AndreaBozzo/ceres-open-data-index huggingface dataset:
Roadway Intersection Approach

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Intersection Approach Segments are short segments of the route that approach an intersection, in other words, a short section of the road leading up to an intersection.</SPAN></P><P><SPAN>Roads and Highways manages intersections, however they are not singular points; RH creates a series of points - one for each intersecting road at that intersection. For DDOT, it is more useful to have a single intersection point representing the intersection. Through a custom DDOT script,the series of intersection points is reduced into a single representative point.</SPAN></P><P><SPAN>For more information please visit </SPAN><A href="https://wiki.ddot.dc.gov/display/GIS/Roadway+Characteristics"><SPAN>DDOT's wiki page</SPAN></A><SPAN>.</SPAN></P></DIV></DIV></DIV>

Tags: dc, ddot, district-of-columbia, intersection, intersection-approach, linear-referencing, lrs, roadway, roadway-block, roadwayhub, transportation
Organization: District of Columbia
Street Lights

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Street Light Assets. The dataset contains locations and attributes of street lights provided by the District Department of Transportation (DDOT).</SPAN></P></DIV></DIV></DIV>

Tags: dc, district-of-columbia, safety, street-lights, trail-lights, transportation, tunnel-lights, washington-dc
Organization: District of Columbia
Closed Circuit TV Street Cameras

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Closed Circuit TV Street Cameras locations. The dataset contains locations and attributes of CCTV and other cameras, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies.</SPAN></P></DIV></DIV></DIV>

Tags: camera, cctv, commuter, congestion, d-c, dc, dc-gis, dcgis, district-of-columbia, public-safety, street, traffic, transportation, washington, washington-dc
Organization: District of Columbia
Sidewalk Condition Assessment

<div style='text-align:Left;'><div><div><p><span>The data includes the five condition categories, excellent, good, fair, poor and failed. The data reflects a sidewalk condition index score ranging from 0 to 11. The higher the value, the better the sidewalk condition. The data also includes the primary and secondary material type of the sidewalk. It also entails the 8 most common conditions and the value expressed numerically.</span></p></div></div></div>

Tags: dc, ddot, district-of-columbia, sidewalk-condition, sidewalks, washington-dc
Organization: District of Columbia
Urban Forestry Street Trees

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>DDOT's Urban Forestry Division (UFD) is the primary steward of Washington DC's ~175,000 public trees and has a mission of keeping this resource healthy, safe, &amp; growing. Trees in the city are critical to our well-being. Visit </SPAN><A href="https://trees.dc.gov:443/" STYLE="text-decoration:underline;"><SPAN>trees.dc.gov</SPAN></A><SPAN> for more information.</SPAN></P></DIV></DIV></DIV>

Tags: canopy, dc, ddot, district-of-columbia, environment, street-tree, terrestrial, tree, washington-dc
Organization: District of Columbia
Odor Control Plans

<div style='text-align:Left;'><div><div><p><span>To better enforce and regulate nuisance odor concerns, DOEE requires certain facilities known to produce odors to develop an Odor Control Plan (OCP) subject to DOEE approval. This data set is available to show the status of OCPs and provide access to the submitted plans. It includes information on the facilities that have submitted plans, the status of approval or disapproval, and links to the plans.</span></p></div></div></div>

Tags: air-pollution, dc, district-of-columbia, doee, environment, odor, odor-control, washington-dc
Organization: District of Columbia
DC Well Permits

<div style='text-align:Left;'><div><div><p><span>Wells are defined by 21 DCMR Chapter 18 as any test hole, shaft, or soil excavation created by any means including, but not limited to, drilling, coring, boring, washing, driving, digging, or jetting, for purposes including, but not limited to, locating, testing, diverting, artificially recharging, or withdrawing fluids, or for the purpose of underground injection. The </span><a href='https://doee.dc.gov:443/' style='text-decoration:underline;' rel='nofollow ugc'><span>Department of Energy &amp; Environment</span></a><span>'s Regulatory Review Division reviews permit applications to install wells in private and public space through the Department of Licensing and Consumer Protection and the District Department of Transportation.</span></p></div></div></div>

Tags: dc-water, district-of-columbia, environment, washington-dc, well-permits, wells
Organization: District of Columbia
Respiratory Virus Hospital Admissions Over Time

<strong>A. SUMMARY</strong>
This dataset includes weekly respiratory disease hospital admissions for Influenza, RSV, and COVID-19 into San Francisco hospitals. Columns in the dataset include a count and rate of hospital admissions per 100,000 people. The data are reported by week.
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<strong>B. HOW THE DATASET IS CREATED </strong>
Hospital admission data is reported to the San Francisco Department of Public Health (SFDPH) from the United States Center for Disease Control’s (CDC) National Healthcare Safety Network (<u><a href="https://www.cdc.gov/nhsn/index.html">NHSN</a></u>) program.

San Francisco population estimates are pulled from a view based on the<u> <a href="https://data.sfgov.org/Economy-and-Community/SFDPH-reporting-demographics-population-estimates/cedd-86uf">San Francisco Population and Demographic Census dataset</a></u>. These population estimates are from the 2019-2023 5-year American Community Survey (ACS).
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<strong>C. UPDATE PROCESS </strong>
The dataset is updated every Friday and includes data from the previous Sunday through Saturday. For example, the update on Friday, October 17th will include data through Saturday, October 11th.  Data may change as more current information becomes available.
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<strong>D. HOW TO USE THIS DATASET</strong>
Weekly data represent a count of confirmed admissions of Influenza, RSV, and COVID-19 patients to San Francisco hospitals by week. The admission rate per 100,000 is calculated by multiplying the count of admissions each week by 100,000 and dividing by the population estimate.
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<strong>E. ARCHIVED DATA</strong>
A previous version of COVID-19 Hospital Admissions Over TIme  dataset was archived. For historical purposes, you can access the archived dataset <u><a href="https://data.sfgov.org/Health-and-Social-Services/ARCHIVED-COVID-19-Hospital-Admissions-Over-Time/82gu-asz5/about_data">here</a></u>.

Organization: City of San Francisco
Open Data DC

<p>On this site the District of Columbia government shares opportunities to explore hundreds of datasets through direct downloads, interactive applications and developer resources through APIs. Engage with the District through government open data.</p><p><br /></p>

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	<a href='https://opendata.dc.gov/pages/apps-and-maps' style='color:transparent;' rel='nofollow ugc'>
<img alt='Apps and Maps' src='https://dcgis.maps.arcgis.com/sharing/rest/content/items/815aa68f23314515814edd06e0355b9d/data' />
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	<h2>Apps &amp; Maps</h2>
	<p style='font-size:17px;'>Discover data in DC's urban landscape with these web maps &amp; apps.</p><br />
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<div style='text-align:center;'>
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	<a style='color:transparent;' href='https://opendata.dc.gov/pages/data-stories' rel='nofollow ugc'>
<img src='https://dcgis.maps.arcgis.com/sharing/rest/content/items/4f00dbe21855487ebc076b330b5799c2/data' alt='Data Stories' />
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	<h2>Data Stories</h2>
	<p style='font-size:17px;'>Opportunities for all learners to read how DC is using data for operations, education and encouraging civic participation.</p><br />
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<div style='text-align:center;'>
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	<a style='color:transparent;' href='https://opendata.dc.gov/pages/dashboards' rel='nofollow ugc'>
  <img src='https://dcgis.maps.arcgis.com/sharing/rest/content/items/6e1e36d509ec4dbe9499a55e31b23853/data' alt='Dashboards' />
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	</div>
	<h2>Dashboards</h2>
	<p style='font-size:17px;'>Link today's data with yesterday and see patterns with these interactive web visualizations.</p><br />
</div>

<div style='text-align:center;'>
<div>
<a style='color:transparent;' href='https://opendata.dc.gov/search' rel='nofollow ugc'>
<img src='https://dcgis.maps.arcgis.com/sharing/rest/content/items/cc784bf6d13d4b41b560495a384c19d3/data' alt='Data Catalog' />
</a>
</div>
	<h2>Data Catalog</h2>
	<p style='font-size:17px;'>Browse the data, download it as a file, analyze it with your tools, or build apps using our APIs.<br /></p><br />
</div>

Tags: district-of-columbia, washington-dc
Organization: District of Columbia
DC Smart Street Lights

The DC Smart Street Lighting Project will modernize streetlights in the District of Columbia by converting them to LED technology with remote monitoring and control capabilities. LEDs better direct light onto the road, sidewalks, and trails, all helping to improve safety and advance the District’s Vision Zero goals. The project increases the city’s sustainability efforts by reducing streetlight energy consumption by more than 50 percent, eliminating 38,000 tons of greenhouse gas emissions each year.

Tags: hub-site
Organization: District of Columbia
Bus Priority Projects

Mayor Muriel Bowser established the Bus Priority Program to improve bus speeds and reliability for riders across the District, whether on Metrobus, DC Circulator, or commuter buses. The bus network provides vital connections to jobs, schools, healthcare, and other destinations. By improving bus service, the District Department of Transportation (DDOT) is improving mobility and access to opportunities for District residents, workers, and visitors. Learn more about District Department of Transportation Bus Priority projects. Email: <a href='mailto:buspriority@dc.gov' target='_blank' rel='nofollow ugc noopener noreferrer'>buspriority@dc.gov</a>. This site includes current, future, and completed project information, as well as how to provide feedback on bus priority projects.

Tags: bus, ddot, district-of-columbia, featuredprogram, hub-site, transit, washington-dc
Organization: District of Columbia
Potomac Interceptor E. coli Sample Results

<p><span style='font-size:16px;'>A regional dataset containing<i> E. coli</i> monitoring sampling results collected along the Potomac and Anacostia Rivers, in response to the January 2026 Potomac Interceptor Collapse. Each data provider retains responsibility for its own data and submits to this compilation dataset voluntarily. Check the <i>Source</i> field to identify the data provider:</span></p><ul><li><a target='_blank' href='https://doee.dc.gov/' rel='nofollow ugc noopener noreferrer'><span style='font-size:16px;'>DC Department of Energy &amp; Environment (DOEE)</span></a></li><li><a target='_blank' href='https://mde.maryland.gov/Pages/index.aspx' rel='nofollow ugc noopener noreferrer'><span style='font-size:16px;'>Maryland Department of the Environment (MDE)</span></a></li><li><a target='_blank' href='https://www.deq.virginia.gov/' rel='nofollow ugc noopener noreferrer'><span style='font-size:16px;'>Virginia Deparment of Environmental Quality (VADEQ)</span></a></li><li><a target='_blank' href='https://www.dcwater.com/' rel='nofollow ugc noopener noreferrer'><span style='font-size:16px;'>DC Water</span></a></li><li><a target='_blank' href='https://potomacriverkeepernetwork.org/' rel='nofollow ugc noopener noreferrer'><span style='font-size:16px;'>Potomac Riverkeepers Network (PRK)</span></a><span style='font-size:16px;'> with University of Maryland (UMD)&nbsp;</span></li></ul><p><span style='font-size:16px;'>Contact individual data providers to learn more about their data (i.e., collection, quality assurance, terms of use, etc.). Questions regarding DC Department of Energy &amp; Environment sampling sites can be directed to </span><a href='mailto:pi.data@dc.gov' rel='nofollow ugc'><span style='font-size:16px;'>pi.data@dc.gov</span></a><span style='font-size:16px;'>.</span></p>

Tags: e-coli, potomac, water-quality
Organization: District of Columbia
BLM OR Biological Treatments Polygon Hub

BIO_POLY: This dataset represents completed biological land treatments for BLM managed lands in the states of Oregon and Washington. Biological treatments are the introduction of foraging species, predators or parasites to control plant or animal pests, or to selectively suppress or remove vegetation.

Tags: bio, biological, biota, completed, environment, geospatial, management, oregon, treatments, vegetation, washington, wildlife
Organization: Department of the Interior
BLM OR Exclosure Protection Treatments Polygon Hub

PROT_POLY: This dataset represents completed treatments involving fenced exclosures or protective devices on trees or soil surfaces on BLM managed lands in the states of Oregon and Washington. The entire area is considered "treated" with protection measures. The individual structures or devices used may or may not be captured on a separate theme (STRCT_ARC and/or STRCT_PT).

Tags: biota, completed, disturbance, economy, environment, exclosures, farming, fire, forest, land-use-planning, location, oregon, protection, treatments, vegetation, washington
Organization: Department of the Interior
BLM Colorado Recreation Sites

<div style='text-align:Left; font-size:12pt;'><div><p><span>Illustrate BLM Colorado Recreation point locations and boundaries. The point dataset represents the point features that show the physical locations of BLM Colorado Recreation Sites. The polygon dataset represents the spatial extent and boundaries of the BLM Colorado Recreation Sites.</span></p></div></div>

Tags: blm, bureau-of-land-management, colorado, economy, facility, geospatial, location, management, public-lands, recreation, recreation-sites, society, structure, transportation
Organization: Department of the Interior
BLM Colorado Recreation Points

<div style='text-align:Left; font-size:12pt;'><div><p><span>Illustrate BLM Colorado Recreation point locations and boundaries. The point dataset represents the point features that show the physical locations of BLM Colorado Recreation Sites. The polygon dataset represents the spatial extent and boundaries of the BLM Colorado Recreation Sites.</span></p></div></div>

Tags: blm, bureau-of-land-management, colorado, economy, facility, geospatial, location, management, public-lands, recreation, recreation-sites, society, structure, transportation
Organization: Department of the Interior
BLM Natl MLRS Coal Cases

This dataset contains coal cases derived from Legal Land Descriptions (LLD) contained in the US Bureau of Land Management's, BLM, Mineral and Land Record System(MLRS) and geocoded (mapped) using the Public Land Survey System (PLSS) derived from the most accurate survey data available through BLM Cadastral Survey workforce. Geospatial representations might be missing for some cases that can not be geocoded using the MLRS algorithm. This data set contains cases with the dispositions of 'Authorized', 'Pending','Closed', and 'Interim'.<div><br /></div><div>Each case is given a data quality score based on how well it mapped.  These can be lumped into seven groups to provide a simplified way to understand the scores. <div><ul><li>Group 1: Direct PLSS Match. Scores “0”, “1”, “2”, “3” should all have a match to the PLSS data. There are slight differences, but the primary expectation is that these match the PLSS.</li><li> Group 2: Calculated PLSS Match. Scores “4”, “4.1”, “5”, “6”, “7” and “8” were generated through a process of creating the geometry that is not a direct capture from the PLSS. They represent a best guess based on the underlining PLSS</li><li> Group 3 – Mapped to Section. Score of “8.1”, “8.2”, “8.3”, “9” and “10” are mapped to the Section for various reasons (refer to log information in data quality field).</li><li> Group 4- Combination of mapped and unmapped areas. Score of 15 represents a case that has some portions that would map and others that do not. </li><li> Group 5 – No NLSDB Geometry, Only Attributes. Scores “11”, “12”, “20”, “21” and “22” do not have a match to the PLSS and no geometry is in the NLSDB, and only attributes exist in the data. </li><li> Group 6 – Mapped to County. Scores of “25” map to the County.</li><li> Group 7 – Improved Geometry. Scores of “100” are cases that have had their geometry edited by BLM staff using ArcGIS Pro or MLRS bulk upload tool.</li></ul></div></div>

Tags: alabama, alaska, arizona, arkansas, authorization, boundaries, california, colorado, connecticut, delaware, district-of-columbia, eastern-states, energy, florida, geology, georgia, geoscientificinformation, geospatial, idaho, illinois, indiana, iowa, kansas, kentucky, land-grid, lease, louisiana, maine, management, maryland, massachusetts, michigan, mining, minnesota, mississippi, missouri, montana, nebraska, nevada, new-hampshire, new-jersey, new-mexico, new-york, north-carolina, north-dakota, ohio, oklahoma, oregon, pennsylvania, permit, planningcadastre, plss, public-land-survey-system, rhode-island, section, south-carolina, south-dakota, tennessee, texas, township, utah, vermont, virginia, washington, west-virginia, wisconsin, wyoming
Organization: Department of the Interior
BLM ID Sage Grouse Habitat 2022

The 2022 Sage-grouse Habitat Planning Map update incorporates wildfire data and other edits relevant to the 2022 field and fire season as per typical processes used during the past decade. Additional areas of non-habitat, such as paved highways, municipal boundaries, water bodies etc., were also removed. However, the map extent for sage-grouse key habitat and potential restoration areas should be considered provisional, contingent on the final outcome of additional analyses currently underway in association with the national Greater Sage-grouse Conservation Strategy. This data set contains simple, landscape-scale greater sage-grouse habitat types for Idaho and constitutes a current approximation of sage-grouse habitat in the state. The data can be used for general conservation and restoration planning purposes, but additional data or field verification are needed for applications at finer scales. The habitat types include: (1) key sage-grouse habitat areas and (2) four habitat restoration types: (a) R1 - perennial native and non-native grasslands with high restoration potential; (b) R2 - annual grass dominated areas (either shrubland or grassland) with low restoration potential; (c) R3 - conifer encroachment areas with high restoration potential and (d) RB - areas that have recently burned and the type of habitat that is coming back and its restoration potential has not yet been determined. Beginning in 2015, the NA class was included to track areas that were previously identified as habitat but were removed due to vegetation type or terrain (eg. stands of existing timber on North-facing slopes). A new data set will be developed annually to update the planning map and chart landscape-level changes in sage-grouse habitat over time. Edits may also document refinements discovered through inventory, monitoring and modeling. This data covers all of Idaho and a small area in Nevada that is managed by Idaho BLM. Intended scale of use is 1:100,000. This dataset is not synonymous with BLM's Sage-grouse Habitat Management Areas (Priority, Important and General) as those incorporate additional habitat and sage-grouse population data or models.

Tags: 2022, biota, blm, boise-district-office, bruneau-field-office, bureau-of-land-management, burley-field-office, centrocercus-urophasianus, challis-field-office, department-of-energy, department-of-the-interior, doe, doi, environment, forest-service, four-rivers-field-office, fragmentation, greater-sage-grouse, habitat, id, idaho, idaho-falls-district, jarbidge-field-office, nevada, nv, owyhee-field-office, pocatello-field-office, restoration, sage-grouse, salmon-field-office, shoshone-field-office, twin-falls-district-office, u-s-department-of-agriculture, united-states, upper-snake-field-office, us, vegetation, wildlife
Organization: Department of the Interior
BLM OR Stand Exam Publication Point Hub

STAND_EXAM_PUB_PT: This dataset is a spatial representation of Forest Stand Exam point locations that are recorded in the tabular EcoSurvey application. The EcoSurvey application utilizes a handheld data recorder to collect stand exam data in the field and PC application to process the data to generate custom reports to summarize the data. Data summaries include stand level statistics, and export files for growth and yield models. The EcoSurvey application provides the ability to run summary reports on select groupings of plots. The purpose of this dataset is to display plot data spatially to be able to run summary reports on a spatially selected group of plots. The Stand Exam Points dataset is a sub-class of the Oregon Data Framework Sample Points dataset theme. For ease of publishing this data, it is presented as a separate dataset from other sample point data types. Dataset (Theme) Name: Stand Exam Points · Dataset (Feature Class): STAND_EXAM_PUB_PT

Tags: biota, ecosurvey, forest, forest-cover, forest-regeneration, forest-restocking, geospatial, management, natural-resources, oregon, pacific-northwest, timber-stand, trees, washington
Organization: Department of the Interior
BLM CO Range Improvement Points

Range Improvements are man-made or man-caused features on the landscape designed and implemented for the purpose of improving the available forage, managing the season of use or use patterns and enhancing the overall rangeland health of areas available for domestic livestock use. Range improvements may occur on private, state, and public lands under the jurisdiction of the Bureau of Land Management (BLM) and/or other federal or state agencies. On public lands managed by the Bureau of Land Management (BLM), permittees or lessees (henceforth, “operators”) may be required to install range improvements to meet the terms and conditions of their permits or leases. Often the BLM, operators, and other interested parties work together and jointly contribute to construction.Range improvements are authorized physical modifications or treatment which are designed to improve production of forage; change vegetation composition; control patterns of use; provide water; stabilize soil and water conditions; restore, protect, and improve the conditions of the rangeland ecosystems to benefit livestock, wild horses and burros, and fish and wildlife. They include, but are not limited to, structures, treatment projects and use of mechanical devices or modifications achieved through mechanical means. Range Improvements. There are two kinds of range improvements: nonstructural and structural. Seeding or prescribed burns are examples of nonstructural range improvements. Fences or facilities such as wells or water pipelines are examples of structural improvements. Many structural improvements are considered permanent, as they are not easily removed from the land. This data standard will only relate to structural range improvements features as GIS and attribute data related to almost all non-structural range improvements is stored in other national data standard datasets (e.g. NISIMS, VTRT, NFPORS). Range improvement data is also available in the Range Improvement System (RIPS), a BLM database used for tracking the establishment and maintenance of range improvments. RIPS is the database of record and contains the data to be used for budgetary and workload planning. This data set shall be comprised of a spatial display of the data in RIPS. The record unique identifier within the RIPS database (RIPS number) will be added to GIS features in this data standard to link between spatial depictions of range improvements features to their corresponding RIPS records. Wherever possible RIPS data shall be used to populate this data set.

Tags: biota, blm-colorado, colorado, environment, farming, geospatial, health, inlandwaters, range, range-improvements, rips
Organization: Department of the Interior