cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5522/04/22109651.v1
title: CAP-2030 Nepal: Dataset on sociodemographic characteristics, phone and internet access and climate change awareness

description: The Stata data file "CAP_Demographics_Jumla_Kavre_recoded.dta” and equivalent excel file of the same name comprises data collected by adolescent secondary school students during a "Citizen Science" project in the district of Kavre in the central hills of Nepal during April 2022 and in the district of Jumla in the remote mountains of West Nepal during June 2022. The project was part of a CIFF-funded Children in All Policies 2030 (CAP2030) project. <br> The data were generated by the students using a mobile device data collection form developed using "Open Data Kit (ODK) Collect" electronic data collection platform by Kathmandu Living Labs (KLL) and University College London (UCL) for the purposes of this study. Researchers from KLL and UCL trained the adolescents to record basic socio-demographic information about themselves and their households including caste/ethnicity, religion, education, water sources, assets, household characteristics, and income sources. The form also asked about their access to mobile phones or other devices and internet and their concerns with respect to climate change. The resulting data describe the participants in the citizen science project, but their names and addresses have been removed. The app and the process of gathering the data are described in a paper entitled "Citizen science for climate change resilience: engaging adolescents to study climate hazards, biodiversity and nutrition in rural Nepal" submitted to Wellcome Open Research in Feb 2023. The data contributed to Tables 2 and 3 of this paper.
DOI: 10.5281/zenodo.6460275
title: Identified journal descriptor (JD), semantic type (ST), and MAUI keywords for PubMed/MEDLINE articles

description: The Journal descriptor (JD) and Semantic type (ST) of PubMed articles were identified using a tool, called Journal descriptor indexing (JDI). MAUI keywords are identified by the MAUI tool and they can be used as a complement to MESH terms, as MeSH keywords are not always available in all PubMed articles. The methods of building the datasets can be found in the two articles: "Author name disambiguation in MEDLINE based on journal descriptors and semantic types" and " Exploring author name disambiguation on PubMed-scale" The PubMed database used is the 2019 baseline version, the number of articles in the two datasets are as follows: $ wc -l pubmed-paper-jd-st.tsv <br> 29796281 pubmed-paper-jd-st.tsv $ wc -l pubmed-paper-maui-keywords.tsv <br> 26509210 pubmed-paper-maui-keywords.tsv<br>
DOI: 10.5281/zenodo.6460274
title: Identified journal descriptor (JD), semantic type (ST), and MAUI keywords for PubMed/MEDLINE articles

description: The Journal descriptor (JD) and Semantic type (ST) of PubMed articles were identified using a tool, called Journal descriptor indexing (JDI). MAUI keywords are identified by the MAUI tool and they can be used as a complement to MESH terms, as MeSH keywords are not always available in all PubMed articles. The methods of building the datasets can be found in the two articles: "Author name disambiguation in MEDLINE based on journal descriptors and semantic types" and " Exploring author name disambiguation on PubMed-scale" The PubMed database used is the 2019 baseline version, the number of articles in the two datasets are as follows: $ wc -l pubmed-paper-jd-st.tsv <br> 29796281 pubmed-paper-jd-st.tsv $ wc -l pubmed-paper-maui-keywords.tsv <br> 26509210 pubmed-paper-maui-keywords.tsv<br>
DOI: 10.5522/04/22109639
title: CAP-2030 Nepal: Dataset on plant diversity in Jumla district

description: The file plants_recorded_collapsed_edited.xls is derived from "CAP2030_Plant_Atlas_Jumla_2022-06-20-19-18-13_labelled.dta". It contains the number of times each of the species was recorded by the Citizen Scientists, separated into crop and wild plants. The data contributed to Annex 3 of this paper.
DOI: 10.5522/04/22109639.v1
title: CAP-2030 Nepal: Dataset on plant diversity in Jumla district

description: The file plants_recorded_collapsed_edited.xls is derived from "CAP2030_Plant_Atlas_Jumla_2022-06-20-19-18-13_labelled.dta". It contains the number of times each of the species was recorded by the Citizen Scientists, separated into crop and wild plants. The data contributed to Annex 3 of this paper.
DOI: 10.5281/zenodo.7618343
title: database with pre- intervention data of children with Dyslexia treated with VHSS

description: The database contains pre-intervention data of a group of 55 children with Developmental Dyslexia who were going to be treated with Visual-Hemisphere-Specific stimulation at IRCCS E. Medea. Data include z-scores for reading, spelling, phonological awareness, memory, rapid automatized naming and visual search tests. IQ scores are also reported as z-scores. All variables ending with _a are the weighed scores with respect to reading accuracy (i.e., the product of the score multiplied by its correlation with reading accuracy, as calculated on the total sample of 266 children). All variables ending with _s are the weighed scores with respect to reading speed (i.e., the product of the score multiplied by its correlation with reading speed, as calculated on the total sample of 266 children). .
description: {"references": ["Lorusso, M. L., & Toraldo, A. (2023). Revisiting Multifactor Models of Dyslexia: Do They Fit Empirical Data and What Are Their Implications for Intervention?. Brain Sciences, 13(2), 328."]}
DOI: 10.5281/zenodo.7618344
title: database with pre- intervention data of children with Dyslexia treated with VHSS

description: The database contains pre-intervention data of a group of 55 children with Developmental Dyslexia who were going to be treated with Visual-Hemisphere-Specific stimulation at IRCCS E. Medea. Data include z-scores for reading, spelling, phonological awareness, memory, rapid automatized naming and visual search tests. IQ scores are also reported as z-scores. All variables ending with _a are the weighed scores with respect to reading accuracy (i.e., the product of the score multiplied by its correlation with reading accuracy, as calculated on the total sample of 266 children). All variables ending with _s are the weighed scores with respect to reading speed (i.e., the product of the score multiplied by its correlation with reading speed, as calculated on the total sample of 266 children). .
description: {"references": ["Lorusso, M. L., & Toraldo, A. (2023). Revisiting Multifactor Models of Dyslexia: Do They Fit Empirical Data and What Are Their Implications for Intervention?. Brain Sciences, 13(2), 328."]}
DOI: 10.5522/04/22109618
title: CAP-2030 Nepal: Dataset on plant diversity in Jumla district l (raw data)

description: The Stata data file "CAP2030_Plant_Atlas_Jumla_2022-06-20-19-18-13_labelled.dta” and equivalent excel file of the same name comprises data collected by adolescent secondary school students during a "Citizen Science" project in the district of Jumla in the remote mountains of West Nepal during June 2022. The project was part of a CIFF-funded Children in All Policies 2030 (CAP2030) project. <br> The data were generated by the students using a mobile device data collection form developed using "Open Data Kit (ODK) Collect" electronic data collection platform by Kathmandu Living Labs (KLL) and University College London (UCL) for the purposes of this study. KLL and UCL adapted a CommCare form, and a printed 'Plant Atlas' developed by Bristol University and HERD International as part of the ‘Micropoll’ project, implemented in Jumla district between 2021 and 2022. Citizen science users of the app used the printed photographic 'Plant Atlas', which depicts different species of plant and their flowers and encodes information about its Nepali, English and Scientific names in a QR code. Data collectors had to scan the QR code of the plant once they had matched it to a species in their locale. They then went on to record any insects visiting the flowers and any pests of diseases affecting the plant. They took photographs of the plants and of pests or diseases. Researchers from KLL and UCL trained the adolescents to record the plants identified and associated pollinators or pests and take photos. The resulting datafile includes the latitude/longitude, name of the plant and category (crop, wild), date it was recorded, and the district. Links to photographs of the plant are included but require login to the KLL server. Users of the data may contact KLL (contact@kathmandulivinglabs.org) or UCL (n.saville@ucl.ac.uk) if access to photographs is required.<br> The data were generated as part of a learning exercise for students to raise awareness of biodiversity in their locale and to develop a sense of environmental stewardship. Since the students were using 10 android tablets to record information in a reasonably limited geographical area, the dataset may contain several copies of the same plant recorded by different individuals, so cannot be used for calculation of prevalence of species. Rather, the data serve to demonstrate the potential of citizen science methods with Nepali school students to record such information. The app and the process of gathering the data are described in a paper entitled "Citizen science for climate change resilience: engaging adolescents to study climate hazards, biodiversity and nutrition in rural Nepal" submitted to Wellcome Open Research in Feb 2023. The data contributed to Annex 3 of this paper.
DOI: 10.5522/04/22109618.v1
title: CAP-2030 Nepal: Dataset on plant diversity in Jumla district l (raw data)

description: The Stata data file "CAP2030_Plant_Atlas_Jumla_2022-06-20-19-18-13_labelled.dta” and equivalent excel file of the same name comprises data collected by adolescent secondary school students during a "Citizen Science" project in the district of Jumla in the remote mountains of West Nepal during June 2022. The project was part of a CIFF-funded Children in All Policies 2030 (CAP2030) project. <br> The data were generated by the students using a mobile device data collection form developed using "Open Data Kit (ODK) Collect" electronic data collection platform by Kathmandu Living Labs (KLL) and University College London (UCL) for the purposes of this study. KLL and UCL adapted a CommCare form, and a printed 'Plant Atlas' developed by Bristol University and HERD International as part of the ‘Micropoll’ project, implemented in Jumla district between 2021 and 2022. Citizen science users of the app used the printed photographic 'Plant Atlas', which depicts different species of plant and their flowers and encodes information about its Nepali, English and Scientific names in a QR code. Data collectors had to scan the QR code of the plant once they had matched it to a species in their locale. They then went on to record any insects visiting the flowers and any pests of diseases affecting the plant. They took photographs of the plants and of pests or diseases. Researchers from KLL and UCL trained the adolescents to record the plants identified and associated pollinators or pests and take photos. The resulting datafile includes the latitude/longitude, name of the plant and category (crop, wild), date it was recorded, and the district. Links to photographs of the plant are included but require login to the KLL server. Users of the data may contact KLL (contact@kathmandulivinglabs.org) or UCL (n.saville@ucl.ac.uk) if access to photographs is required.<br> The data were generated as part of a learning exercise for students to raise awareness of biodiversity in their locale and to develop a sense of environmental stewardship. Since the students were using 10 android tablets to record information in a reasonably limited geographical area, the dataset may contain several copies of the same plant recorded by different individuals, so cannot be used for calculation of prevalence of species. Rather, the data serve to demonstrate the potential of citizen science methods with Nepali school students to record such information. The app and the process of gathering the data are described in a paper entitled "Citizen science for climate change resilience: engaging adolescents to study climate hazards, biodiversity and nutrition in rural Nepal" submitted to Wellcome Open Research in Feb 2023. The data contributed to Annex 3 of this paper.
DOI: 10.5522/04/22109603
title: CAP-2030 Nepal: Dataset on climate-change related hazards

description: The Stata data file "CAP_Hazard_Kavre_Jumla_varnames.dta" and equivalent excel file of the same name comprises data collected by adolescent secondary school students during a "Citizen Science" project in the district of Kavre in the central hills of Nepal during April 2022 and in the district of Jumla in the remote mountains of West Nepal during June 2022. The project was part of a CIFF-funded Children in All Policies 2030 (CAP2030) project. <br> The data were generated by the students using a mobile device data collection form developed using "Open Data Kit (ODK) Collect" electronic data collection platform by Kathmandu Living Labs (KLL) and University College London (UCL) for the purposes of this study. Researchers from KLL and UCL trained the adolescents to record information, geolocation and/or photos about climate-change associated hazards including landslides, floods, extreme weather events and crop pests/failure. The resulting datafile includes the latitude/longitude, name, and category of the type of hazard, date the hazard event was recorded, date it occurred and the district. Links to photographs of the hazards are included but require login to the KLL server. Users of the data may contact KLL (contact@kathmandulivinglabs.org) or UCL (n.saville@ucl.ac.uk) if access to photographs is required.<br> The data were generated as part of a learning exercise for students to raise awareness of the impacts of climate change in their locale. Since the students were using 10 android tablets to record information in a reasonably limited geographical area, the dataset may contain several copies of the same event recorded by different individuals, so cannot be used for calculation of prevalence of hazard events. Rather, the data serve to demonstrate the potential of citizen science methods with Nepali school students to record such information. The app and the process of gathering the data are described in a paper entitled "Citizen science for climate change resilience: engaging adolescents to study climate hazards, biodiversity and nutrition in rural Nepal" submitted to Wellcome Open Research in Feb 2023. The data contributed to Table 4 of this paper.
DOI: 10.5522/04/22109603.v1
title: CAP-2030 Nepal: Dataset on climate-change related hazards

description: The Stata data file "CAP_Hazard_Kavre_Jumla_varnames.dta" and equivalent excel file of the same name comprises data collected by adolescent secondary school students during a "Citizen Science" project in the district of Kavre in the central hills of Nepal during April 2022 and in the district of Jumla in the remote mountains of West Nepal during June 2022. The project was part of a CIFF-funded Children in All Policies 2030 (CAP2030) project. <br> The data were generated by the students using a mobile device data collection form developed using "Open Data Kit (ODK) Collect" electronic data collection platform by Kathmandu Living Labs (KLL) and University College London (UCL) for the purposes of this study. Researchers from KLL and UCL trained the adolescents to record information, geolocation and/or photos about climate-change associated hazards including landslides, floods, extreme weather events and crop pests/failure. The resulting datafile includes the latitude/longitude, name, and category of the type of hazard, date the hazard event was recorded, date it occurred and the district. Links to photographs of the hazards are included but require login to the KLL server. Users of the data may contact KLL (contact@kathmandulivinglabs.org) or UCL (n.saville@ucl.ac.uk) if access to photographs is required.<br> The data were generated as part of a learning exercise for students to raise awareness of the impacts of climate change in their locale. Since the students were using 10 android tablets to record information in a reasonably limited geographical area, the dataset may contain several copies of the same event recorded by different individuals, so cannot be used for calculation of prevalence of hazard events. Rather, the data serve to demonstrate the potential of citizen science methods with Nepali school students to record such information. The app and the process of gathering the data are described in a paper entitled "Citizen science for climate change resilience: engaging adolescents to study climate hazards, biodiversity and nutrition in rural Nepal" submitted to Wellcome Open Research in Feb 2023. The data contributed to Table 4 of this paper.
DOI: 10.5281/zenodo.7660883
title: data set related to article Callous-Unemotional Traits and Intelligence in Children with Externalizing Behavioral Problems

description: This record contains raw data related to article Callous-Unemotional Traits and Intelligence in Children with Externalizing Behavioral Problems. Per la richiesta di accesso al file contattare il Dottore Pietro Muratori all'indirizzo email: pietro.muratori@fsm.unipi.it
DOI: 10.5281/zenodo.7660882
title: data set related to article Callous-Unemotional Traits and Intelligence in Children with Externalizing Behavioral Problems

description: This record contains raw data related to article Callous-Unemotional Traits and Intelligence in Children with Externalizing Behavioral Problems. Per la richiesta di accesso al file contattare il Dottore Pietro Muratori all'indirizzo email: pietro.muratori@fsm.unipi.it
DOI: 10.6084/m9.figshare.21155419.v6
title: Database of freshwater macroinvertebrate occurrences across Cuba

description: File “dataset_freshw_macroinv_cu.csv”: a dataset of georeferenced occurrence records of freshwater flatworms (Platyhelminthes: Tricladida), insects (Ephemeroptera, Odonata, Hemiptera, Trichoptera, Coleoptera, Diptera), crabs and shrimps (Crustacea: Decapoda), and mollusks (Mollusca) of Cuba. The information was collated from the scientific literature, unpublished field records, museum collections and online databases. The dataset is organized in 32 fields that contains information about the taxonomic classification of each recorded species; sex, and life stage of individuals; location, author and date of the record and a reference to the original data source. File “species_list.csv”: an updated species list of 590 species of tricladid flatworms (Tricladida, phylum Platyhelminthes), the insect orders Ephemeroptera (mayflies), Odonata (dragonflies and damselflies), Trichoptera (cadiflies) and freshwater Hemiptera, Coleoptera, Decapoda (crabs and shrimps, subphylum Crustacea) and Mollusca from Cuba created after a revision of the literature. Only binomial scientific names (genus + species) were considered, avoiding the use of subgenus and subespecies categories. This list was taken as taxonomic reference to search information on species occurrence records and compile the information stored in “dataset_freshw_macroinv_cu.csv”. File “fields_dataset.docx”: list of fields and definitions used in the dataset (file “dataset_freshw_macroinv_cu.csv”) of freshwater macroinvertebrates occurrence records from Cuba. Terms and definitions are according to Darwin Core standards (dc, http://www.tdwg.org/standards/450 ), Freshwater Core Template at Freshwater Biodiversity Data Portal (fwct, https://data.freshwaterbiodiversity.eu/) and Global Biodiversity Information Facility (gbif, https://www.gbif.org ). File “script_technical_validation.R”: R script to screen “dataset_freshw_macroinv_cu.csv” for georeferencing errors, incomplete information and redundant occurrence records. File “script_download_ocurr_gbif_inaturalist.R”: R script to download species occurrence records from GBIF and iNaturalist included in “dataset_freshw_macroinv_cu.csv”.
DOI: 10.34740/kaggle/dsv/5038183
title: COVID Vaccination in World (updated daily)
DOI: 10.5281/zenodo.7660920
title: Periodontal outcomes of impacted anterior maxillary teeth following surgical exposure and orthodontic alignment: a systematic review and meta-analysis

description: Dataset for all analyses
DOI: 10.5281/zenodo.7660919
title: Periodontal outcomes of impacted anterior maxillary teeth following surgical exposure and orthodontic alignment: a systematic review and meta-analysis

description: Dataset for all analyses
DOI: 10.6084/m9.figshare.21155419.v7
title: Database of freshwater macroinvertebrate occurrences across Cuba

description: File “occurrence_records.csv”: a dataset of georeferenced occurrence records of freshwater flatworms (Platyhelminthes: Tricladida), insects (Ephemeroptera, Odonata, Hemiptera, Trichoptera, Coleoptera, Diptera), crabs and shrimps (Crustacea: Decapoda), and mollusks (Mollusca) of Cuba. The information was collated from the scientific literature, unpublished field records, museum collections and online databases. The dataset is organized in 32 fields that contains information about the taxonomic classification of each recorded species; sex, and life stage of individuals; location, author and date of the record and a reference to the original data source. <br> File “species_list.csv”: an updated species list of 590 species of tricladid flatworms (Tricladida, phylum Platyhelminthes), the insect orders Ephemeroptera (mayflies), Odonata (dragonflies and damselflies), Trichoptera (cadiflies) and freshwater Hemiptera, Coleoptera, Decapoda (crabs and shrimps, subphylum Crustacea) and Mollusca from Cuba created after a revision of the literature. Only binomial scientific names (genus + species) were considered, avoiding the use of subgenus and subespecies categories. This list was taken as taxonomic reference to search information on species occurrence records and compile the information stored in “occurrence_records.csv”. <br> File “fields_database.docx”: list of fields and definitions used in the dataset (file “occurrence_records.csv”) of freshwater macroinvertebrates occurrence records from Cuba. Terms and definitions are according to Darwin Core standards (dc, http://www.tdwg.org/standards/450 ), Freshwater Core Template at Freshwater Biodiversity Data Portal (fwct, https://data.freshwaterbiodiversity.eu/) and Global Biodiversity Information Facility (gbif, https://www.gbif.org ). <br> File “scr_tech_val.R”: R script to screen “occurrence_records.csv” for georeferencing errors, incomplete information and redundant occurrence records. <br> File “scr_down_o_gbif_inat.R”: R script to download species occurrence records from GBIF and iNaturalist included in “occurrence_records.csv”.
DOI: 10.21335/nmdc-1518531676
title: Late-winter hydrographic and geochemical climatology of the Nordic Seas during 2000-2019

description: Observations of temperature, salinity, oxygen, nitrate, and phosphate during 2000-2019 are used to create a late-winter (February to April) climatology of the Nordic Seas. All observations were modified to represent late-winter conditions, when the mixed layer is deepest and densest, by homogenizing each hydrographic and geochemical profile from the local late-winter mixed-layer depth to the surface (Brakstad et al., 2023: https://doi.org/10.1016/j.pocean.2023.102981). The observations were then interpolated onto a three-dimensional grid with a regular horizontal resolution of 1/3˚ longitude and 1/8˚ latitude, and 46 vertical levels with intervals ranging from 10m near the surface to 250m at depth. The corresponding observational uncertainties were estimated based on the number of observations included in each grid cell and their variance. In general, the uncertainty decreases with depth due to the lower variance at depth and with increased number of observations. The final late-winter hydrographic and geochemical climatology and the associated uncertainties cover the domain 58.5-84.0˚N and 45.0˚W-45.0˚E.