AndreaBozzo/ceres-open-data-index huggingface dataset:
Active Bacterial Core surveillance (ABCs) Haemophilus influenzae

ABCs is an ongoing surveillance program that began in 1997. <a href="https://www.cdc.gov/abcs/reports-findings/surv-reports.html">ABCs reports</a> describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year.  The methods, <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html">surveillance areas</a>, and <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html">laboratory isolate collection areas</a> have changed over time.
                Additionally, the way missing data are taken into account changed in 2010.  It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method.
                Given these changes over time, trends should be interpreted with caution.
<ul> <li> <a href="http://www.cdc.gov/abcs/methodology/index.html">Methodology</a>
Find details about surveillance population, case determination, surveillance evaluation, and more. </li>                    <li> <a href="http://www.cdc.gov/abcs/reports-findings/index.html">Reports and Findings</a>
Get official interpretations from reports and publications created from ABCs data. </li>
  </ul>

Tags: abcs, bactfacts
Organization: U.S. Department of Health & Human Services
Active Bacterial Core surveillance (ABCs) Group B Streptococcus

ABCs is an ongoing surveillance program that began in 1997. <a href="https://www.cdc.gov/abcs/reports-findings/surv-reports.html">ABCs reports</a> describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year.  The methods, <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html">surveillance areas</a>, and <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html">laboratory isolate collection areas</a> have changed over time.
                Additionally, the way missing data are taken into account changed in 2010.  It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method.
                Given these changes over time, trends should be interpreted with caution.
<ul><li> <a href="http://www.cdc.gov/abcs/methodology/index.html">Methodology</a>
Find details about surveillance population, case determination, surveillance evaluation, and more. </li> <li><a href="http://www.cdc.gov/abcs/reports-findings/index.html">Reports and Findings</a>
Get official interpretations from reports and publications created from ABCs data.
 </li>                </ul>

Tags: abcs, bactfacts
Organization: U.S. Department of Health & Human Services
Active Bacterial Core surveillance (ABCs) Streptococcus pneumoniae

ABCs is an ongoing surveillance program that began in 1997. <a href="https://www.cdc.gov/abcs/reports-findings/surv-reports.html">ABCs reports</a> describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year.  The methods, <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html">surveillance areas</a>, and <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html">laboratory isolate collection areas</a> have changed over time.
                Additionally, the way missing data are taken into account changed in 2010.  It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method.
                Given these changes over time, trends should be interpreted with caution.
<ul>  <li> <a href="http://www.cdc.gov/abcs/methodology/index.html">Methodology</a>
                Find details about surveillance population, case determination, surveillance evaluation, and more.  </li>                    <li> <a href="http://www.cdc.gov/abcs/reports-findings/index.html">Reports and Findings</a>  
                 Get official interpretations from reports and publications created from ABCs data.        </li> </ul>

Tags: abcs, bactfacts
Organization: U.S. Department of Health & Human Services
Active Bacterial Core surveillance (ABCs) Neisseria meningitidis

<p>ABCs is an ongoing surveillance program that began in 1997. <a href="https://www.cdc.gov/abcs/reports-findings/surv-reports.html">ABCs reports</a> describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year.  The methods, <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html">surveillance areas</a>, and <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html">laboratory isolate collection areas</a> have changed over time.
                Additionally, the way missing data are taken into account changed in 2010.  It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method.
                Given these changes over time, trends should be interpreted with caution.
<ul> <li> <a href="http://www.cdc.gov/abcs/methodology/index.html">Methodology</a>
Find details about surveillance population, case determination, surveillance evaluation, and more. </li>                    <li> <a href="http://www.cdc.gov/abcs/reports-findings/index.html">Reports and Findings</a>
Get official interpretations from reports and publications created from ABCs data. </li>
  </ul>

Tags: abcs, bactfacts
Organization: U.S. Department of Health & Human Services
Active Bacterial Core surveillance (ABCs) Group A Streptococcus

ABCs is an ongoing surveillance program that began in 1997. <a href="https://www.cdc.gov/abcs/reports-findings/surv-reports.html">ABCs reports</a> describe the ABCs case definition and the specific methodology used to calculate rates and estimated numbers in the United States for each bacterium by year.  The methods, <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html">surveillance areas</a>, and <a href="https://www.cdc.gov/abcs/methodology/surv-pop.html" >laboratory isolate collection areas</a> have changed over time.
                Additionally, the way missing data are taken into account changed in 2010.  It went from distributing unknown values based on known values of cases by site to use of multiple imputation using a sequential regression imputation method.
                Given these changes over time, trends should be interpreted with caution.
<ul><li><a href="http://www.cdc.gov/abcs/methodology/index.html">Methodology</a>
Find details about surveillance population, case determination, surveillance evaluation, and more. </li> <li> <a href="http://www.cdc.gov/abcs/reports-findings/index.html">Reports and Findings</a>
Get official interpretations from reports and publications created from ABCs data.
</li>                </ul>

Tags: abcs, bactfacts
Organization: U.S. Department of Health & Human Services
Durable Assets For Hawaii Noncandidate Committees From January 1, 2015 – June 30, 2025

Durable Assets For Hawaii Noncandidate Committees From January 1, 2015 – June 30, 2025 . The data set also includes searchable data from amended reports filed in the last ten years with transactions dated prior to January 1, 2015.

Tags: campaign-contributions, campaign-finance, campaign-spending, campaign-spending-commission, candidate, contributions, hawaii-candidates, political-contributions
Organization: State of Hawaii
Other Receipts For Hawaii State and County Candidates From January 1, 2015 – June 30, 2025

Other Receipts For Hawaii State and County Candidates From January 1, 2015 – June 30, 2025. The data set also includes searchable data from amended reports filed in the last ten years with transactions dated prior to January 1, 2015.

Tags: campaign-contributions, campaign-finance, campaign-spending, campaign-spending-commission, candidate, contributions, hawaii-candidates, political-contributions
Organization: State of Hawaii
Other Receipts For Hawaii Noncandidate Committees From January 1, 2015 – June 30, 2025

Other Receipts For Hawaii Noncandidate Committees From January 1, 2015 – June 30, 2025. The data set also includes searchable data from amended reports filed in the last ten years with transactions dated prior to January 1, 2015.

Tags: campaign-contributions, campaign-finance, campaign-spending, campaign-spending-commission, candidate, contributions, hawaii-candidates, political-contributions
Organization: State of Hawaii
Loans Received By Hawaii State and County Candidates From January 1, 2015 – June 30, 2025

Loans Received By Hawaii State and County Candidates From January 1, 2015 – June 30, 2025. The data set also includes searchable data from amended reports filed in the last ten years with transactions dated prior to January 1, 2015.

Tags: campaign-contributions, campaign-finance, campaign-spending, campaign-spending-commission, candidate, contributions, hawaii-candidates, political-contributions
Organization: State of Hawaii
Durable Assets For Hawaii State and County Candidates From January 1, 2015 – June 30, 2025

Durable Assets For Hawaii State and County Candidates From January 1, 2015 – June 30, 2025. The data set also includes searchable data from amended reports filed in the last ten years with transactions dated prior to January 1, 2015.

Tags: campaign-contributions, campaign-finance, campaign-spending, campaign-spending-commission, candidate, contributions, hawaii-candidates, political-contributions
Organization: State of Hawaii
Expenditures Made By Hawaii Noncandidate Committees From January 1, 2015 – June 30, 2025

Expenditures Made By Hawaii Noncandidate Committees From January 1, 2015 – June 30, 2025. The data set also includes searchable data from amended reports filed in the last ten years with transactions dated prior to January 1, 2015.

Tags: campaign-contributions, campaign-finance, campaign-spending, campaign-spending-commission, candidate, contributions, hawaii-candidates, political-contributions
Organization: State of Hawaii
Campaign Contributions Received By Hawaii State and County Candidates From January 1, 2015 – June 30, 2025

Campaign Contributions Received By Hawaii State and County Candidates From January 1, 2015 – June 30, 2025. The data set also includes searchable data from amended reports filed in the last ten years with transactions dated prior to January 1, 2015.

Tags: campaign, campaign-contributions, campaign-finance, campaign-spending, campaign-spending-commission, candidate-committee, contributions, csc, elections, hawaii-candidates, political-contributions
Organization: State of Hawaii
Unpaid Expenditures For Hawaii Noncandidate Committees From January 1, 2015 – June 30, 2025

Unpaid Expenditures For Hawaii Noncandidate Committees From January 1, 2015 – June 30, 2025. The data set also includes searchable data from amended reports filed in the last ten years with transactions dated prior to January 1, 2015.

Tags: campaign-contributions, campaign-finance, campaign-spending, campaign-spending-commission, candidate, contributions, hawaii-candidates, political-contributions
Organization: State of Hawaii
Metrics for Offline Evaluation of Prognostic Performance

Prognostic performance evaluation has gained significant attention in the past few years.*Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end- user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.

Tags: ames, dashlink, nasa
Organization: National Aeronautics and Space Administration
MTA Subway and Rail Station Envelopes with 50 Foot Buffer

This dataset consists of a set of 2D geospatial polygons that are intended to capture a 50-foot buffer around all publicly accessible areas of NYCT, LIRR, and MNR rail mass transit stations within the City of New York as defined by the New York City Zoning Resolution Article 6 Chapter 6 – Special Regulations Applying Around Mass Transit Stations (NYC ZR § 66-00). This dataset is intended to help inform property owners whose property may fall under the requirements of NYC ZR § 66-00, specifically those that significantly enlarge or develop real property with an area larger than 5,000 square feet within 50 feet of a mass transit station.

Tags: accessibility, commuter-rail, lirr, long-island-rail-road, metro-north, metro-north-railroad, metropolitan-transportation-authority, mnr, new-york-city-transit, nyct, path, port-authority-trans-hudson, sir, staten-island-railway, subway, subway-stations, zoning-for-accessibility
Organization: State of New York
MTA Subway and Rail Station Envelopes

This dataset consists of a set of 2D geospatial polygons that are intended to capture all publicly accessible areas of NYCT, LIRR, and MNR rail mass transit stations within the City of New York as defined by the New York City Zoning Resolution Article 6 Chapter 6 – Special Regulations Applying Around Mass Transit Stations (NYC ZR § 66-00). This dataset is intended to help inform property owners whose property may fall under the requirements of NYC ZR § 66-00, specifically those that significantly enlarge or develop real property with an area larger than 5,000 square feet within 50 feet of a mass transit station.

Tags: accessibility, commuter-rail, lirr, long-island-rail-road, metro-north, metro-north-railroad, metropolitan-transportation-authority, mnr, new-york-city-transit, nyct, path, port-authority-trans-hudson, sir, staten-island-railway, subway, subway-stations, zoning-for-accessibility
Organization: State of New York
A Vision for Safer Roads

<div><p><b><font size='4'>What is Vision Zero?</font></b></p>

<p>Vision Zero is a traffic safety policy that takes an ethical
approach towards achieving safety for all road users. The goal is to achieve a
reduction in the number of fatal and serious injury crashes to zero in Tempe,
because no loss of life is acceptable.</p>

<p><b><font size='4'>Data Driven Safety Policies</font></b></p>

<p>Fatal and serious injury crashes are not “accidents” and are
preventable. The City of Tempe is committed to reducing the number of fatal and
serious injury crashes to zero. One death is too many. One serious injury is
too many.</p>

<p>This application explores Tempe's crash data which is
collected by the Tempe Police Department and reported to the Arizona Department
of Transportation. Traffic engineers use this data for network screening, which
they can then use for diagnosing potential safety issues and implementing
countermeasures to improve safety.</p>

<p><b><font size='4'>Community Input</font></b></p>

<p>Included in this application is an option for people from
the community to add their own transportation safety concerns that the City of
Tempe should be made aware of.</p>

<p><font size='4' style=''><b>Story map sections include:</b></font></p>

<p><ul><li>A Vision for Safer Roads<br /></li><li>Mode of Travel<br /></li><li>Data Visualization<br /></li><li>Crash Data Map Viewer<br /></li><li>Community Feedback<br /></li></ul></p>

<p></p>

<p></p>

<p></p>

<p></p>

<p>More information on Tempe’s Vision Zero program may be found
at <a href='https://www.tempe.gov/city-hall/public-works/transportation/vision-zero#STRATEGIES' target='_blank' rel='nofollow ugc noopener noreferrer'>https://www.tempe.gov/city-hall/public-works/transportation/vision-zero#STRATEGIES</a>.</p></div><p><span style='font-family:Roboto'></span></p>

Tags: accident, arizona, car-accidents, crash, cyclist, high-severity-traffic-crashes-pm-1-08, pedestrian, safe-and-secure-communities, tempe, transportation, vision-zero
Organization: City of Tempe
1.08 Crash Data Report (detail)

<p><strong>Please note that 2025 data are incomplete and will be updated as additional records become available. Data are complete through 12/31/2024.</strong><br />&nbsp;</p><p>Fatal and serious injury crashes are not “accidents” and are preventable. The City of Tempe is committed to reducing the number of fatal and serious injury crashes to zero. This data page provides details about the performance measure related to High Severity Traffic Crashes, as well as access to the data sets and any supplemental data. The Engineering and Transportation Department uses this data to improve safety in Tempe.</p><p><span style='color:#444849; font-size:medium;'>This data includes vehicle/vehicle, vehicle/bicycle, and vehicle/pedestrian crashes in Tempe. The data also includes the type of crash and location. This layer is used in the related Vision Zero story map, web maps, and operations dashboard.&nbsp;</span><br /><br /><span style='color:#444849; font-size:medium;'><u>Time Zones</u></span><br /><span style='color:#444849; font-size:medium;'>Please note that data is stored in Arizona time, which is UTC-07:00 (7 hours behind UTC) and does not adjust for daylight saving (as Arizona does not partake in daylight saving). The data is intended to be viewed in Arizona time. Data downloaded as a CSV may appear in UTC time and, in some rare circumstances and locations, may display online in UTC or local time zones.&nbsp;<i>As a reference to check data, the record with incident number&nbsp;2579417 should appear as Jan. 10, 2012, 9:04 AM.</i></span></p><p><strong>Please note that 2025 data are incomplete and will be updated as additional records become available. Data are complete through 12/31/2024.</strong></p><p>This page provides data for the High Severity Traffic Crashes performance measure.&nbsp;<br /><br />The performance measure page is available at&nbsp;<a target='_blank' href='https://safe-and-secure-communities-tempegov.hub.arcgis.com/pages/high-severity-traffic-crashes' rel='nofollow ugc noopener noreferrer'>1.08 High Severity Traffic Crashes</a><br /><br /><strong>Additional Information</strong></p><p>Source: Arizona Department of Transportation (ADOT)<br />Contact (author): Shelly Seyler<br />Contact (author)&nbsp; E-Mail: Shelly_Seyler@tempe.gov<br />Contact (maintainer): Julian Dresang<br />Contact (maintainer) E-Mail: Julian_Dresang@tempe.gov<br />Data Source Type: CSV files and Excel spreadsheets can be downloaded from the ADOT website<br />Preparation Method: Data is sorted to remove license plate numbers and other sensitive information<br />Publish Frequency: semi-annually<br />Publish Method: Manual<br /><a target='_blank' href='https://tempe.gitbook.io/data-dictionary/1.08-crash-data' rel='nofollow ugc noopener noreferrer'>Data Dictionary</a></p>

Tags: accident, arizona, car-accidents, crash, cyclist, engineering-and-transportation, high-severity-traffic-crashes-pm-1-08, pedestrian, safe-and-secure-communities, tempe, transportation, vision-zero
Organization: City of Tempe
Vision Zero Dashboard

<div><div>This Vision Zero Dashboard shows City of Tempe crash data from crashes involving fatal or serious injuries from 2012 to the latest available data.<br /></div></div><div><br /></div><div><font size='3'>Vision Zero
is a traffic safety policy that takes an ethical approach towards achieving
safety for all road users. The goal is to achieve a reduction in the number of
fatal and serious injury crashes to zero in Tempe, because no loss of life is
acceptable.<br /></font><br /></div><div><i>Dashboard crash data includes:</i></div><div><ul><li>Violations<br /></li><li>Crash Types<br /></li><li>Alcohol / Drug Use<br /></li><li>Annual / Monthly Counts<br /></li><li>Age<br /></li><li>Gender<br /></li><li>Mode of Travel<br /></li><li>Lighting Condition<br /></li><li>Incident Junction Type<br /></li></ul></div>

Tags: accident, arizona, car-accidents, crash, cyclist, engineering-and-transportation, high-severity-traffic-crashes-pm-1-08, pedestrian, safe-and-secure-communities, tempe, transportation, vision-zero
Organization: City of Tempe
Park Districts

<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;'>Feature layer containing Park District information in the City of Sioux Falls, South Dakota.</span>

Tags: lincoln, minnehaha, park-districts, parks, sd, sioux-falls, south-dakota
Organization: City of Sioux Falls
Structures

<p style='margin-top:0px; margin-bottom:0.75rem; max-width:100%; 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 style='max-width:100%; display:inherit;'>Feature layer containing authoritative building structure information for Sioux Falls, South Dakota.</span></p>

Tags: lincoln, minnehaha, property, sd, sioux-falls, south-dakota, structure
Organization: City of Sioux Falls
Annual Self Insurance Fund Lawsuit Settlement Report

List of Case Names, Settlement Amounts, and Parties’ Demographic Information if available, for the prior fiscal year”. Demographic survey is not applicable to cases settled prior to Bill 19-21’s effective date 1/12/2022 NA = Not applicable, NR = Not responded, OO = Opt Out.The Settlement amount shown is for the entire matter, not for each individual plaintiff. Report updates annually.

Tags: county-attorney, law-suits, payout, settlements
Organization: Montgomery County of Maryland
High Impact Areas

Provides a visual representation of areas that are of heightened concern for SDOT Street Use, whether because of intense development and construction activity, increased scrutiny, increased safety concerns, or other reason. <br /><br />| Attibute Information: <a href='https://drive.google.com/open?id=1dKqQhXR9nB6ksMKs6TxyKrXpSKrePLoo' target='_blank'>High_Impact_Areas_OD.pdf</a><br /><br />| Update Cycle: As Needed  <br />| Contact Email: <a href='mailto:DOT_IT_GIS@seattle.gov' target='_blank'>DOT_IT_GIS@seattle.gov</a>  <br /><br />Common SDOT Queries: <br />| <a href='https://data-seattlecitygis.opendata.arcgis.com/datasets/high-impact-areas/data?where=STATUS%20like%20%27%25HUB%25%27' target='_blank'>SDOT HUBS</a> <br />STATUS = 'HUB'<br /><br /><a href='https://www.seattle.gov/transportation/projects-and-programs/programs/project-and-construction-coordination-office/construction-hub-coordination' target='_blank'>https://www.seattle.gov/transportation/projects-and-programs/programs/project-and-construction-coordination-office/construction-hub-coordination</a>

Tags: gis, high-impact-areas, sdot, seattle, seattle-gis-open-data, street-use, streets, transportation, wa
Organization: City of Seattle