cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8335931
title: Historical Travel and Communications in Finland

description: This dataset contains a proof-of-concept GIS database of over 29,000 individual historical road polyline segments as a shapefile dataset, covering over 11,000 km<sup>2</sup> in the western Finland from the city of Turku to northern parts of the province of Satakunta. These polylines capture the regional layout of the overland transport infrastructure of late nineteenth and early twentieth century Finland.
description: {"references": ["Oksanen, Eljas, Saarenp\u00e4\u00e4, Ida. and Lahtinen, Anu. 2023. The HISCOM Project. Exploring Methodologies for Large-scale Digitisation of Historical Roadways. SKAS 2/2022, 8-14"]}
DOI: 10.5281/zenodo.8336244
title: Historical Travel and Communications in Finland

description: This dataset contains a proof-of-concept GIS database of over 29,000 individual historical road polyline segments as a shapefile dataset, covering over 11,000 km<sup>2</sup> in the western Finland from the city of Turku to northern parts of the province of Satakunta. These polylines capture the regional layout of the overland transport infrastructure of late nineteenth and early twentieth century Finland.
description: {"references": ["Oksanen, Eljas, Saarenp\u00e4\u00e4, Ida. and Lahtinen, Anu. 2023. The HISCOM Project. Exploring Methodologies for Large-scale Digitisation of Historical Roadways. SKAS 2/2022, 8-14"]}
DOI: 10.7303/syn38814662
title: AMP-RA.SLE_Genomic Variants
DOI: 10.15139/s3/mww6lz
title: Replication Data for: The Electoral Dynamics of Capital Punishment Commutations

description: We explore electoral explanations for United States' governors' willingness to commute death sentences in their state. Across descriptive tests and pre-registered regression specifications, we find little evidence that election timing or term limits affect either the probability of commuting death sentences or the proportion of such sentences governors might commute. However, we do find evidence that governors are more likely to commute sentences---and commute sentences for a higher proportion of defendants---during the ``lame duck'' period after their successor's election but before their inauguration.
DOI: 10.25345/c5td9nj9w
title: MassIVE MSV000092833 - GNPS - HNRC_MIBI_DATASET_2023_DORRESTEIN
title: Untargeted LC-MS/MS acquisition was performed on a Vanquish UHPLC system coupled to a Q-Exactive Hybrid Quadrupole-Orbitrap (Thermo Fisher Scientific, Bremen, Germany).
DOI: 10.5519/qd.163j3151
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (77 records)
DOI: 10.6084/m9.figshare.22696312.v1
title: Data Archive for "Identifying a developmental transition in honey bees using gene expression data"

description: This data archive contains gene expression data used in the following publication: <br> Identifying a developmental transition in honey bees using gene expression data. Bryan C. Daniels, Ying Wang, Robert E. Page, Jr, and Gro V. Amdam. <br> A preprint of the manuscript is available on biorxiv here: https://doi.org/10.1101/2022.11.03.514986 <br> Code used in the publication is available here: https://github.com/Collective-Logic-Lab/landau <br> A summary of data collection methods follows: <br> The bee collection was conducted during March 18th to April 7th, 2016. Five strong wild type colonies were chosen as sources of newly emerging bees. Two small nuclear colonies with 9 frames in each were used as recipient colonies that had similar supplies of pollen and honey, and similar numbers of brood and adult bees. The emerging frames from source colonies were put into incubator (37 degrees C) and about 200 newly emerged bees were collected, marked in a color on the bee thoraxes and distributed evenly to the recipient colonies. This procedure was repeated for three consecutive days. About 600 newly emerged bees were introduced in the recipient colonies from March 19th to March 21st, 2016. Ten each of 1 day old, 3 day old, 5 day old, 10 day old and 15 day old bees from each recipient colony were collected in the following days. Therefore, there were total 20 sample bees for further experiment from two recipient colonies for each age. RNA was extracted from 16 randomly selected bees of each age using TRIZOL method. The quality of RNA was measured by Nanodrop and 260/280 was between 1.85-2.00, indicating good quality of RNA. RNA samples were sent to the University of Arizona Core lab for Nanostring analysis, a method to quantify the copy of RNA for the target genes. <br> 94 genes were selected based on prior knowledge and the potential association between these genes, VG production, and social behavior. Genes were selected from the honey bee <em>Apis mellifera</em> assembly and gene annotation information at NCBI (https://www.ncbi.nlm.nih.gov). Genes were prioritized using a pragmatic approach. In brief, our strategy integrated information on a specific biological process (the nurse-forager transition) with information on genes that were suggestively, correlatively, or potentially causally involved. Thus, gene selection relied on a process of extensive literature review as well as interdisciplinary biological expertise. The gene prioritization was reviewed by three members of the interdisciplinary team (YW, GVA, and REP) to minimize operator biases. Four housekeeping genes, actin (GB17681), rp49 (GB10903), GAPDH (LOC410122) and RPS18 (LOC552726) were used for sample normalization. Finally, the vitellogenin (VG) protein was measured in the honey bee hemolymph.
DOI: 10.6084/m9.figshare.22696312
title: Data Archive for "Identifying a developmental transition in honey bees using gene expression data"

description: This data archive contains gene expression data used in the following publication: <br> Identifying a developmental transition in honey bees using gene expression data. Bryan C. Daniels, Ying Wang, Robert E. Page, Jr, and Gro V. Amdam. <br> A preprint of the manuscript is available on biorxiv here: https://doi.org/10.1101/2022.11.03.514986 <br> Code used in the publication is available here: https://github.com/Collective-Logic-Lab/landau <br> A summary of data collection methods follows: <br> The bee collection was conducted during March 18th to April 7th, 2016. Five strong wild type colonies were chosen as sources of newly emerging bees. Two small nuclear colonies with 9 frames in each were used as recipient colonies that had similar supplies of pollen and honey, and similar numbers of brood and adult bees. The emerging frames from source colonies were put into incubator (37 degrees C) and about 200 newly emerged bees were collected, marked in a color on the bee thoraxes and distributed evenly to the recipient colonies. This procedure was repeated for three consecutive days. About 600 newly emerged bees were introduced in the recipient colonies from March 19th to March 21st, 2016. Ten each of 1 day old, 3 day old, 5 day old, 10 day old and 15 day old bees from each recipient colony were collected in the following days. Therefore, there were total 20 sample bees for further experiment from two recipient colonies for each age. RNA was extracted from 16 randomly selected bees of each age using TRIZOL method. The quality of RNA was measured by Nanodrop and 260/280 was between 1.85-2.00, indicating good quality of RNA. RNA samples were sent to the University of Arizona Core lab for Nanostring analysis, a method to quantify the copy of RNA for the target genes. <br> 94 genes were selected based on prior knowledge and the potential association between these genes, VG production, and social behavior. Genes were selected from the honey bee <em>Apis mellifera</em> assembly and gene annotation information at NCBI (https://www.ncbi.nlm.nih.gov). Genes were prioritized using a pragmatic approach. In brief, our strategy integrated information on a specific biological process (the nurse-forager transition) with information on genes that were suggestively, correlatively, or potentially causally involved. Thus, gene selection relied on a process of extensive literature review as well as interdisciplinary biological expertise. The gene prioritization was reviewed by three members of the interdisciplinary team (YW, GVA, and REP) to minimize operator biases. Four housekeeping genes, actin (GB17681), rp49 (GB10903), GAPDH (LOC410122) and RPS18 (LOC552726) were used for sample normalization. Finally, the vitellogenin (VG) protein was measured in the honey bee hemolymph.
DOI: 10.22003/xfel.eu-data-005916-00
title: Reference Cu complex measurements
DOI: 10.5281/zenodo.8336346
title: PARAGON 1 - KM2112 - Fluorometric Chlorophyll - CTD

description: These Simons Collaboration on Ocean Processes and Ecology (SCOPE) data products were produced by the University of Hawaiʻi at Mānoa with support from the Simons Foundation. This dataset was collected on the R/V Kilo Moana, which departed and returned to Honolulu, HI, with most of the cruise spent following an anticyclonic eddy northeast of the Hawaiian islands. Fluorometric Chlorophyll were collected from the R/V Kilo Moana's CTD/Rosette system and filtered at low vacuum through a glass fiber filter. Samples were then frozen and stored in foil until analysis. Post cruise, the filters were extracted using 90% acetone for a total of 48 hours in a -20°C freezer, covered to prevent the photodegradation of pigments. Samples were then run on a Turner 10-AU Fluorometer. Data were corrected for average glass fiber filter blank values and when available is reported as the average of duplicate samples. Time in UTC.
DOI: 10.5281/zenodo.8336345
title: PARAGON 1 - KM2112 - Fluorometric Chlorophyll - CTD

description: These Simons Collaboration on Ocean Processes and Ecology (SCOPE) data products were produced by the University of Hawaiʻi at Mānoa with support from the Simons Foundation. This dataset was collected on the R/V Kilo Moana, which departed and returned to Honolulu, HI, with most of the cruise spent following an anticyclonic eddy northeast of the Hawaiian islands. Fluorometric Chlorophyll were collected from the R/V Kilo Moana's CTD/Rosette system and filtered at low vacuum through a glass fiber filter. Samples were then frozen and stored in foil until analysis. Post cruise, the filters were extracted using 90% acetone for a total of 48 hours in a -20°C freezer, covered to prevent the photodegradation of pigments. Samples were then run on a Turner 10-AU Fluorometer. Data were corrected for average glass fiber filter blank values and when available is reported as the average of duplicate samples. Time in UTC.
DOI: 10.5281/zenodo.8336350
title: Building a knowledge graph of the Benetton's group suppliers network

description: Some resources used for the PW4 of the master's AI4GOV. It concerns the Benetton Group's supplier network
DOI: 10.5281/zenodo.8336349
title: Building a knowledge graph of the Benetton's group suppliers network

description: Some resources used for the PW4 of the master's AI4GOV. It concerns the Benetton Group's supplier network
DOI: 10.5067/v8tcj7hqd15a
title: OCO-2 Level 2 spatially ordered geolocated retrievals using the A-band retrieval algorithm, Retrospective Processing V10r
DOI: 10.5281/zenodo.8309945
title: Active Regions with Multiple NOAA Numbers, 2011-2019

description: This is a list of active regions which have been identified as lasting for multiple rotations, and their subsequent-rotation NOAA number designation. It was generated via a list of candidates using the differential rotation tool in SunPy, which was then vetted via visual inspection using data from SDO HMI. This is the expert classification data set <em>only</em>; the classifications from the citizen science project Solar Active Region Spotters will be included in a separate upload.
DOI: 10.5281/zenodo.8336354
title: Active Regions with Multiple NOAA Numbers, 2011-2019

description: This is a list of active regions which have been identified as lasting for multiple rotations, and their subsequent-rotation NOAA number designation. It was generated via a list of candidates using the differential rotation tool in SunPy, which was then vetted via visual inspection using data from SDO HMI. This is the expert classification data set <em>only</em>; the classifications from the citizen science project Solar Active Region Spotters will be included in a separate upload. Note 1: this is an update of the original file, which had been produced with a glitch resulting in some non-matches being listed as matches. It has been updated with the correct matches. Note 2: this list is <em>not exhaustive</em>. It comprises only those returning active regions which were identified by the code and confirmed by hand, as well as some active regions in those pairs' immediate vicinity which were clearly also matches.
DOI: 10.6084/m9.figshare.24121281
title: Summary statistics from <i>Novel Risk Loci in Tinnitus and Causal Inference With Neuropsychiatric Disorders Among Adults of European Ancestry</i>

description: Summary statistics from Clifford et al., 2020 (doi:10.1001/jamaoto.2020.2920).Please refer to original publication for detailed study information and phenotype definitions.
DOI: 10.48320/3b36697d-7a54-46b9-9890-e19c4dc5702a
title: Participatory Budgeting in Ukraine
DOI: 10.5281/zenodo.8336363
title: PARAGON 1 - KM2112 - LISST DEEP Profiles

description: These Simons Collaboration on Ocean Processes and Ecology (SCOPE) data products were produced by the University of Hawaiʻi at Mānoa with support from the Simons Foundation. This dataset was collected on the R/V Kilo Moana, which departed and returned to Honolulu, HI, with most of the cruise spent following an anticyclonic eddy northeast of the Hawaiian islands. A Sequoia Scientific LISST-100X instrument performed yo-yo profiles to 200m depth. The data presented here are blank-corrected using a deepwater background scattering calibration, and binned in 2-meter bins from 2 to 200m depths. Note that data have not been processed to remove outliers. Time stamp is in UTC.
DOI: 10.5281/zenodo.8336362
title: PARAGON 1 - KM2112 - LISST DEEP Profiles

description: These Simons Collaboration on Ocean Processes and Ecology (SCOPE) data products were produced by the University of Hawaiʻi at Mānoa with support from the Simons Foundation. This dataset was collected on the R/V Kilo Moana, which departed and returned to Honolulu, HI, with most of the cruise spent following an anticyclonic eddy northeast of the Hawaiian islands. A Sequoia Scientific LISST-100X instrument performed yo-yo profiles to 200m depth. The data presented here are blank-corrected using a deepwater background scattering calibration, and binned in 2-meter bins from 2 to 200m depths. Note that data have not been processed to remove outliers. Time stamp is in UTC.
DOI: 10.5281/zenodo.8336376
title: PARAGON 1 - KM2112 - Underway CTD

description: These Simons Collaboration on Ocean Processes and Ecology (SCOPE) data products were produced by the University of Hawaiʻi at Mānoa with support from the Simons Foundation. This dataset was collected on the R/V Kilo Moana, which departed and returned to Honolulu, HI, with most of the cruise spent following an anticyclonic eddy northeast of the Hawaiian islands. Underway CTD profiles were conducted with the ship moving less than 8 knots by dropping a probe over the stern. The data were binned to every 2 meters and a negative lag was applied to the temperature data to align it with the conductivity data and avoid spikes in salinity. Time is in UTC.
DOI: 10.5281/zenodo.8336375
title: PARAGON 1 - KM2112 - Underway CTD

description: These Simons Collaboration on Ocean Processes and Ecology (SCOPE) data products were produced by the University of Hawaiʻi at Mānoa with support from the Simons Foundation. This dataset was collected on the R/V Kilo Moana, which departed and returned to Honolulu, HI, with most of the cruise spent following an anticyclonic eddy northeast of the Hawaiian islands. Underway CTD profiles were conducted with the ship moving less than 8 knots by dropping a probe over the stern. The data were binned to every 2 meters and a negative lag was applied to the temperature data to align it with the conductivity data and avoid spikes in salinity. Time is in UTC.
DOI: 10.5519/qd.iljv2bqn
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (55 records)
DOI: 10.5281/zenodo.8336383
title: PARAGON 1 - KM2112 - Optics - C-STAR and ECO

description: These Simons Collaboration on Ocean Processes and Ecology (SCOPE) data products were produced by the University of Hawaiʻi at Mānoa with support from the Simons Foundation. This dataset was collected on the R/V Kilo Moana, which departed and returned to Honolulu, HI, with most of the cruise spent following an anticyclonic eddy northeast of the Hawaiian islands. Two biooptical instruments were plumbed to the underway uncontaminated seawater (intake depth 6m). Data for each instrument were averaged to the minute and matched to a timestamp on the minute. C-STAR: Filtered values (&lt;0.2 um) removed from all data (see White et al., 2017, GRL); ECO: filtered values (&lt;0.2 um) removed from chl and volume scattering data; chl fluorescence converted to mg/m3 using factory calibrations. CDOM not included due to faulty channel. Time is in UTC.
DOI: 10.5281/zenodo.8336382
title: PARAGON 1 - KM2112 - Optics - C-STAR and ECO

description: These Simons Collaboration on Ocean Processes and Ecology (SCOPE) data products were produced by the University of Hawaiʻi at Mānoa with support from the Simons Foundation. This dataset was collected on the R/V Kilo Moana, which departed and returned to Honolulu, HI, with most of the cruise spent following an anticyclonic eddy northeast of the Hawaiian islands. Two biooptical instruments were plumbed to the underway uncontaminated seawater (intake depth 6m). Data for each instrument were averaged to the minute and matched to a timestamp on the minute. C-STAR: Filtered values (&lt;0.2 um) removed from all data (see White et al., 2017, GRL); ECO: filtered values (&lt;0.2 um) removed from chl and volume scattering data; chl fluorescence converted to mg/m3 using factory calibrations. CDOM not included due to faulty channel. Time is in UTC.
DOI: 10.15482/usda.adc/1529551
title: Data from: Honeydew associated with four common crop aphid species increases longevity of the parasitoid wasp, Bracon cephi (Hymenoptera: Braconidae)

description: Data are from a laboratory experiment conducted to examine the potential effects of honeydew from six different aphid species by crop species combinations on the longevity of Bracon cephi Gahan (Hymenoptera: Braconidae), the most important biological control of the wheat stem sawfly, Cephus cinctus Norton (Hymenoptera: Cephidae), a major pest of wheat in the northern Great Plains of North America. We quantified the number of days parasitoids lived on each honeydew type.
Abstract from published manuscript:
The absence of sugar resources can be an important factor in limiting the success of parasitoids as biological control agents. Restoring vegetation complexity within agricultural landscapes has thus become a major focus of conservation biological control efforts, with a traditional emphasis on nectar resources. Aphid honeydew is also an important source of sugars that is infrequently considered. We carried out a laboratory experiment to examine the potential effects of honeydew from six different aphid species by crop species combinations on the longevity of Bracon cephi Gahan (Hymenoptera: Braconidae), the most important biological control of the wheat stem sawfly, Cephus cinctus Norton (Hymenoptera: Cephidae), a major pest of wheat in the northern Great Plains of North America. The benefits of honeydew for parasitoid longevity varied significantly among different aphid and crop species, illustrating the complexity of these interactions. However, honeydew produced by four aphid species commonly found in wheat, pea, and canola crops significantly increased the longevity (by two- to threefold) of the parasitoid. The study suggests that honeydew provisioning could be an important mechanism underlying the benefits of crop diversification to support biological control that merits further research.
Resources in this dataset:


Resource title: Data Directory
File name: Data Directory for Bc x Honeydew.xlsx
Resource description: Column descriptions for WSS BC X Honeydew longevity_ Ag Data Commons


Resource title: Parasitoid survival by honeydew treatment
File name: WSS BC X Honeydew longevity_ Ag Data Commons.xlsx
Resource description: The data are parasitoid survival in days on six different honeydew sugar resources.
DOI: 10.15468/f3pbtt
title: Digital Catalogue of Biodiversity of Poland — Plantae: Charophyta

description: The dataset presents a chapter of the Digital Catalogue of Biodiversity of Poland, comprising taxa of (infra)specific level, reported from Poland in the present administrative boundaries of the country. In this instance of the Catalogue, the list includes only taxa of confirmed occurrence, ignoring doubtful records that need verification as well as synonyms and other not valid names. The occurrence of each species is supported by a published reference.
DOI: 10.6084/m9.figshare.3761562.v2705
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5281/zenodo.7988099
title: Model and code for "On the influence of hydroxyl radical and ocean sinks on estimated HCFC and HFC emissions and banks"

description: This archive contains the following contents for the manuscript "On the influence of hydroxyl radical and ocean sinks on estimated HCFC and HFC emissions and banks": plotting_code.zip: <br> This directory contains python code that plot all the figures in the paper residence_time_tables.zip: <br> This directory contains csv files for each species on their atmospheric residence times under different OH and ocean scenarios discussed in the paper (a list of scenarios is in the header of each file) Agage12box_outputs: <br> This directory contains AGAGE 12 box model inputs (observed atmospheric mole fraction) and outputs (12-box model simulated atmospheric mole fractions and inferred emissions). This data is used in the WMO (2022) report (Laube & Tegtmeier, 2022; Liang & Rigby, 2022). HCFC-22.tar.gz (similar structure for the other 5 species):<br> Folders with prefix 'run_' contain the output from the MITgcm ocean and the 12-box coupled model simulation. Different OH and ocean scenarios are followed after the prefix 'run_'. <br> Folders with prefix 'code_' contain the modified MITgcm code. The AGAGE 12-box atmosphere model is coded in these fortran files. <br> Folder named 'Input' contains the input emission, atmospheric initial conditions, other lifetime (mainly stratospheric photochemistry), advection and diffusion timescales in the atmosphere, OH concentration, and atmospheric temperature. <br> These species-specific directories are placed under the folder 'MITgcm/verification/' after installing the MITgcm ocean general circulation model. A detailed instruction on how to install and run the MITgcm can be found at https://mitgcm.readthedocs.io/en/latest/.<br> Note that the plotting_codes can run without installing MITgcm, since the run folders already have all the model outputs. References:<br> Laube, J., & Tegtmeier, S. (2022). Scientific Assessment of Ozone Depletion: 2022, Chapter 1: Update on ozone-depleting substances (ODSs) and other gases of interest to the Montreal Protocol (No. 278) (p. 509). Geneva: World Meteorological Organization.<br> Liang, Q., & Rigby, M. (2022). Scientific Assessment of Ozone Depletion: 2022, Chapter 2: Hydrofluorocarbons (No. 278) (p. 509). Geneva: World Meteorological Organization.