cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1102813.10fu
title: SH1102813.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1102814.10fu
title: SH1102814.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1102817.10fu
title: SH1102817.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1102818.10fu
title: SH1102818.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1102822.10fu
title: SH1102822.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.j7kr44
title: Occurrence Download

description: A dataset containing 8572 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is one of (Europe, Asia, North America)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Continent derived from coordinates, Country derived from coordinates)",
 "OccurrenceStatus is Present",
 "TaxonKey is Haliaeetus albicilla (Linnaeus, 1758)",
 "Year 1901-1990"
 ]
}

 The dataset includes 8572 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012588-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rpby89
title: Occurrence Download

description: A dataset containing 47 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gladiolus pulcherrimus (G.J.Lewis) Goldblatt & J.C.Manning"
 ]
}

 The dataset includes 47 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012070-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7u8w6s
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((2.18481 51.00577,6.82010 51.00577,6.82010 52.86193,2.18481 52.86193,2.18481 51.00577))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Edmundsella pedata (Montagu, 1816)"
 ]
}

 The dataset includes 38 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046075-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5uv6bf
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "HasCoordinate is true",
 "TaxonKey is Swietenia macrophylla G.King",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 12 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031916-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8j66qm
title: Occurrence Download

description: A dataset containing 20462048 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Mexico"
 ]
}

 The dataset includes 20462048 records from 3013 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0185923-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57761/2g79-q705
title: Local Government & Immigrant Communities Survey

description: If you have questions or concerns, please contact Ron Nakao at ronbo@stanford.edu.
description: ICMA and Cornell University partnered on this survey to gain a better understanding of local government policies, programs, and other activities related to immigrant populations in their communities.
description: ICMA’s database of local governments includes approximately 11,000 U.S. municipalities and 2,900 U.S. counties with populations of 2,500 or greater, as well as a majority of municipalities and counties with populations under 2,500 ([https://icma.org/survey-research](<https://icma.org/survey-research>)).



The survey was distributed in the spring of 2018 to chief administrative officers of all municipalities with a population over 10,000 and counties of all populations across the United States. It was completed by 1,201 local governments, yielding an overall response rate of 17% with a 3% margin of error. Not all respondents answered every question.


description: Available documentation is contained in zip files labelled by survey year (see

***Supporting Files***). Documentation will always include the survey instrument; where available, documentation may also include codebooks and response rates.
DOI: 10.57761/4xd1-af08
title: Solar Survey of Local Governments

description: If you have questions or concerns, please contact Ron Nakao at ronbo@stanford.edu.
description: The Solar Survey of Local Governments collects data about the priorities and activities of U.S. local governments related to the adoption of solar energy. The U.S. Department of Energy provided support for the Solar Survey of Local Governments.
description: ICMA’s database of local governments includes approximately 11,000 U.S. municipalities and 2,900 U.S. counties with populations of 2,500 or greater, as well as a majority of municipalities and counties with populations under 2,500 ([https://icma.org/survey-research](<https://icma.org/survey-research>)).



**2011 Solar Survey of Local Governments:**



Detailed methodology is not available.



**2016 Solar Survey of Local Governments:**



With support from the U.S. Department of Energy, the International City/County Management Association (ICMA) conducted a survey to learn more about the priorities and activities of U.S. local governments related to the adoption of solar energy. Launched in the spring of 2016, this survey was conducted in follow-up to ICMA’s 2011 Solar Survey of Local Governments.



A paper questionnaire was mailed to the chief administrative officers of 2,507 local governments across the country. An online submission option was also made available. The sample frame included all jurisdictions that responded to ICMA’s 2011 Solar Survey of Local Governments.



Responses were received from 816 jurisdictions, yielding a response rate of 32.5%. With 816 cases, the results of this survey can be generalized to all U.S. cities and counties with a margin of error of +/- 3.3% at the 95% confidence level. In order to study changes in the solar landscape over the last five years, survey responses were compared among the 816 jurisdictions that responded to both the 2011 and 2016 surveys. Not all respondents answered each question. The number reporting (N) is included for each question and is the basis for the percentages shown.


description: Available documentation is contained in zip files labelled by survey year (see

***Supporting Files***). Documentation will always include the survey instrument; where available, documentation may also include codebooks and response rates.
DOI: 10.57761/g1q5-1e82
title: Local Government Sustainability Practices Survey

description: If you have questions or concerns, please contact Ron Nakao at ronbo@stanford.edu.
description: Topics in this national sustainability survey cover water, transportation, energy, recycling, recognition programs, and policy actions.
description: ICMA’s database of local governments includes approximately 11,000 U.S. municipalities and 2,900 U.S. counties with populations of 2,500 or greater, as well as a majority of municipalities and counties with populations under 2,500 ([https://icma.org/survey-research](<https://icma.org/survey-research>)).



**2010:**



The 2010 Local Government Sustainability Practices Survey was sent to 8,569 local governments. The survey response rate is 25.4%, with 2,176 local governments responding. The survey was developed with the input of ICMA’s Center for Sustainable Communities, the Center for Urban Innovation, Arizona State University’s Global Institute of Sustainability (ASU GIOS), the Alliance for Innovation, and others. Survey distribution was conducted through a collaboration of ICMA, ASU GIOS and the Sustainable Cities Network, a multi-jurisdictional partnership. The survey was provided in electronic and print formats because the local government response rate is both higher and more scientifically representative than for an electronic survey.



**2015:**



The 2015 Local Government Sustainability Practices Survey is a joint project of ICMA, the Sustainable Communities and Small Town and Rural Planning Divisions of the American Planning Association, Binghamton University, Cornell University, and the U.S. Department of Agriculture. The survey was administered in paper format via direct mail, with an online submission option. The survey was sent to 8,562 local governments and achieved a response rate of 22.2%, with 1,899 local governments responding.


description: Available documentation is contained in zip files labelled by survey year (see

***Supporting Files***). Documentation will always include the survey instrument; where available, documentation may also include codebooks and response rates.
DOI: 10.57761/ad7s-q446
title: palmerpenguins
DOI: 10.57761/j2y1-6q13
title: Synthetic Medicare Fee-For-Service Claims

description: Sample dataset for training webinar on Tuesday, April 16 2024.
description: See: [https://data.cms.gov/collection/synthetic-medicare-enrollment-fee-for-service-claims-and-prescription-drug-event](<https://data.cms.gov/collection/synthetic-medicare-enrollment-fee-for-service-claims-and-prescription-drug-event>)
DOI: 10.57761/8y6b-nw25
title: PMC patient notes

description: Sample dataset for training webinar on Tuesday, April 16 2024.
description: **PMC-Patients is a first-of-its-kind dataset consisting of 167k patient summaries extracted from case reports in PubMed Central (PMC), 3.1M patient-article relevance and 293k patient-patient similarity annotations defined by PubMed citation graph.**



**Dataset Description** \- \*\*Homepage:\*\* https://github.com/pmc-patients/pmc-patients

\- \*\*Repository:\*\* https://github.com/pmc-patients/pmc-patients

\- \*\*Paper:\*\* https://arxiv.org/pdf/2202.13876.pdf

\- \*\*Leaderboard:\*\* https://pmc-patients.github.io/

\- \*\*Point of Contact:\*\* zhengyun21@mails.tsinghua.edu.cn **Dataset Structure** This file contains all information about patients summaries in PMC-Patients, with the following columns:

- \`patient\_id\`: string. A continuous id of patients, starting from 0.
- \`patient\_uid\`: string. Unique ID for each patient, with format PMID-x, where PMID is the PubMed Identifier of the source article of the patient and x denotes index of the patient in source article.
- \`PMID\`: string. PMID for source article.
- \`file\_path\`: string. File path of xml file of source article.
- \`title\`: string. Source article title.
- \`patient\`: string. Patient summary.
- \`age\`: list of tuples. Each entry is in format \`(value, unit)\` where value is a float number and unit is in 'year', 'month', 'week', 'day' and 'hour' indicating age unit. For example, \`[[1.0, 'year'], [2.0, 'month']]\` indicating the patient is a one-year- and two-month-old infant.
- \`gender\`: 'M' or 'F'. Male or Female.
- \`relevant\_articles\`: dict. The key is PMID of the relevant articles and the corresponding value is its relevance score (2 or 1 as defined in the \`\`Methods'' section).
- \`similar\_patients\`: dict. The key is patient\_uid of the similar patients and the corresponding value is its similarity score (2 or 1 as defined in the \`\`Methods'' section).

<!-- -->



**Dataset Creation**

If you are interested in the collection of PMC-Patients and reproducing our baselines, please refer to [this repository\]\(https://github.com/zhao-zy15/PMC-Patients).
DOI: 10.57761/ejgy-k440
title: Harmonized Learning Outcomes
DOI: 10.57761/fs8t-qx65
title: Medicaid-Medicare crosswalk  (CMS 59429)

description: This is a crosswalk between 20% Medicare (DUA28777) and 100% Medicaid (DUA 56911). You need either an approved DUA RSCH-2023-59429 or approval for reusing RSCH-2023-59429 to access this data. Please attach the approval from CMS.
DOI: 10.57761/z6vp-ax30
title: Economic Development Survey

description: If you have questions or concerns, please contact Ron Nakao at ronbo@stanford.edu.
description: The Economic Development survey examines the economic development practices in local governments, including economic development funding activities, business retention, business attraction, small business development, accountability, and business incentives. Between 1984 and 2014, this survey was conducted once every 5 years.
description: ICMA’s database of local governments includes approximately 11,000 U.S. municipalities and 2,900 U.S. counties with populations of 2,500 or greater, as well as a majority of municipalities and counties with populations under 2,500 ([https://icma.org/survey-research](<https://icma.org/survey-research>)). The survey was distributed to chief administrative officers of local governments.


description: Available documentation is contained in zip files labelled by survey year (see

***Supporting Files***). Documentation will always include the survey instrument; where available, documentation may also include codebooks and response rates.



For most years, survey data was split across multiple files. Consequently, in Redivis, a single year of data is split into multiple tables. Users can `JOIN` the tables on shared variables (keys) like `IMISID`, `USTATE`, etc.
DOI: 10.57761/60b3-cv76
title: CREW Dataset

description: The Curated Regional Earthquake Waveforms (CREW) Dataset is a dataset of earthquake arrivals recorded at local and regional distances. CREW was assembled from millions of waveforms with quality control through semi-supervised learning. CREW includes 1.6 million waveforms that have global coverage. Each waveform consists of a 5 minute three component seismogram with labels for both a P and S arrival. CREW provides a high quality labelled waveform data set that can be used to develop and test machine learning models for the analysis of earthquakes recorded at regional distances.
description: Please see the example project:

[https://redivis.com/projects/k4k5-1hdesm2pc](<https://redivis.com/projects/k4k5-1hdesm2pc>)
DOI: 10.57761/txwb-bq83
title: Labor Management Relations Survey

description: If you have questions or concerns, please contact Ron Nakao at ronbo@stanford.edu.
description: The Labor Management Relations Survey examines the relationship between public employee unionization and local governments. The survey results provide information on bargaining issues, management rights, and how local governments negotiate with public employees.
description: ICMA’s database of local governments includes approximately 11,000 U.S. municipalities and 2,900 U.S. counties with populations of 2,500 or greater, as well as a majority of municipalities and counties with populations under 2,500 ([https://icma.org/survey-research](<https://icma.org/survey-research>)). The survey was distributed to chief administrative officers of local governments.


description: Available documentation is contained in zip files labelled by survey year (see

***Supporting Files***). Documentation will always include the survey instrument; where available, documentation may also include codebooks and response rates.



The 1988 survey data is split across multiple files. Consequently, in Redivis, a single year of data is split into multiple tables. Users can JOIN the tables on shared variables (keys) like IMISID, USTATE, etc.
DOI: 10.57761/c7tm-n460
title: V3 2021 Files: MarketScan Medicare Supplemental Database

description: We had to delete V3 of MarketScan Medicare Supplemental because of some unusual circumstances with the formats of some of the files we were sent (to prevent the duplication of records). V3.1 contains all of the info that was in V3, however V3.1 has 2022 data & a slightly different version of the 2021 data. The data on this page is the version of the 2021 data that was in V3. Our purpose in posting this is to enable researchers who completed analyses on V3 to replicate their work by combining the data here with the data on the main page.

FOR THE MAJORITY OF RESEARCHERS, however, we strongly recommend using V3.1, and ignoring this page, as it will be irrelevant for most research going forward. (Rule of thumb: If you are unsure whether you need the data on this page, then you probably don't need it.)
description: To recreate V3 of the data, use the data for 2020 and earlier that is on the [main MarketScan Medicare Supplemental page](<https://redivis.com/datasets/jv2x-25dm36err>), and combine it with the data on this page. That will give you the exact same data that was in V3.



The data documentation on the [main MarketScan Medicare Supplemental page](<https://redivis.com/datasets/jv2x-25dm36err>) also applies to the data on this page.