEQ Data Fact Sheet</a><span style='font-family:&quot;Segoe UI&quot;; font-size:12pt;'><span style='background-attachment:initial; background-clip:initial; background-image:initial; background-origin:initial; background-position:initial; background-repeat:initial; background-size:initial;'></span></span></p>
Virginia Physiographic Regions

This is a polygon coverage of Physiographic Divisions in the conterminous United States cropped to the state boundary of Virginia. It was automated from Fenneman's 1:7,000,000-scale map, "Physical Divisions of the United States," which is based on eight major 1946 divisions, 25 provinces, and 86 sections representing distinctive areas having common topography, rock types and structure, and geologic and geomorphic history.
Virginia County Fiscal Stress

Polygon layer representing the Fiscal Stress of Virginia's Cities and Counties. Data from VA Dept of Housing and Community Development and Virginia Admin Boundaries Dataset (VGIN). For more information please see the current report: <span style='font-size:11.0pt;font-family:&quot;Calibri&quot;,sans-serif;color:#1f497d'><a href='https://www.dhcd.virginia.gov/fiscal-stress' rel='nofollow ugc' target='_blank'>https://www.dhcd.virginia.gov/fiscal-stress</a></span>
US Census Urbanized Areas (2010)

selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation.

After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes.

 Access Constraints: None, Use Constraints:The TIGER/Line Shapefile products are not copyrighted however TIGER/Line and Census TIGER are registered trademarks of the U.S. Census Bureau. These products are free to use in a product or publication, however acknowledgement must be given to the U.S. Census Bureau as the source. The boundary information in the TIGER/Line Shapefiles are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement and they are not legal land descriptions.Coordinates in the TIGER/Line shapefiles have six implied decimal places, but the positional accuracy of these coordinates is not as great as the six decimal places suggest.

https://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural/2010-urban-rural.html