cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.7ewx6c
title: Occurrence Download

description: A dataset containing 1504 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eriocaulon decemflorum Maxim."
 ]
}

 The dataset includes 1504 records from 83 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0201347-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9fstoj
title: Occurrence Download

description: A dataset containing 234 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eugenia xalapensis (Kunth) DC.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 234 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097525-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.funaxf
title: Occurrence Download

description: A dataset containing 10574 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Momordica charantia L."
 ]
}

 The dataset includes 10574 records from 402 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065507-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15622741
title: Theoretical Exploration of Isomerization Pathways in H2SO4·HX (X = OH, Cl, Br) Complexes

description: The compressed archive includes the original output files from geometry optimization, IRC calculations, and  frequency calculations of isomers and transition states for three reaction systems: H₂SO₄ + HX (where X = OH, Cl, or Br). Calculations were carried out using Gaussian 16 at the B3LYP-D3BJ/aug-cc-pVTZ level of theory.
DOI: 10.5281/zenodo.15622742
title: Theoretical Exploration of Isomerization Pathways in H2SO4·HX (X = OH, Cl, Br) Complexes

description: The compressed archive includes the original output files from geometry optimization, IRC calculations, and  frequency calculations of isomers and transition states for three reaction systems: H₂SO₄ + HX (where X = OH, Cl, or Br). Calculations were carried out using Gaussian 16 at the B3LYP-D3BJ/aug-cc-pVTZ level of theory.
DOI: 10.15468/dl.bjs2cq
title: Occurrence Download

description: A dataset containing 806 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (India, China, Myanmar, Bhutan, Bangladesh, Pakistan, Afghanistan, Nepal)",
 "TaxonKey is Delias pasithoe (Linnaeus, 1758)"
 ]
}

 The dataset includes 806 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030462-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7fzhn5
title: Occurrence Download

description: A dataset containing 261 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amietia fuscigula (Duméril & Bibron, 1841)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((18.2339 -32.5266,18.1411 -32.657,18.1007 -32.7021,18.0224 -32.6366,17.8923 -32.6419,17.754 -32.8255,17.7723 -32.9007,20.509 -32.9007,20.509 -28.5786,16.2782 -28.5786,16.4358 -28.7202,16.726 -29.1235,17.1957 -30.3752,17.6655 -31.1743,18.1322 -31.7679,18.2495 -32.2638,18.2339 -32.5266))"
 ]
}

 The dataset includes 261 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030463-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vzjrv7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euglenophyceae",
 "HasCoordinate is true",
 "Country is one of (Poland)",
 "HasGeospatialIssue is false",
 "Year is greater than 2009"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0231729-210914110416597/datasets/export for details.
DOI: 10.15468/dl.enqzgb
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Callitriche stenoptera Lansdown"
 ]
}

 The dataset includes 29 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115684-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vthdfp
title: Occurrence Download

description: A dataset containing 2229 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Litoria darlingtoni (Loveridge, 1945)"
 ]
}

 The dataset includes 2229 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0308127-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.us6ews
title: Occurrence Download

description: A dataset containing 79 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Callostylis pulchella (Lindl.) S.C.Chen & Z.H.Tsi"
 ]
}

 The dataset includes 79 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115712-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8ppj2j
title: Occurrence Download

description: A dataset containing 181 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Helicops pastazae Shreve, 1934"
 ]
}

 The dataset includes 181 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0284841-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q869bv
title: Occurrence Download

description: A dataset containing 1013632 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Lauraceae)"
 ]
}

 The dataset includes 1013632 records from 1935 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0115681-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qcnrum
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sphaenorhynchus canga Araujo-Vieira, Lacerda, Pezzuti, Leite, Assis & Cruz, 2015"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019403-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z7tttf
title: Occurrence Download

description: A dataset containing 7889 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lysmata wurdemanni (Gibbes, 1850)"
 ]
}

 The dataset includes 7889 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019402-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dps3sc
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sphaenorhynchus canga Araujo-Vieira, Lacerda, Pezzuti, Leite, Assis & Cruz, 2015"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019404-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ryu4hy
title: Occurrence Download

description: A dataset listing the 3040 species recorded in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Canada",
 "Country is Canada"
 ]
 },
 {
 "or" : [
 "Locality ~Anticosti",
 "Locality ~*anticosti*"
 ]
 }
 ]
}

 The dataset's 3040 records were derived from 162 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019395-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3g2ssw
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:AAA8757"
 ]
}

 The dataset includes 20 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019405-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12706592
title: Multi-Objective Personnel Scheduling Problem with Multiple Qualification and Client's Satisfaction: Real Case
DOI: 10.5281/zenodo.12706593
title: Multi-Objective Personnel Scheduling Problem with Multiple Qualification and Client's Satisfaction: Real Case
DOI: 10.15468/dl.kgwjfs
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hippolyte wurdemanni Gibbes, 1850"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019408-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eek2zt
title: Occurrence Download

description: A dataset containing 11583 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rubus rosifolius Sm."
 ]
}

 The dataset includes 11583 records from 322 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019407-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eeuf96
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hippolysmata wurdemanni (Gibbes, 1850)"
 ]
}

 The dataset includes 51 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019409-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bp65rj
title: Occurrence Download

description: A dataset containing 1354 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Burkina Faso",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Vitellaria paradoxa C.F.Gaertn."
 ]
}

 The dataset includes 1354 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019410-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.4235193
title: Reliance on Science in Patenting

description: This dataset contains both front-page and in-text citations from patents to scientific articles. <em>If you use the data, please cite </em>these two articles: <strong>1. M. Marx, & A. Fuegi, "Reliance on Science: Worldwide Front-Page Patent Citations to Scientific Articles" (2020), <em>Strategic Management Journal 41(9):1572-1594</em>. (</strong>https://onlinelibrary.wiley.com/doi/full/10.1002/smj.3145<strong>) </strong> <strong>2. M. Marx & A. Fuegi, "Reliance on Science by Inventors: Hybrid Extraction of In-text Patent-to-Article Citations." NBER Working Paper 27987</strong>.(https://www.nber.org/papers/w27987) The datafile containing the citations is <strong>_pcs_mag_doi_pmid.tsv. </strong>DOIs and PMIDs provided where available. Each citation has the applicant/examiner flag, confidence score (1-10), and whether the reference was a) only on the front page, b) only in the body text, or c) in both. <strong>_data_description.pdf</strong> has full details. <strong>bodytextknowngood.tsv</strong> contains the known-good references for calculating recall. <strong>bodytextpatrefstopatents.tsv</strong> contains references to patents in the body text of patents. The remaining files redistribute the Microsoft Academic Graph. Please also cite Sinha, A, et al. 2015. Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW ’15 Companion). ACM, New York, NY, USA, 243-246. These data are under an Open Data Commons Attribution license (ODC-By); use them for anything as long as you cite us! Source code for front-page matches: https://github.com/mattmarx/reliance_on_science. Questions & feedback to support@relianceonscience.org<em>.</em>
description: {"references": ["Marx, Matt and Aaron Fuegi, \"Reliance on Science in Patenting: USPTO Front-Page Citations to Scientific Articles\" (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3331686)", "Sinha, Arnab, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June (Paul) Hsu, and Kuansan Wang. 2015. An Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW '15 Companion). ACM, New York, NY, USA, 243-246"]}
DOI: 10.5281/zenodo.4850763
title: Reliance on Science in Patenting

description: This dataset contains both front-page and in-text citations from patents to scientific articles through 2020. <em>If you use the data, please cite </em>these two articles: <strong>1. M. Marx, & A. Fuegi, "Reliance on Science: Worldwide Front-Page Patent Citations to Scientific Articles" (2020), <em>Strategic Management Journal 41(9):1572-1594</em>. (</strong>https://onlinelibrary.wiley.com/doi/full/10.1002/smj.3145<strong>) </strong> <strong>2. M. Marx & A. Fuegi, "Reliance on Science by Inventors: Hybrid Extraction of In-text Patent-to-Article Citations." NBER Working Paper 27987</strong>.(https://www.nber.org/papers/w27987) The datafile containing the citations is <strong>_pcs_mag_doi_pmid.tsv. </strong>DOIs and PMIDs provided where available. Each citation has the applicant/examiner flag, confidence score (1-10), and whether the reference was a) only on the front page, b) only in the body text, or c) in both. <strong>_data_description.pdf</strong> has full details. <strong>bodytextknowngood.tsv</strong> contains the known-good references for calculating recall. <strong>bodytextpatrefstopatents.tsv</strong> contains references to patents in the body text of patents. The remaining files redistribute the Microsoft Academic Graph. Please also cite Sinha, A, et al. 2015. Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW ’15 Companion). ACM, New York, NY, USA, 243-246. These data are under an Open Data Commons Attribution license (ODC-By); use them for anything as long as you cite us! Source code for front-page matches is at https://github.com/mattmarx/reliance_on_science and for in-text is at https://github.com/mattmarx/intextcitations. Questions & feedback to support@relianceonscience.org<em>.</em>
description: {"references": ["Marx, Matt and Aaron Fuegi, \"Reliance on Science in Patenting: USPTO Front-Page Citations to Scientific Articles\" (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3331686)", "Sinha, Arnab, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June (Paul) Hsu, and Kuansan Wang. 2015. An Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW '15 Companion). ACM, New York, NY, USA, 243-246"]}
DOI: 10.5281/zenodo.5080264
title: Reliance on Science in Patenting

description: This dataset contains both front-page and in-text citations from patents to scientific articles through 2020. <em>If you use the data, please cite </em>these two articles: <strong>1. M. Marx, & A. Fuegi, "Reliance on Science: Worldwide Front-Page Patent Citations to Scientific Articles" (2020), <em>Strategic Management Journal 41(9):1572-1594</em>. (</strong>https://onlinelibrary.wiley.com/doi/full/10.1002/smj.3145<strong>) </strong> <strong>2. M. Marx & A. Fuegi, "Reliance on Science by Inventors: Hybrid Extraction of In-text Patent-to-Article Citations." NBER Working Paper 27987</strong>.(https://www.nber.org/papers/w27987) The datafile containing the citations is <strong>_pcs_mag_doi_pmid.tsv. </strong>DOIs and PMIDs provided where available. Each citation has the applicant/examiner flag, confidence score (1-10), and whether the reference was a) only on the front page, b) only in the body text, or c) in both. <strong>_data_description.pdf</strong> has full details. <strong>bodytextknowngood.tsv</strong> contains the known-good references for calculating recall. <strong>bodytextpatrefstopatents.tsv</strong> contains references to patents in the body text of patents. The remaining files redistribute the Microsoft Academic Graph. Please also cite Sinha, A, et al. 2015. Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW ’15 Companion). ACM, New York, NY, USA, 243-246. These data are under an Open Data Commons Attribution license (ODC-By); use them for anything as long as you cite us! Source code for front-page matches is at https://github.com/mattmarx/reliance_on_science and for in-text is at https://github.com/mattmarx/intextcitations. Questions & feedback to support@relianceonscience.org<em>.</em>
description: {"references": ["Marx, Matt and Aaron Fuegi, \"Reliance on Science in Patenting: USPTO Front-Page Citations to Scientific Articles\" (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3331686)", "Sinha, Arnab, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June (Paul) Hsu, and Kuansan Wang. 2015. An Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW '15 Companion). ACM, New York, NY, USA, 243-246"]}
DOI: 10.5281/zenodo.5803985
title: Reliance on Science in Patenting

description: This dataset contains both front-page and in-text citations from patents to scientific articles through 2020. <em>If you use the data, please cite </em>these two articles: <strong>1. M. Marx, & A. Fuegi, "Reliance on Science: Worldwide Front-Page Patent Citations to Scientific Articles" (2020), <em>Strategic Management Journal 41(9):1572-1594</em>. (</strong>https://onlinelibrary.wiley.com/doi/full/10.1002/smj.3145<strong>) </strong> <strong>2. M. Marx & A. Fuegi, "Reliance on Science by Inventors: Hybrid Extraction of In-text Patent-to-Article Citations." </strong> <em>forthcoming in Journal of Economics and Management Strategy. </em>(http://doi.org/10.1111/jems.12455) The datafile containing the citations is <strong>_pcs_mag_doi_pmid.tsv. </strong>DOIs and PMIDs provided where available. Each citation has the applicant/examiner flag, confidence score (1-10), and whether the reference was a) only on the front page, b) only in the body text, or c) in both. <strong>_data_description.pdf</strong> has full details. <strong>bodytextknowngood.tsv</strong> contains the known-good references for calculating recall. The remaining files redistribute much of the *final* edition of the Microsoft Academic Graph (12/20/2021). Please also cite Sinha, A, et al. 2015. Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW ’15 Companion). ACM, New York, NY, USA, 243-246. Note that jif.zip, jcif.zip, and the OECD/wos-category crosswalks are derivatives of MAG and may not be updated through the end of 2021. These data are under an Open Data Commons Attribution license (ODC-By); use them for anything as long as you cite us! Source code for front-page matches is at https://github.com/mattmarx/reliance_on_science and for in-text is at https://github.com/mattmarx/intextcitations. Questions & feedback to support@relianceonscience.org<em>.</em> <strong><em>This work is sponsored by the Alfred P. Sloan Foundation grant #G-2021-16822.</em></strong>
description: {"references": ["Marx, Matt and Aaron Fuegi, \"Reliance on Science in Patenting: USPTO Front-Page Citations to Scientific Articles\" (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3331686)", "Sinha, Arnab, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June (Paul) Hsu, and Kuansan Wang. 2015. An Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW '15 Companion). ACM, New York, NY, USA, 243-246"]}
DOI: 10.5281/zenodo.10215169
title: Reliance on Science

description: This dataset contains patent-to-paper citations through 2022 as well as patent-paper pairs (through 2021).  If you use the data, please cite these two articles:
1. M. Marx & A. Fuegi, "Reliance on Science by Inventors: Hybrid Extraction of In-text Patent-to-Article Citations."  forthcoming in Journal of Economics and Management Strategy. (http://doi.org/10.1111/jems.12455)
2. M. Marx, & A. Fuegi, "Reliance on Science: Worldwide Front-Page Patent Citations to Scientific Articles" (2020), Strategic Management Journal 41(9):1572-1594. (https://onlinelibrary.wiley.com/doi/full/10.1002/smj.3145) 
The datafile containing the citations is _pcs_oa.csv.  Each citation has the applicant/examiner flag, confidence score (1-10), whether the reference was a) only on the front page, b) only in the body text, or c) in both, and an indicator for a self-citation (i.e., one of the authors is an inventor on the patent). There are two "shorthand" files, _pcs_countsbypatent.csv and _pcs_countsbypaper.csv, which collapse these to the paper and patent level by citation type.
The datafile containing the patent-paper pairs (PPPs) is _patent_paper_pairs.tsv. These are USPTO only, through 2021. Each PPP has a confidence score and the count of days between the publication of the paper and the filing of the patent. (If the patent is a continuation of another patent, the filing date of the original patent is used.) Also, when a paper is paired with multiple patents, an indicator variable reports whether those patents are continuations or otherwise identical. 
(The redistribution of OpenAlex is temporarily removed, but we hope to re-add it soon.)
The above is documented in greater detail in __reliance_on_science.pdf.
These data are provided under a Creative Commons Attribution Non-Commercial license. Please contact us regarding commercial use.  Questions & feedback to support@relianceonscience.org.
This work is sponsored by the Alfred P. Sloan Foundation grant #G-2021-16822.