cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e113569v1-176461
title: Replication data for: To Work or Not to Work? Child Development and Maternal Labor Supply

description: We estimate the effect of early child development on maternal labor
force participation. Mothers of poorly developing children may
remain at home to care for their children. Alternatively, mothers
may enter the labor force to pay for additional educational and
health resources. Which action dominates is the empirical question
we answer in this paper. We control for the potential endogeneity
of child development by using an instrumental variables approach,
uniquely exploiting exogenous variation in child development associated
with child handedness. We find that a one unit increase in
poor child development decreases maternal labor force participation
by approximately 10 percentage points. (JEL J13, J16, J22)
DOI: 10.5281/zenodo.15287850
title: BOSHLANG'ICH SINF O'QUVCHILARINING YOZMA NUTQINI SHAKLLANTIRISHNING ILIMIY-USLUBIY STRATEGIYASI
DOI: 10.5281/zenodo.15287851
title: BOSHLANG'ICH SINF O'QUVCHILARINING YOZMA NUTQINI SHAKLLANTIRISHNING ILIMIY-USLUBIY STRATEGIYASI
DOI: 10.5281/zenodo.15287860
title: USING METHODS IN TEACHING FOLK EPICS
DOI: 10.5281/zenodo.15287861
title: USING METHODS IN TEACHING FOLK EPICS
DOI: 10.5281/zenodo.15287868
title: INNOVATIVE TECHNOLOGIES OF INCREASING PROFESSIONAL COMPETENCE OF ENGLISH TEACHERS IN PRE SCHOOL ORGANIZATIONS
DOI: 10.5281/zenodo.15287869
title: INNOVATIVE TECHNOLOGIES OF INCREASING PROFESSIONAL COMPETENCE OF ENGLISH TEACHERS IN PRE SCHOOL ORGANIZATIONS
DOI: 10.5281/zenodo.13929898
title: Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite

description: Data necessary to reproduce figures in manuscript titled "Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite". Includes:



Compressed arrow dataset used to produce Figure S6 (subtlseq_dataset.tar)

Annotations used to process data (Hs_ensembl_lvl1_and_2.gtf and Hs_ensembl.gtf)

Processed data to produce Figures 3C and S2 (cB_ensembl_totRNAsubtlseq.csv.gz and cB_ensemblLvl1and2_totRNAsubtlseq.csv.gz, respectively).


Also includes supplemental tables of:



List of genes producing transcripts predicting to undergo nuclear decay (PUNDs; Supplemental_Table_PUNDs.csv)

Estimates for mature RNA synthesis, nuclear degradation, nuclear export, and cytoplasmic degradation rate constants from Ietswaart et al., 2024 total-cytoplasmic-nuclear TimeLapse-seq dataset (Supplemental_Table_NucCytoEsts.csv)

Estimates for premature RNA synthesis, premature RNA processing, and mature RNA degreadation obtained from EZbakR analysis of Ietswaart et al., 2024 total RNA TimeLapse-seq dataset (Supplemental_Table_PtoMests.csv).


Scripts to reproduce figures can be found at: https://github.com/isaacvock/EZbakRsuite_paper_code
DOI: 10.5281/zenodo.13946128
title: Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite

description: Data necessary to reproduce figures in manuscript titled "Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite". Includes:



Compressed arrow dataset used to produce Figure S6 (subtlseq_dataset.tar)

Annotations used to process data (Hs_ensembl_lvl1_and_2.gtf and Hs_ensembl.gtf)

Processed data to produce Figures 3C and S2 (cB_ensembl_totRNAsubtlseq.csv.gz and cB_ensemblLvl1and2_totRNAsubtlseq.csv.gz, respectively).

Simulated data originally used in bakR publication (Vock and Simon, 2023) used to make Figure 6 of EZbakR suite paper.


Also includes supplemental tables of:



List of genes producing transcripts predicting to undergo nuclear decay (PUNDs; Supplemental_Table_PUNDs.csv)

Estimates for mature RNA synthesis, nuclear degradation, nuclear export, and cytoplasmic degradation rate constants from Ietswaart et al., 2024 total-cytoplasmic-nuclear TimeLapse-seq dataset (Supplemental_Table_NucCytoEsts.csv)

Estimates for premature RNA synthesis, premature RNA processing, and mature RNA degreadation obtained from EZbakR analysis of Ietswaart et al., 2024 total RNA TimeLapse-seq dataset (Supplemental_Table_PtoMests.csv).


Scripts to reproduce figures can be found at: https://github.com/isaacvock/EZbakRsuite_paper_code
DOI: 10.5281/zenodo.13929897
title: Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite

description: Data necessary to reproduce figures in manuscript titled "Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite". Includes:



Compressed arrow dataset used to produce Figure S6 and S7 (subtlseq_data.tar.gz)

Compressed arrow dataset used to produce Figure 7 (subtlseq_perturbations_data.tar.gz)

eCLIP DDX3X peak calls from ENCODE used in Figure 7 (ENCFF901BYH_DDX3X_eCLIP.bed)

Annotations used to process data (Hs_ensembl_lvl1_and_2.gtf and Hs_ensembl.gtf)

Processed data to produce Figures 3C and S2 (cB_ensembl_totRNAsubtlseq.csv.gz and cB_ensemblLvl1and2_totRNAsubtlseq.csv.gz, respectively).

Simulated data originally used in bakR publication (Vock and Simon, 2023) used to make Figure 6 of EZbakR suite paper.

Processed data from the nanodynamo paper (Tarrerro et al. 2024) used to make Figure S9

Table from Ietswaart et al. 2024 of kinetic parameter estimates and PUND calls from that study (mmc2.xlsx)


Also includes supplemental tables of:



List of genes producing transcripts predicting to undergo nuclear decay (PUNDs; Supplemental_Table_PUNDs.csv)

Estimates for mature RNA synthesis, nuclear degradation, nuclear export, and cytoplasmic degradation rate constants from Ietswaart et al., 2024 total-cytoplasmic-nuclear TimeLapse-seq dataset (Supplemental_Table_NucCytoEsts.csv)

Estimates for premature RNA synthesis, premature RNA processing, and mature RNA degreadation obtained from EZbakR analysis of Ietswaart et al., 2024 total RNA TimeLapse-seq dataset (Supplemental_Table_PtoMests.csv).


Scripts to reproduce figures can be found at: https://github.com/isaacvock/EZbakRsuite_paper_code

Updated to include data necessary to reproduce new figures/panels in revisions.
DOI: 10.5281/zenodo.15287752
title: Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite

description: Data necessary to reproduce figures in manuscript titled "Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite". Includes:



Compressed arrow dataset used to produce Figure S6 and S7 (subtlseq_data.tar.gz)

Compressed arrow dataset used to produce Figure 7 (subtlseq_perturbations_data.tar.gz)

eCLIP DDX3X peak calls from ENCODE used in Figure 7 (ENCFF901BYH_DDX3X_eCLIP.bed)

Annotations used to process data (Hs_ensembl_lvl1_and_2.gtf and Hs_ensembl.gtf)

Processed data to produce Figures 3C and S2 (cB_ensembl_totRNAsubtlseq.csv.gz and cB_ensemblLvl1and2_totRNAsubtlseq.csv.gz, respectively).

Simulated data originally used in bakR publication (Vock and Simon, 2023) used to make Figure 6 of EZbakR suite paper.

Processed data from the nanodynamo paper (Tarrerro et al. 2024) used to make Figure S9

Table from Ietswaart et al. 2024 of kinetic parameter estimates and PUND calls from that study (mmc2.xlsx)


Also includes supplemental tables of:



List of genes producing transcripts predicting to undergo nuclear decay (PUNDs; Supplemental_Table_PUNDs.csv)

Estimates for mature RNA synthesis, nuclear degradation, nuclear export, and cytoplasmic degradation rate constants from Ietswaart et al., 2024 total-cytoplasmic-nuclear TimeLapse-seq dataset (Supplemental_Table_NucCytoEsts.csv)

Estimates for premature RNA synthesis, premature RNA processing, and mature RNA degreadation obtained from EZbakR analysis of Ietswaart et al., 2024 total RNA TimeLapse-seq dataset (Supplemental_Table_PtoMests.csv).


Scripts to reproduce figures can be found at: https://github.com/isaacvock/EZbakRsuite_paper_code

Updated to include data necessary to reproduce new figures/panels in revisions.
DOI: 10.23668/psycharchives.16305
title: Dataset for: Investigating Inhibition in German-Turkish Multilinguals: The Role of Language Dominance and Language Context in Bilingual and Trilingual Language Switching

description: Language production in multilinguals typically involves the simultaneous activation of multiple languages, leading to interference. The Inhibitory Control Model (ICM) posits that this interference is resolved through the inhibition of non-target languages, yet evidence of inhibition markers during language switching is often ambiguous. This study tested 24 balanced German-Turkish multilinguals (L1a German, L1b Turkish, L2 English) in cued picture naming and assessed n-2 language repetition costs as a marker of inhibition. These costs reflect persisting inhibition when switching back to a previously abandoned language (e.g., German-English-German) relative to a control condition (e.g., Turkish-English-German). We also asked participants to switch in all three pairwise language combinations in separate blocks, before and after the switching block with all three languages, to assess n-1 switch costs as a function of language pairing. Overall, we found n-2 language repetition costs, but these costs were not significantly stronger for the more dominant language(s). Moreover, all pairwise n-1 switch costs were symmetric, showing no evidence for differential control as a function of language dominance. Finally, we found that the intense switching experience with three languages produced a sustained relative downregulation of L1a German, suggesting proactive control of L1a German. Together, these findings provide support for inhibition being the main underlying mechanism of language control and question how language dominance relates to the strength of language control.
DOI: 10.34740/kaggle/dsv/11577766
title: Mahanagar Yatayat Transport Dataset
DOI: 10.15468/dl.s4ceuw
title: Occurrence Download

description: A dataset containing 8824 species occurrences available in GBIF matching the query:
{
 "GadmGid" : [
 "is IND.5.26_1"
 ]
}

 The dataset includes 8824 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000086-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7agg9f
title: Occurrence Download

description: A dataset containing 71 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Cameroon",
 "Geometry POLYGON((-10.23651 -4.48528,32.23651 -4.48528,32.23651 12.48528,-10.23651 12.48528,-10.23651 -4.48528))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plagiosiphon longituba (Harms) J.Léonard"
 ]
}

 The dataset includes 71 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000096-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15287169
title: Data Florist (Paper OM)
DOI: 10.5281/zenodo.15287170
title: Data Florist (Paper OM)
DOI: 10.15468/dl.exj3nr
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((114 34,123 34,123 39,114 39,114 34))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (January, March, February, April, May, June, July, August, September, October, November, December)",
 "TaxonKey is Hyphantria cunea (Drury, 1773)",
 "Year 2000-2025"
 ]
}

 The dataset includes 34 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000097-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6efqy6
title: Occurrence Download

description: A dataset containing 385 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (COL.31_2, COL.25_2, COL.26_2)",
 "TaxonKey is Cuniculus paca (Linnaeus, 1766)"
 ]
}

 The dataset includes 385 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000115-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15287888
title: Host identity drives the assembly of phytoplankton microbiomes across a continental scale environmental gradient

description: These datasets correspond with the following publication: 

P. Signe White1,2, Taryn Y. Broe1, Mirte C. M. Kuijpers1, Jonathan R. Dickey1 and Sara L. Jackrel1*

1Department of Ecology, Behavior, and Evolution, University of California San Diego

2Department of Integrative Biology, University of California Berkeley, Berkeley, CA

 

*Corresponding Author Email: sjackrel@ucsd.eduCorresponding Author Mailing Address: 

Sara L. Jackrel 

Department of Ecology, Behavior, and Evolution

University of California San Diego, 9500 Gilman Drive

La Jolla, CA, 92093-0116 USA

 

Abstract Host-associated microbiomes often promote host health, yet the key drivers of microbiome assembly and its consequences for host fitness remain unclear. We aimed to determine the relative roles of host identity versus the environment in driving host-microbiome assembly and the consequences of this variation in assembly for host fitness, which may help predict the resilience of host-associated microbiomes and host health amidst fluctuating environmental conditions. Here, we tracked microbiome assembly in association with initially axenic phytoplankton when incubated in seawater originating from four nearshore locations along a continental-scale environmental gradient of North America. Microbiome assembly was highly deterministic. Unexpectedly, host species identity was the overwhelming driver of microbiome community assembly despite continental scale variation in the environment. Although secondary to host identity, the environment was a significant driver of microbiome assembly for each species evaluated, which in turn conferred cascading effects on host fitness as shown by thermal tolerance growth assays. We also found that host-specific microbiomes had host-specific fitness effects, particularly under thermally stressful conditions. Overall, our results advance our understanding of microbiome assembly by empirically demonstrating that although variation among host microbiomes imparted by the local environment has significant implications for host health, the host species is the overwhelming driver of microbiome assembly regardless of wide scale variation in the environment.
DOI: 10.5281/zenodo.15287889
title: Host identity drives the assembly of phytoplankton microbiomes across a continental scale environmental gradient

description: These datasets correspond with the following publication: 

P. Signe White1,2, Taryn Y. Broe1, Mirte C. M. Kuijpers1, Jonathan R. Dickey1 and Sara L. Jackrel1*

1Department of Ecology, Behavior, and Evolution, University of California San Diego

2Department of Integrative Biology, University of California Berkeley, Berkeley, CA

 

*Corresponding Author Email: sjackrel@ucsd.eduCorresponding Author Mailing Address: 

Sara L. Jackrel 

Department of Ecology, Behavior, and Evolution

University of California San Diego, 9500 Gilman Drive

La Jolla, CA, 92093-0116 USA

 

Abstract Host-associated microbiomes often promote host health, yet the key drivers of microbiome assembly and its consequences for host fitness remain unclear. We aimed to determine the relative roles of host identity versus the environment in driving host-microbiome assembly and the consequences of this variation in assembly for host fitness, which may help predict the resilience of host-associated microbiomes and host health amidst fluctuating environmental conditions. Here, we tracked microbiome assembly in association with initially axenic phytoplankton when incubated in seawater originating from four nearshore locations along a continental-scale environmental gradient of North America. Microbiome assembly was highly deterministic. Unexpectedly, host species identity was the overwhelming driver of microbiome community assembly despite continental scale variation in the environment. Although secondary to host identity, the environment was a significant driver of microbiome assembly for each species evaluated, which in turn conferred cascading effects on host fitness as shown by thermal tolerance growth assays. We also found that host-specific microbiomes had host-specific fitness effects, particularly under thermally stressful conditions. Overall, our results advance our understanding of microbiome assembly by empirically demonstrating that although variation among host microbiomes imparted by the local environment has significant implications for host health, the host species is the overwhelming driver of microbiome assembly regardless of wide scale variation in the environment.
DOI: 10.15468/dl.yq8p52
title: Occurrence Download

description: A dataset containing 4044 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "Geometry POLYGON((118 29.5,122.5 29.5,122.5 32.5,118 32.5,118 29.5))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Anura",
 "Year 1990-2024"
 ]
}

 The dataset includes 4044 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000125-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wjc346
title: Occurrence Download

description: A dataset containing 316 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 {
 "or" : [
 "InstitutionKey is not null",
 "CollectionKey is not null"
 ]
 },
 "BasisOfRecord is one of (Specimen, Fossil, Material sample, Living Specimen, Material citation)"
 ]
 },
 {
 "and" : [
 "RecordedBy is one of (gauba, gauba, e., gauba,e., gauba e., gauba e, gauba, e, gauba,d.e., gauba, erwin, gauba, j.e., gauba., gauba, e. ?, gauba, erwin; sabeti, habib allah, gauba, e.; sabeti, gauba & sabeti 1939, gauba,e. s.n. [1938-05-30], gauba,e. s.n. [1940-06-25], gauba ?, e., gauba & behboudi,e. plantae iranicae 119, gauba & behboudi,e. 491, gauba,e. 37)",
 "Country is one of (Iran (Islamic Republic of))"
 ]
 }
 ]
}

 The dataset includes 316 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000133-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sxssur
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Saruma henryi Oliv."
 ]
}

 The dataset includes 15 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000131-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yssdg6
title: Occurrence Download

description: A dataset containing 5923 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Australian Coral Ecoregions"
 ]
}

 The dataset includes 5923 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000136-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nmjeau
title: Occurrence Download

description: A dataset containing 9793 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Adansonia digitata L.",
 "Year 1882-2025"
 ]
}

 The dataset includes 9793 records from 160 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000140-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.75nwjs
title: Occurrence Download

description: A dataset containing 44265 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 PRINTF('%04d-%02d-%02d', "year", "month", "day") yearmonthday,
 countrycode countrycode,
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, countrycode, PRINTF('%04d-%02d-%02d', "year", "month", "day"))) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, countrycode, PRINTF('%04d-%02d-%02d', "year", "month", "day"))) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, countrycode, PRINTF('%04d-%02d-%02d', "year", "month", "day"))) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, countrycode, PRINTF('%04d-%02d-%02d', "year", "month", "day"))) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, countrycode, PRINTF('%04d-%02d-%02d', "year", "month", "day"))) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, countrycode, PRINTF('%04d-%02d-%02d', "year", "month", "day"))) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode = 'VN'
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.taxonkey = 6 OR occurrence.acceptedtaxonkey = 6 OR occurrence.kingdomkey = 6 OR occurrence.phylumkey = 6 OR occurrence.classkey = 6 OR occurrence.orderkey = 6 OR occurrence.familykey = 6 OR occurrence.genuskey = 6 OR occurrence.specieskey = 6)
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL AND occurrence."month" IS NOT NULL AND occurrence."day" IS NOT NULL AND occurrence.hascoordinate = TRUE)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 PRINTF('%04d-%02d-%02d', "year", "month", "day"),
 occurrence.countrycode

 The dataset's 44265 records were derived from 186 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000146-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eck59s
title: Occurrence Download

description: A dataset containing 72363 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is ICN - Universidad Nacional de Colombia"
 ]
}

 The dataset includes 72363 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000150-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qqdcd8
title: Occurrence Download

description: A dataset containing 330 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Ambystoma mexicanum (Shaw & Nodder, 1798)"
 ]
}

 The dataset includes 330 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000142-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.