cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/d5b7e8ec7e83ab089f90aa6336517be6
title: Survey of Family Forest Owners Regarding Invasive Insects in the Connecticut River Watershed 2017

description: Forest insects have significant direct impacts on forest ecosystems; they are also generating new risks, uncertainties, and opportunities for forest landowners. Our research objective is to understand: (1) whether and how insect infestations are shifting land-use regimes in New England by altering human decision-making, (2) how these changes to human decisions may affect regional forest ecosystems and the provisioning of select ecosystem services, and (3) how subsequent changes to forest ecosystems, in turn, affect landowners. The dataset is a result of gathering information from a random sample of family forest owners (FFOs) in the Connecticut River Watershed; FFOs own approximately half of the private forestland in the region. We collected information on characteristics and perceptions of these FFOs as well as their intentions for their land if faced with the presence or threat of invasive forest insects. To better understand FFO intentions, contingent behavior questions populate the conjoint analysis format of the questionnaire. These are the foundational data that form our further efforts to simulate the impacts of insect dynamics and landowner behavior on regional forest ecosystems, including forest carbon stores, forest structure and composition, and timber yields. One of our overarching hypotheses is that forest land-use change in response to insects will have greater near-term ecological consequences than climate change or insects by themselves.
DOI: 10.7910/dvn/qkamhr/jppjlc
title: M242_data_UPC_2019_03.xlsx

description: Data for UPC - column names according to http://unpaywall.org/data-format
DOI: 10.7910/dvn/qkamhr/pybm7u
title: M242_data_UB_2019_03.xlsx

description: Data for UB - column names according to http://unpaywall.org/data-format
DOI: 10.25386/genetics.9936284
title: Supplemental Material for Wisser et al., 2019

description: Supplementary Methods, Tables, Figures, and Files.
DOI: 10.25386/genetics.9936284.v1
title: Supplemental Material for Wisser et al., 2019

description: Supplementary Methods, Tables, Figures, and Files.
DOI: 10.5281/zenodo.630132
title: Mammal trapping grid data for the SAFE Project

description: <b>Description: </b>This zipfile contains point grids used for mammal live trapping and camera trapping at the SAFE Project. There are 46 grids, each one consisting of a 4 by 12 grid of points, spread across blocks of old growth forest, logged forest and oil palm.<br><br>The grids were established by Ollie Wearn and processed by David Orme to convert the original GIS files to a single dataset using the UTM 50N projetion. Details of the geoprocessing can be found here: https://www.safeproject.net/dokuwiki/safe_gis/mammaltraps.<b>Project: </b>This dataset was collected as part of the following SAFE research project: <b>SAFE CORE DATA</b><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available here<b>Files: </b>This dataset consists of 2 files: SAFE_Mammal_traps_metadata.xlsx, SAFE_MammalTraps_UTM50N_WGS84.zip<b>SAFE_Mammal_traps_metadata.xlsx</b>This file only contains metadata for the files below<b>SAFE_MammalTraps_UTM50N_WGS84.zip</b>Description: Shapefile containing 2208 point locations of trapping grid points across SAFE locationsThis file contains 1 data tables:<b>Feature properties</b> (described in worksheet Properties)Description: Field descriptions for shapefile propertiesNumber of fields: 8Number of data rows: Unavailable (table metadata description only).Fields: <b>GPS_Ident</b>: Name of trap point in original GPS ident (Field type: location)<b>Altitude</b>: GPS Elevation of point (Field type: numeric)<b>Project</b>: Project name - all values are 'SAFE' (Field type: categorical)<b>Site</b>: SAFE Project main block identity for point (Field type: categorical)<b>Station</b>: Identical to GPS_Ident (Field type: location)<b>Location</b>: Specific location within main block (Field type: categorical)<b>Block</b>: Sub-block number or location within main site block (Field type: categorical)<b>Number</b>: Trap point number - each grid has 48 points (Field type: numeric)<b>Date range: </b>2010-10-01 to 2019-10-01<b>Latitudinal extent: </b>4.6348 to 4.7539<b>Longitudinal extent: </b>116.9471 to 117.6254
DOI: 10.7910/dvn/0q5rgo/hoezbd
title: data.tab

description: :unav
DOI: 10.7910/dvn/0q5rgo/wmg7hi
title: Stata_do_file_RR_Submission.do

description: :unav
DOI: 10.17632/47bxwyhnvp.1
title: Data for: Morphological and optical features of superposition compound eye in Monochamus alternatus Hope (Coleoptera: Cerambycidae)

description: In order to improve our understanding of visual behavior and its mechanism in M. alternatus, the compound eye external morphology and fine structures were observed with a scanning electron microscope (SEM), a transmission electron microscope (TEM) and light microscopy (LM). This descriptive work and mapping provides a basis for future investigation of M. alternatus behavior.
DOI: 10.7910/dvn/biifaj/g3zqi4
title: exported_data_occupancy.tab

description: Values of the different sensors and ground truth value for occupancy detection. Generated by pandas dataframe.
DOI: 10.5281/zenodo.3490564
title: Mammal trapping grid data for the SAFE Project

description: <b>Description: </b>This zipfile contains point grids used for mammal live trapping and camera trapping at the SAFE Project. There are 46 grids, each one consisting of a 4 by 12 grid of points, spread across blocks of old growth forest, logged forest and oil palm.<br><br>The grids were established by Ollie Wearn and processed by David Orme to convert the original GIS files to a single dataset using the UTM 50N projetion. Details of the geoprocessing can be found here: https://www.safeproject.net/dokuwiki/safe_gis/mammaltraps.<b>Project: </b>This dataset was collected as part of the following SAFE research project: <b>SAFE CORE DATA</b><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available here<b>Files: </b>This dataset consists of 2 files: SAFE_Mammal_traps_metadata.xlsx, SAFE_MammalTraps_UTM50N_WGS84.zip<b>SAFE_Mammal_traps_metadata.xlsx</b>This file only contains metadata for the files below<b>SAFE_MammalTraps_UTM50N_WGS84.zip</b>Description: Shapefile containing 2208 point locations of trapping grid points across SAFE locations<b>Date range: </b>2010-10-01 to 2019-10-01<b>Latitudinal extent: </b>4.6348 to 4.7539<b>Longitudinal extent: </b>116.9471 to 117.6254
DOI: 10.5519/qd.pwpnqyad
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4462743 records)
DOI: 10.5281/zenodo.3490082
title: Dataset and scripts for "Sentiment Analysis over Collaborative Relationships in Open Source Software Projects"

description: Dataset and scripts for "Sentiment Analysis over Collaborative Relationships in Open Source Software Projects". README is included in the files
DOI: 10.5281/zenodo.3490297
title: A Novel Framework to Harmonise Satellite Data Series for Climate Applications: Matchups, Calibration Parameters and Residuals

description: The datasets included with this archive supplement the journal article: Giering, R.; Quast, R.; Mittaz, J.P.D.; Hunt, S.E.; Harris, P.M.; Woolliams, E.R.; Merchant, C.J. A Novel Framework to Harmonise Satellite Data Series for Climate Applications. <em>Remote Sens. 2019</em>, <strong>11</strong>, 1002. doi:10.3390/rs11091002. The archive includes a README file with further explanations.
description: {"references": ["Giering, R.; Quast, R.; Mittaz, J.P.D.; Hunt, S.E.; Harris, P.M.; Woolliams, E.R.; Merchant, C.J. A Novel Framework to Harmonise Satellite Data Series for Climate Applications. Remote Sens. 2019, 11, 1002"]}
DOI: 10.5281/zenodo.3490298
title: A Novel Framework to Harmonise Satellite Data Series for Climate Applications: Matchups, Calibration Parameters and Residuals

description: The datasets included with this archive supplement the journal article: Giering, R.; Quast, R.; Mittaz, J.P.D.; Hunt, S.E.; Harris, P.M.; Woolliams, E.R.; Merchant, C.J. A Novel Framework to Harmonise Satellite Data Series for Climate Applications. <em>Remote Sens. 2019</em>, <strong>11</strong>, 1002. doi:10.3390/rs11091002. The archive includes a README file with further explanations.
description: {"references": ["Giering, R.; Quast, R.; Mittaz, J.P.D.; Hunt, S.E.; Harris, P.M.; Woolliams, E.R.; Merchant, C.J. A Novel Framework to Harmonise Satellite Data Series for Climate Applications. Remote Sens. 2019, 11, 1002"]}
DOI: 10.5281/zenodo.3490937
title: Interaction-Based Behavioral Analysis in Twitter Social Network

description: Literature studies usually use data sets consisting of data collected from many different metrics and user counts collected over different time periods. The data set used in this article was formed using completely up-to-date data obtained as a result of metrics measured in terms of scope and efficiency, sufficient and effective user counts, and filtering processes. To classify users correctly and make the classification performance high—in addition to parameters used in the literature such as tweets, account age, follower rank, average retweets and average likes—other parameters such as diameter, density, reciprocity, centralization and modularity were used. These metrics are the parameters that focus on a different area to reveal many aspects in which social network users interact. The data used to create the data set was collected from Twitter. The metric data forming the data set was extracted using Twitter Rest API V1.1 supporting search/tweet endpoints by means of the SocialBlade and Netlytic platforms.
DOI: 10.5281/zenodo.3490938
title: Interaction-Based Behavioral Analysis in Twitter Social Network

description: Literature studies usually use data sets consisting of data collected from many different metrics and user counts collected over different time periods. The data set used in this article was formed using completely up-to-date data obtained as a result of metrics measured in terms of scope and efficiency, sufficient and effective user counts, and filtering processes. To classify users correctly and make the classification performance high—in addition to parameters used in the literature such as tweets, account age, follower rank, average retweets and average likes—other parameters such as diameter, density, reciprocity, centralization and modularity were used. These metrics are the parameters that focus on a different area to reveal many aspects in which social network users interact. The data used to create the data set was collected from Twitter. The metric data forming the data set was extracted using Twitter Rest API V1.1 supporting search/tweet endpoints by means of the SocialBlade and Netlytic platforms.
DOI: 10.7910/dvn/9gpuwh/fzdnmw
title: morocco_data.tab

description: Weekly influenza activity and influenza-related Google search frequencies in Morocco from September 6, 2015 to December 31, 2017.
DOI: 10.7910/dvn/9gpuwh/lsfqtk
title: south_africa_data.tab

description: Weekly influenza activity and influenza-related Google search frequencies in South Africa from January 8, 2012 to December 3, 2017.
DOI: 10.7910/dvn/9gpuwh/pdz83x
title: ghana_data.tab

description: Weekly influenza activity and influenza-related Google search frequencies in Ghana from January 8, 2012 to December 31, 2017.
DOI: 10.7910/dvn/9gpuwh/zpnjcl
title: algeria_data.tab

description: Weekly influenza activity and influenza-related Google search frequencies in Algeria from January 8, 2012 to January 3, 2016.
DOI: 10.5519/qd.d7s91f7g
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (63 records)
DOI: 10.7910/dvn/axd0cz/2zpsxq
title: Microcredit_BL_mini_anonym.tab

description: :unav
DOI: 10.7910/dvn/axd0cz/51mamf
title: table_names_key.tab

description: :unav
DOI: 10.5281/zenodo.3490749
title: GWAS on self-reported hearing difficulty in the UK Biobank

description: The dataset contains results of two genome-wide association studies for age-related hearing impairment (ARHI)-related traits as described in the following publication <em>Wells HRR, Freidin MB, Zainul Abidin FN, Payton A, Dawes P, Munro KJ, Morton CC, Moore DR, Dawson SJ, Williams FMK. GWAS Identifies 44 Independent Associated Genomic Loci for Self-Reported Adult Hearing Difficulty in UK Biobank. Am J Hum Genet. 2019 Oct 3;105(4):788-802. doi: 10.1016/j.ajhg.2019.09.008. Epub 2019 Sep 26.</em> Please cite the article if using this dataset. Two files provide summary statistics for discovery analysis of <em><strong>Hearing difficulty (HD) </strong></em>and <em><strong>Hearing aid use (HAID)</strong></em> phenotypes for individuals of European descent from UK Biobank. <strong>Acknowledgements</strong> The research was carried out using the UK Biobank Resource under application number 11516. H.R.R.W. is funded by a PhD Studentship Grant, S44, from Action on Hearing Loss. The study was also supported by funding from NIHR UCLH BRC Deafness and Hearing Problems Theme, a grant from MED_EL, and the NIHR Manchester Biomedical Research Centre. The English Longitudinal Study of Aging is jointly run by University College London, Institute for Fiscal Studies, University of Manchester, and National Centre for Social Research. Genetic analyses have been carried out by UCL Genomics and funded by the Economic and Social Research Council and the National Institute on Aging. Data governance was provided by the METADAC data access committee, funded by ESRC, Wellcome, and MRC (2015-2018: Grant Number MR/N01104X/1 2018-2020: Grant Number ES/S008349/1). TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. We would like to thank all the participants of UK Biobank, English Longitudinal Study of Aging, and TwinsUK. <strong>Column headers:</strong> SNP, SNP rsID CHR, chromosome BP, genomic position (GRCh37 build) ALLELE1, effect allele (coded as "1") ALLELE0, reference allele (coded as "0") A1FREQ, effect allele frequency INFO, imputation quality BETA, effect size of effect allele SE: standard error of effect size P, P-value of association (without GC correction)
DOI: 10.5281/zenodo.3490750
title: GWAS on self-reported hearing difficulty in the UK Biobank

description: The dataset contains results of two genome-wide association studies for age-related hearing impairment (ARHI)-related traits as described in the following publication <em>Wells HRR, Freidin MB, Zainul Abidin FN, Payton A, Dawes P, Munro KJ, Morton CC, Moore DR, Dawson SJ, Williams FMK. GWAS Identifies 44 Independent Associated Genomic Loci for Self-Reported Adult Hearing Difficulty in UK Biobank. Am J Hum Genet. 2019 Oct 3;105(4):788-802. doi: 10.1016/j.ajhg.2019.09.008. Epub 2019 Sep 26.</em> Please cite the article if using this dataset. Two files provide summary statistics for discovery analysis of <em><strong>Hearing difficulty (HD) </strong></em>and <em><strong>Hearing aid use (HAID)</strong></em> phenotypes for individuals of European descent from UK Biobank. <strong>Acknowledgements</strong> The research was carried out using the UK Biobank Resource under application number 11516. H.R.R.W. is funded by a PhD Studentship Grant, S44, from Action on Hearing Loss. The study was also supported by funding from NIHR UCLH BRC Deafness and Hearing Problems Theme, a grant from MED_EL, and the NIHR Manchester Biomedical Research Centre. The English Longitudinal Study of Aging is jointly run by University College London, Institute for Fiscal Studies, University of Manchester, and National Centre for Social Research. Genetic analyses have been carried out by UCL Genomics and funded by the Economic and Social Research Council and the National Institute on Aging. Data governance was provided by the METADAC data access committee, funded by ESRC, Wellcome, and MRC (2015-2018: Grant Number MR/N01104X/1 2018-2020: Grant Number ES/S008349/1). TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. We would like to thank all the participants of UK Biobank, English Longitudinal Study of Aging, and TwinsUK. <strong>Column headers:</strong> SNP, SNP rsID CHR, chromosome BP, genomic position (GRCh37 build) ALLELE1, effect allele (coded as "1") ALLELE0, reference allele (coded as "0") A1FREQ, effect allele frequency INFO, imputation quality BETA, effect size of effect allele SE: standard error of effect size P, P-value of association (without GC correction)
DOI: 10.7910/dvn/axd0cz/4fcedn
title: OutcomeConstruction_baseline_June2019.do

description: :unav
DOI: 10.7910/dvn/axd0cz/7odh4k
title: Microcredit_MS_anonym.tab

description: :unav
DOI: 10.7910/dvn/axd0cz/ewhdv6
title: MatchingE1_updated.tab

description: :unav
DOI: 10.7910/dvn/axd0cz/jgp1tq
title: Microcredit_EL_mini_anonym.tab

description: :unav
DOI: 10.7910/dvn/axd0cz/slrayd
title: READ ME Verifying the internal validity of a flagship RCT - A rejoinder.docx

description: :unav
DOI: 10.5066/p9cfxhgt
title: Crosswalk Table Between NHDPlus V2.1 and its Accompanying Watershed Boundary Dataset Snapshot of 12-Digit Hydrologic Units

description: A crosswalk table between NHDPlus version 2.1 flowlines (using the unique field COMID) and the Watershed Boundary Dataset (WBD) 12-digit-hydrologic units (HU-12) is provided for the 48 contiguous United States. The crosswalk table provides a WBD HU-12 assignment for every networked flowline in the NHDPlus. In this way, the network developed for navigation and modeling, NHDPlus, is aligned with accounting units of the WBD HU-12s to the extent possible given the assumptions that were made in creating each. A crosswalk table for NHDPlus isolated sinks was produced by a simple overlay process where the sinks were assigned HU-12 values based on their position relative to the WBD snapshot HU-12s. This table was integrated with the flowline associations into one crosswalk table for both feature types. There is good alignment between aggregated NHDPlus catchments and WBD HU-12 units in many locations. These are areas where the flows and chemical or nutrient loads that are accumulated leave the HU-12 at a single outlet and are passed down to the next HU-12 downstream (or to the coast) as is assumed in the WBD model. A second pass through the data was made to account for any secondary outlet from each HU-12. The location of a secondary outlet with a significant drainage from that HU was identified in the alignment with NHDPlus. This resulted in a reduction in areas of mismatch as well as an improved crosswalk table. The crosswalk table should be used with caution in areas where efforts could be made to improve the data. For example, with medium-resolution NHD, a better definition of flow direction of the flowlines in Southern Florida would result in more flowlines being included in the "networked" flowlines with catchments, and that, in turn, would result in better alignment between NHDPlus catchments and HU-12s. Correcting errors in either the medium-resolution NHD or WBD would improve the alignment between the two datasets. Both datasets, NHDPlus and the Watershed Boundary Dataset can be used as building blocks for stream?water?quality modeling analysis and reporting. Each has its strengths and weaknesses. Care and an understanding of these networks should be considered when employing appropriate applications.
DOI: 10.7910/dvn/axd0cz/3jb1ne
title: Analysis_June2019.do

description: :unav
DOI: 10.7910/dvn/axd0cz/9yeoqn
title: OutcomeConstruction_endline_June2019.do

description: :unav
DOI: 10.7910/dvn/axd0cz/anilfu
title: SupplementaryAnalysis_June2019.do

description: :unav
DOI: 10.7910/dvn/axd0cz/m1ugrk
title: outreg.ado

description: :unav
DOI: 10.25345/c59671
title: MassIVE MSV000084456 - UHPLC-MS data of organic extract from red macroalga Asparagopsis taxiformis
title: UHPLC-MS data of organic extract from red macroalga Asparagopsis taxiformis collected from Guam
DOI: 10.5066/p9iqhj06
title: Stormwater-quality data for lined permeable pavement systems in Madison, WI, from September 2016 through July 2018

description: This dataset describes water-quality data measured from the parking lot influent and underdrain and overflow effluent from the porous asphalt, pervious concrete, and permeable interlocking concrete paver test plots in Madison, Wisconsin, USA. Data include precipitation statistics; influent, overflow, and underdrain volumes; and concentrations and loads of total and dissolved forms of solids, nutrients, chloride, metals, and bacteria. Samples were collected in September 2016 through July 2018. These data are interpreted in the Journal of Environmental Management.
DOI: 10.5519/qd.ennnvog3
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (17 records)
DOI: 10.7910/dvn/axd0cz/83ay1f
title: sales_replication.png

description: :unav
DOI: 10.7910/dvn/axd0cz/fw2spi
title: MASTER_Alamana_June2019.do

description: :unav
DOI: 10.7910/dvn/axd0cz/ly5uu4
title: profits_replication.png

description: :unav
DOI: 10.7910/dvn/axd0cz/urenay
title: Create_Figure2.do

description: :unav
DOI: 10.7910/dvn/axd0cz/uyg0yl
title: quantile_no_pooling.png

description: :unav
DOI: 10.7910/dvn/troybd/mbw6vq
title: Raw data_Fertilizer Response_table1_data.csv

description: :unav
DOI: 10.7910/dvn/troybd/ombsoy
title: Raw data_Fertilizer Response_metadata.csv

description: :unav
DOI: 10.7910/dvn/troybd/s1eeaa
title: Raw data_Fertilizer Response_journals_referred.tab

description: :unav
DOI: 10.5281/zenodo.3490514
title: Long-term data from field erosion plot studies in eastern Austria

description: Long-term runoff plot experiments were conducted at three sites in eastern Austria to evaluate the impact of conservation tillage. Following soil tillage treatments were investigated: 1) conventional tillage with ploughing in fall (CT), 2) mulch tillage with cover crops during winter period (MT), and 3) no tillage with cover crops during winter period (NT). Soil textures range from silt loam to loam. Datasets include for each site and each year the period of operation of the plots, the planted crop, the annual precipitation, surface runoff, soil loss, surface losses of nitrogen, phopshorus and soil organic carbon as well as absolute and relative crop yields.
DOI: 10.5281/zenodo.3490515
title: Long-term data from field erosion plot studies in eastern Austria

description: Long-term runoff plot experiments were conducted at three sites in eastern Austria to evaluate the impact of conservation tillage. Following soil tillage treatments were investigated: 1) conventional tillage with ploughing in fall (CT), 2) mulch tillage with cover crops during winter period (MT), and 3) no tillage with cover crops during winter period (NT). Soil textures range from silt loam to loam. Datasets include for each site and each year the period of operation of the plots, the planted crop, the annual precipitation, surface runoff, soil loss, surface losses of nitrogen, phopshorus and soil organic carbon as well as absolute and relative crop yields.