cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/b717135dee05029596e5207402d25008
title: Prairie du Sac - Sauk City, Wisconsin, monthly precipitation data

description: This is a compilation of total monthly precipitation data in total inches for two NOAA weather stations. The Prairie du Sac station data located at the Prairie du Sac dam on the Wisconsin River (43.31 , -89.7283) started with full monthly records being recorded in 1912 with complete monthly records through 2007. In mid-2007 a nearby station was established in Sauk City at the wastewater treatment plant (43.262 , -89.7349) with continuous data from 2008 through the present. The two stations are relatively close (about 3.25 miles apart), and both are slightly more than 4 miles to the west of the centroid of Fish Lake (Dane Co.) a core study lake in the North Temperate Lakes Long-Term Ecological Research Project conducted by the Center for Limnology at the University of Wisconsin-Madison. The compiled monthly records are based on daily NOAA precipitation records available electronically to the public. As a general practice, daily precipitation over weekends and holidays was not regularly recorded at the stations such that cumulative totals were recorded the following workweek day. As such, while the records for each single day were not always accurately recorded, the monthly totals were generally accurate. However, starting in 1996 at the Prairie du Sac station, because the cumulative weekend/holiday precipitation didn’t allow known daily totals, those cumulate weekend/holiday records were not submitted to NOAA so they were recorded as missing data in NOAA’s electronic dataset. To rectify the many months of missing data, pdf’s of the original hand-written monthly submissions were retrieved from NOAA’s archives such that the monthly precipitation totals could be calculated. In the process a few transcription errors in the electronic records of other months were also corrected in this dataset as well as determining a few other monthly records that were missing. Thus, this dataset of monthly precipitation at the two nearby weather stations is complete and hopefully accurate.
DOI: 10.5281/zenodo.7041551
title: Husmuli Injection and Seismicity Data 2015-2020

description: This dataset comprises the injection data, and seismic catalogue recorded in the Húsmúli reinjection area (Hellisheiði geothermal field, SW Iceland) between 2015 and 2020. The hydraulic data was acquired and processed by Reykjavik Energy/ON power, the operator of the Hellisheiði geothermal field. The seismic catalogue is curated by the Icelandic Met Office.
DOI: 10.5281/zenodo.7041552
title: Husmuli Injection and Seismicity Data 2015-2020

description: This dataset comprises the injection data, and seismic catalogue recorded in the Húsmúli reinjection area (Hellisheiði geothermal field, SW Iceland) between 2015 and 2020. The hydraulic data was acquired and processed by Reykjavik Energy/ON power, the operator of the Hellisheiði geothermal field. The seismic catalogue is curated by the Icelandic Met Office.
DOI: 10.5281/zenodo.7273908
title: cobs full part 1

description: Part 1 of the compressed COBS indexes built from all assemblies of the 661k dataset.
DOI: 10.6084/m9.figshare.21543138
title: Raw Meta Data

description: Raw meta data
DOI: 10.6084/m9.figshare.21543138.v1
title: Raw Meta Data

description: Raw meta data
DOI: 10.6084/m9.figshare.21543150.v1
title: CESC-PROG: A compact prognostic model and nomogram for cervical cancer based on miRNA biomarkersUntitled Item

description: Supplementary Information.
DOI: 10.7294/19952654.v2
title: Honey bee waggle dance data and code to analyze foraging at Alson H. Smith Jr. Agricultural Research & Extension Center (WAREC) as part of Bees-as-Bioindicators project.

description: This data set accompanies the article TN Steele, R Schürch, BD Ohlinger, & MJ Couvillon (2022) “Apple orchards feed honey bees during, but even more so after, bloom”, Ecosphere.
DOI: 10.7294/19952654
title: Honey bee waggle dance data and code to analyze foraging at Alson H. Smith Jr. Agricultural Research & Extension Center (WAREC) as part of Bees-as-Bioindicators project.

description: This data set accompanies the article TN Steele, R Schürch, BD Ohlinger, & MJ Couvillon (2022) “Apple orchards feed honey bees during, but even more so after, bloom”, Ecosphere.
DOI: 10.7294/19952654.v1
title: Honey bee waggle dance data and code to analyze foraging at Alson H. Smith Jr. Agricultural Research & Extension Center (WAREC) as part of Bees-as-Bioindicators project.

description: This data set accompanies the article TN Steele, R Schürch, BD Ohlinger, & MJ Couvillon (2022) “Apple orchards feed honey bees during, but even more so after, bloom”, Ecosphere.
DOI: 10.5281/zenodo.7313889
title: Fecundity Petrolisthes laevigatus

description: Table containing information about publication on crab fecundity, Petrolisthes laevigatus
DOI: 10.5281/zenodo.7313888
title: Fecundity Petrolisthes laevigatus

description: Table containing information about publication on crab fecundity, Petrolisthes laevigatus
DOI: 10.25835/0049176
title: Matlab/Simulink Files: Mathematical Modeling of Thyroid Homeostasis: Implications for the AHDS

description: These Matlab/Simulink Files were used to generate the plots for the submitted paper „Mathematical Modeling and Simulation of Thyroid Homeostasis: Implications for the Allan-Herndon-Dudley-Syndrome“. To reproduce the plots, please execute the files in the following order: 1: MM_Parameters_Healthy.m 2: MM_Healthy.slx 3: MM_Parameters_ADHS.m 4: MM_AHDS.slx 5: MM_Plot_Results and analogously regarding the linear case.
DOI: 10.5281/zenodo.7158056
title: DeLTA (Deep Learning Techniques for noise Annoyance detection) Dataset

description: The Deep Learning Techniques for noise Annoyance detection (DeLTA) dataset comprises 2,980 15-second binaural audio recordings collected in urban public spaces across London, Venice, Granada, and Groningen (sourced from International Soundscape Database). A remote listening experiment was designed and hosted on Gorilla Experiment Builder, a professional online platform used for studying complex behaviours. The survey was then distributed via Prolific to a pool of pre-registered participants (N=1,221), and data collected between July 5th and July 23rd, 2021. During the listening experiment, participants listened to ten 15-second-long binaural recordings of urban environments and were instructed to select all the sound sources they could identify within the recording and then to provide an annoyance rating (from 1 to 10). For the sound source recognition task, participants were provided with a list of 24 labels they could select from. To collapse these into a single set of sound sources per recording, a “consensus” approach was considered, i.e., if two or more participants identified a source as being present in a recording, this source was considered to be effectively present. This resulted in a 2890 by 24 data frame (2890 recordings, each with up to 23 possible labels present and an average annoyance rating). On average, each recording has 3.2 identified sound sources present. Due to the constraints of the online survey software, Mp3 files were used for the listening experiment. Higher quality 24- or 32-bit 48kHz WAV files can be made available from the authors upon request. Each binaural audio recording consists of a 2 channel Mp3 file.
description: Funding provided by the UCL Health of the Public Small Grants Scheme
DOI: 10.5281/zenodo.7158057
title: DeLTA (Deep Learning Techniques for noise Annoyance detection) Dataset

description: The Deep Learning Techniques for noise Annoyance detection (DeLTA) dataset comprises 2,980 15-second binaural audio recordings collected in urban public spaces across London, Venice, Granada, and Groningen (sourced from International Soundscape Database). A remote listening experiment was designed and hosted on Gorilla Experiment Builder, a professional online platform used for studying complex behaviours. The survey was then distributed via Prolific to a pool of pre-registered participants (N=1,221), and data collected between July 5th and July 23rd, 2021. During the listening experiment, participants listened to ten 15-second-long binaural recordings of urban environments and were instructed to select all the sound sources they could identify within the recording and then to provide an annoyance rating (from 1 to 10). For the sound source recognition task, participants were provided with a list of 24 labels they could select from. To collapse these into a single set of sound sources per recording, a “consensus” approach was considered, i.e., if two or more participants identified a source as being present in a recording, this source was considered to be effectively present. This resulted in a 2890 by 24 data frame (2890 recordings, each with up to 23 possible labels present and an average annoyance rating). On average, each recording has 3.2 identified sound sources present. Due to the constraints of the online survey software, Mp3 files were used for the listening experiment. Higher quality 24- or 32-bit 48kHz WAV files can be made available from the authors upon request. Each binaural audio recording consists of a 2 channel Mp3 file.
description: Funding provided by the UCL Health of the Public Small Grants Scheme
DOI: 10.5281/zenodo.4751126
title: X-ray crystallography datasets for the F420-reducing sulfite-reductase from Methanocaldococcus jannaschii and Methanothermococcus thermolithotrophicus

description: The three datasets present in this entry are all related to X-ray crystallography data collected from crystals of the F<sub>420</sub>-reducing sulfite-reductase (Fsr) from <em>Methanocaldococcus jannaschii</em> (Mj) and <em>Methanothermococcus thermolithotrophicus</em> (Mt). MjFsr_Fe_Kedge.zip: Dataset collected at a wavelength of 1.74013 Å. Fsr from <em>Methanocaldococcus jannaschii.</em> MjFsr.zip: Dataset collected at a wavelength of 0.97857 Å. Fsr from <em>Methanocaldococcus jannaschii.</em> MtFsr.zip: Datasets collected at a wavelength of 1.00004 Å. Fsr from <em>Methanothermococcus thermolithotrophicus.</em>
DOI: 10.5281/zenodo.4751125
title: X-ray crystallography datasets for the F420-reducing sulfite-reductase from Methanocaldococcus jannaschii and Methanothermococcus thermolithotrophicus

description: The three datasets present in this entry are all related to X-ray crystallography data collected from crystals of the F<sub>420</sub>-reducing sulfite-reductase (Fsr) from <em>Methanocaldococcus jannaschii</em> (Mj) and <em>Methanothermococcus thermolithotrophicus</em> (Mt). MjFsr_Fe_Kedge.zip: Dataset collected at a wavelength of 1.74013 Å. Fsr from <em>Methanocaldococcus jannaschii.</em> MjFsr.zip: Dataset collected at a wavelength of 0.97857 Å. Fsr from <em>Methanocaldococcus jannaschii.</em> MtFsr.zip: Datasets collected at a wavelength of 1.00004 Å. Fsr from <em>Methanothermococcus thermolithotrophicus.</em>
DOI: 10.5281/zenodo.7022783
title: TIME4CS-DataMatrix

description: This data matrix contains the collection of case studies of institutional adoption of citizen science developed for the D 1.1 of WP1 Citizen Science state of the art and overcoming challenges of the project TIME4CS. The data matrix includes three sheets: Data Matrix-Includes the report of the collected case studies Cases Studies Acronyms- acronyms used for the research performing organisations Conditions Acronyms- List the different conditions included in this data set, the acronyms for each of them and the calibration To use this data set to perform QCA it is necessary to delete the second and third page of this excel document and save it as a CSV file.
DOI: 10.5281/zenodo.7022784
title: TIME4CS-DataMatrix

description: This data matrix contains the collection of case studies of institutional adoption of citizen science developed for the D 1.1 of WP1 Citizen Science state of the art and overcoming challenges of the project TIME4CS. The data matrix includes three sheets: Data Matrix-Includes the report of the collected case studies Cases Studies Acronyms- acronyms used for the research performing organisations Conditions Acronyms- List the different conditions included in this data set, the acronyms for each of them and the calibration To use this data set to perform QCA it is necessary to delete the second and third page of this excel document and save it as a CSV file.
DOI: 10.5281/zenodo.7313967
title: TIME4CS-DataMatrix

description: This data matrix contains the collection of case studies of institutional adoption of citizen science developed for the D 1.1 of WP1 Citizen Science state of the art and overcoming challenges of the project TIME4CS. The data matrix includes three sheets: Data Matrix-Includes the report of the collected case studies Cases Studies Acronyms- acronyms used for the research performing organisations Conditions Acronyms- List the different conditions included in this data set, the acronyms for each of them and the calibration To use this data set to perform QCA it is necessary to delete the second and third page of this excel document and save it as a CSV file.
DOI: 10.6084/m9.figshare.19077665
title: OCT images of Apple and Persimmon leaves

description: OCT images of Apple and Persimmon leaves used in this study
DOI: 10.6084/m9.figshare.20770612
title: Image flattening program

description: Image flattening program
DOI: 10.6084/m9.figshare.20770612.v1
title: Image flattening program

description: Image flattening program
DOI: 10.6084/m9.figshare.20770636
title: A scan profiling program

description: A scan profiling program
DOI: 10.6084/m9.figshare.20770636.v1
title: A scan profiling program

description: A scan profiling program
DOI: 10.6084/m9.figshare.21353613
title: MIAPPE checklist

description: MIAPPE checklist data
DOI: 10.6084/m9.figshare.21353613.v1
title: MIAPPE checklist

description: MIAPPE checklist data
DOI: 10.34740/kaggle/dsv/4489826
title: Mahanagar Yatayat Dataset
DOI: 10.48420/21543144
title: XRD analysis of dropcast MXene suspensions - Rigaku

description: Run typical, coupled θ:2θ scan of dropcast Ti<sub>3</sub>C<sub>2</sub> MXene synthesis product to confirm successful synthesis
DOI: 10.48420/21543144.v1
title: XRD analysis of dropcast MXene suspensions - Rigaku

description: Run typical, coupled θ:2θ scan of dropcast Ti<sub>3</sub>C<sub>2</sub> MXene synthesis product to confirm successful synthesis
DOI: 10.5281/zenodo.6346942
title: Svalbox-DOM_2020-0038_Ringdalsfjellet

description: <strong>Model description: </strong><br> Ringdalsfjellet-outcrop in inner-Colesdalen. Outcrop shows exposed sandstone bodies (river- and sandy floodplain) of the terrestrial Aspelintoppen Formation floodplain.<br> <br> <strong>Data availability:</strong><br> All uploaded archives are to be extracted to the same directory for a functional working environment, i.e., at the very least consisting of a project folder with the data and metashape subdirectories. The included processing report specifies the processing parameters that were used as input for the processing software (Agisoft Metashape, v1.6.4.10928).<br> Exported model data use CRS epsg:32633.<br> <br> <strong>Show and visualise on Svalbox.no:</strong><br> Through Svalbox we aim to take geoscientific research and education to the next level – with the simple motto of placing all key information and data sets in their correct spatial position. We bring modern technology, in particular cost-effective digital outcrops, to complement more than 200 years of geoscientific research on Svalbard. Finally, Svalbox provides a sustainable platform for sharing results, workflows and teaching material with the wider geoscientific community.<br> <br> For more information, contact the Svalbox team at svalbox[at]gmail.com.
DOI: 10.5281/zenodo.6346943
title: Svalbox-DOM_2020-0038_Ringdalsfjellet

description: <strong>Model description: </strong><br> Ringdalsfjellet-outcrop in inner-Colesdalen. Outcrop shows exposed sandstone bodies (river- and sandy floodplain) of the terrestrial Aspelintoppen Formation floodplain.<br> <br> <strong>Data availability:</strong><br> All uploaded archives are to be extracted to the same directory for a functional working environment, i.e., at the very least consisting of a project folder with the data and metashape subdirectories. The included processing report specifies the processing parameters that were used as input for the processing software (Agisoft Metashape, v1.6.4.10928).<br> Exported model data use CRS epsg:32633.<br> <br> <strong>Show and visualise on Svalbox.no:</strong><br> Through Svalbox we aim to take geoscientific research and education to the next level – with the simple motto of placing all key information and data sets in their correct spatial position. We bring modern technology, in particular cost-effective digital outcrops, to complement more than 200 years of geoscientific research on Svalbard. Finally, Svalbox provides a sustainable platform for sharing results, workflows and teaching material with the wider geoscientific community.<br> <br> For more information, contact the Svalbox team at svalbox[at]gmail.com.
DOI: 10.5281/zenodo.7038342
title: Internal SDMDb

description: Internal documentation
DOI: 10.5281/zenodo.7038343
title: Internal SDMDb

description: Internal documentation
DOI: 10.5281/zenodo.6642723
title: Svalbox-DOM_2019-0001

description: <strong>Model description: </strong><br> Low resolution overview model of Fortet and adjacent Petuniabukta/Adolfbukta Mountain face. The Petuniabukta mountain side is capped by Wordiekammen Black Crag beds which are locally intersected by solution collapse breccia pipes.Underlying the Black Crag beds is the Minkinfjellet Formation which is mostly scree covered but comprises the Fortet Member at the Fortet locality. The Fortet member is a sollution collapse breccia within the Minkinfjellet Formation and is the result of extensive gypsum dissolution and subsequent collapse of the overburden. The Adolfbukta mountain face displays gypsum, carbonate and sandstone beds of the Minkinfjellet Formation.<br> <br> <strong>Data availability:</strong><br> All uploaded archives are to be extracted to the same directory for a functional working environment, i.e., at the very least consisting of a project folder with the data and metashape subdirectories. The included processing report specifies the processing parameters that were used as input for the processing software (Agisoft Metashape, v1.7.1.11797).<br> Exported model data use CRS epsg:32633.<br> <br> <strong>Show and visualise on Svalbox.no:</strong><br> Through Svalbox we aim to take geoscientific research and education to the next level – with the simple motto of placing all key information and data sets in their correct spatial position. We bring modern technology, in particular cost-effective digital outcrops, to complement more than 200 years of geoscientific research on Svalbard. Finally, Svalbox provides a sustainable platform for sharing results, workflows and teaching material with the wider geoscientific community.<br> <br> For more information, contact the Svalbox team at svalbox[at]gmail.com.
DOI: 10.5281/zenodo.6642722
title: Svalbox-DOM_2019-0001

description: <strong>Model description: </strong><br> Low resolution overview model of Fortet and adjacent Petuniabukta/Adolfbukta Mountain face. The Petuniabukta mountain side is capped by Wordiekammen Black Crag beds which are locally intersected by solution collapse breccia pipes.Underlying the Black Crag beds is the Minkinfjellet Formation which is mostly scree covered but comprises the Fortet Member at the Fortet locality. The Fortet member is a sollution collapse breccia within the Minkinfjellet Formation and is the result of extensive gypsum dissolution and subsequent collapse of the overburden. The Adolfbukta mountain face displays gypsum, carbonate and sandstone beds of the Minkinfjellet Formation.<br> <br> <strong>Data availability:</strong><br> All uploaded archives are to be extracted to the same directory for a functional working environment, i.e., at the very least consisting of a project folder with the data and metashape subdirectories. The included processing report specifies the processing parameters that were used as input for the processing software (Agisoft Metashape, v1.7.1.11797).<br> Exported model data use CRS epsg:32633.<br> <br> <strong>Show and visualise on Svalbox.no:</strong><br> Through Svalbox we aim to take geoscientific research and education to the next level – with the simple motto of placing all key information and data sets in their correct spatial position. We bring modern technology, in particular cost-effective digital outcrops, to complement more than 200 years of geoscientific research on Svalbard. Finally, Svalbox provides a sustainable platform for sharing results, workflows and teaching material with the wider geoscientific community.<br> <br> For more information, contact the Svalbox team at svalbox[at]gmail.com.
DOI: 10.5281/zenodo.6410151
title: Svalbox-DOM_2021-0048_Solryggen

description: <strong>Model description: </strong><br> Digitial outcrop model of the northern face of Solryggen, in Nordenskiöld Land.<br> <br> <strong>Data availability:</strong><br> All uploaded archives are to be extracted to the same directory for a functional working environment, i.e., at the very least consisting of a project folder with the data and metashape subdirectories. The included processing report specifies the processing parameters that were used as input for the processing software (Agisoft Metashape, v1.7.3.12473).<br> Exported model data use CRS epsg:32633.<br> <br> <strong>Show and visualise on Svalbox.no:</strong><br> Through Svalbox we aim to take geoscientific research and education to the next level – with the simple motto of placing all key information and data sets in their correct spatial position. We bring modern technology, in particular cost-effective digital outcrops, to complement more than 200 years of geoscientific research on Svalbard. Finally, Svalbox provides a sustainable platform for sharing results, workflows and teaching material with the wider geoscientific community.<br> <br> For more information, contact the Svalbox team at svalbox[at]gmail.com.
DOI: 10.5281/zenodo.6410172
title: Svalbox-DOM_2021-0049_Solryggen

description: <strong>Model description: </strong><br> Digital outcrop model of the shouthern face of Solryggen, in Nordenskiöld Land.<br> <br> <strong>Data availability:</strong><br> All uploaded archives are to be extracted to the same directory for a functional working environment, i.e., at the very least consisting of a project folder with the data and metashape subdirectories. The included processing report specifies the processing parameters that were used as input for the processing software (Agisoft Metashape, v1.7.3.12473).<br> Exported model data use CRS epsg:32633.<br> <br> <strong>Show and visualise on Svalbox.no:</strong><br> Through Svalbox we aim to take geoscientific research and education to the next level – with the simple motto of placing all key information and data sets in their correct spatial position. We bring modern technology, in particular cost-effective digital outcrops, to complement more than 200 years of geoscientific research on Svalbard. Finally, Svalbox provides a sustainable platform for sharing results, workflows and teaching material with the wider geoscientific community.<br> <br> For more information, contact the Svalbox team at svalbox[at]gmail.com.