cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.y6sxe7
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anoda cristata",
 "Country is Netherlands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 32 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045648-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/2pt-fa4-gwd
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.71728/hw56-vj34
title: Structure-Based Prediction of SARS-CoV-2 Variant Properties Using Machine Learning on Mutational Neighborhoods

description: This dataset presents a structure- and function-annotated resource of SARS-CoV-2 spike receptor-binding domain (RBD) variants. It includes 3,705 theoretical 1-step RBD mutations and 200 higher-order Omicron BA.1 and BA.2 variants, each predicted using AlphaFold2 and ESMFold and enriched with sequence-derived Bio2Byte descriptors. The dataset comprises six CSV files containing variant-level structural and empirical features, including RMSD, TM-score, plDDT, SASA, electrostatic potential, aggregation propensity, disorder, and flexibility, as well as ACE2 binding and RBD expression scores. The resource supports structure–function analysis, mutation impact prediction, and machine learning–based variant modeling for virology and pandemic preparedness.
DOI: 10.3535/acn-0qn-2ce
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/f0b-2a4-8hz
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/gwb-ng4-l9q
title: Bryoria capillaris (Ach.) Brodo & D. Hawksw.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/8kc-8d4-4q6
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/yn7-xl4-00w
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/g3s-k4a-3r9
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/y06-gj2-m5f
title: Ochrolechia tiroliensis (Erichsen) Hafellner & Türk

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ge2-hv9-3eb
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/lkb-fwa-2gf
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/g7b-lxa-d2x
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/nnk-n7v-cg7
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/2yc-2af-pec
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/kf0-cdf-3nq
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/mvh-506-bf3
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/djk-ntg-hq4
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/8fk-pzs-6ma
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.71732/esnq0v/lmaqo1
title: SN166_dati.sav

description: Data
DOI: 10.71732/esnq0v/mrv1io
title: SN166_dati.dta

description: Data
DOI: 10.3535/a0f-twk-kwm
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/d3h-dqa-khp
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.71732/esnq0v/obfgqr
title: SN166_profili.sav

description: Profiles data
DOI: 10.3535/cr1-8h4-bzc
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.71732/esnq0v/hulumj
title: SN166_profili.dta

description: Profiles data
DOI: 10.3535/047-w6j-0rr
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.71732/esnq0v/vqdapc
title: SN166_CB_ita_profili.pdf

description: Codebook profiles (it)
DOI: 10.3535/a36-vba-dkc
title: Pertusaria pertusa (L.) Tuck.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/hep-csd-sve
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.71732/esnq0v/xjnzoy
title: SN166_NM_ita.pdf

description: Methodological notes (it)
DOI: 10.71732/esnq0v/zwcmxj
title: SN166_CB_ita_dati.pdf

description: Codebook data (it)
DOI: 10.3535/z32-5y6-3rg
title: Pertusaria pertusa (L.) Tuck.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.71732/esnq0v/h9xghx
title: SN166_Q_ita.pdf

description: Questionnaire (it)
DOI: 10.3535/2br-vxq-d8c
title: Pertusaria constricta Erichsen

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.71732/esnq0v
title: Elicitazione delle preferenze delle imprese lombarde nella selezione dei curriculum vitae dei neolaureati (2015)

description: This study published by DASSI was previously archived at UniData - Bicocca Data Archive. Data are based on ELECTUS (Education-for-Labour Elicitation from Companies' Attitudes towards University Studies) research project, which is carried out in 2015 by the University of Padua in partnership with several other Italian universities with the aim of study the recruiters' preferences in selecting new graduates who apply for a job position in their companies. In particular, data are related to the research coordinated by the University of Milano-Bicocca. Data are collected through a CAWI questionnaire administered to 471 companies in Lombardy, divided into two parts. In the first one, recruiters are asked to choose and rank four possible profiles of new graduates for five different job vacancies. In the second part the entrepreneurs are asked about their socio-demographic features. The project has adopted an experimental research design using the conjoint analysis method, i.e. the generation of different joint combinations of attributes related to the potential candidates for a specific job position. In this way, instead of directly asking entrepreneurs to express a preference on the characteristics of potential candidates for the company's job vacancies, the context of choice of the candidate with the most suitable profile was simulated in a more realistic way. Data are related to the preferences expressed by the interviewees concerning five job vacancies: Administrative Clerk, Human Resource Assistant, Information and Communication Technology Professional (system analyst), Marketing Assistant and Customer Relationships Manager. Candidates' profiles were constructed taking into account six attributes: Field of Study, Degree Mark, Degree Level, English Knowledge, Relevant Work Experience and Willigness to Travel on Business. For more information on method, research design and data collection process see the Methodological Notes.
DOI: 10.3535/xhj-y7b-vc0
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/bgk-rj4-6xz
title: Pertusaria pertusa (L.) Tuck.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/2w4-1wa-ddt
title: Pertusaria pertusa (L.) Tuck.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.48677/660998b8-3630-4e0f-9a42-33153bf23c3c
title: Digitales Geländehöhenmodell - Höhenraster 100m Stichtag 31.12.2022

description: Ein digitales Geländehöhenmodell (DGM) beschreibt die Erdoberfläche (natürlicher Boden, ohne Bewuchs). Das aus Luftbildern photogrammetrisch ausgewertete Geländehöhenmodell besteht aus Punktmengen, die in einem regelmäßigen Gitter angeordnet und in Lage und Höhe georeferenziert sind. Zusätzliche Geländestrukturen wie Bruchlinien, Formenlinien und markante Einzelpunkte ergänzen den regelmäßigen Höhenraster und liefern detaillierte Informationen über die Topographie.
Das photogrammetrisch ausgewertete Geländehöhenmodell des BEV wird seit dem Jahr 2020 nicht mehr aktualisiert. Aus dem letzten Stand dieses digitalen Geländehöhenmodells wurden neben dem 5m Standard-Raster weitere Raster mit 25m, 50m, 100m, 250m und 500m Gitterweite interpoliert.

Eignung/Nutzung unter Beachtung des Aktualitätsstandes (2020 und älter):
• Grundlage für Orthophotoberechnung
• Planungsgrundlage
• Umweltschutz
• Nachrichtentechnik
• Geologie
• Hydrologie
• Landwirtschaft
• Kartographie
DOI: 10.17034/2942d476-c73b-4238-8b9b-7800ccbba979
title: Dataset for 'Study of thickness distribution on a robotic rotational moulding system'

description: For 50 years, robotic systems have automated injection moulding. While rotational moulding is less advanced, recent innovations like ROBOMOULD® have improved its process control. This technology uses a 6-axis robot arm to manipulate the mould, enabling precise control over thickness distribution. 

This dataset is the measurement results from a full factorial study to study the three control parameters (rocking angle, rotations per rock, and robot feed rate or speed) of this robotic rotational moulding system. The moulded parts were produced using an industrial sized fuel tank mould on the robotic moulding system. This study compares experimental and simulated thickness distributions in robotic rotational moulding. A MATLAB-based finite element model predicts thickness distribution based on powder contact time. Results show that robot feeding rate and the interaction between rocking angle and rotations per movement significantly influence thickness distribution. The simplified simulation model accurately predicts trends at higher feeding rates.

These measurement results can be used to inform future experiments, calibrate simulation models, or validate existing simulations.
DOI: 10.3535/2ly-9t6-kph
title: Pertusaria constricta Erichsen

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vl3-ges-vcg
title: Pertusaria pupillaris (Nyl.) Th. Fr.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/bhq-9hx-j74
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/p0y-bs1-ehe
title: Pertusaria pupillaris (Nyl.) Th. Fr.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/73e-taw-wnp
title: Pertusaria constricta Erichsen

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/kt5-lh1-2ye
title: Pertusaria constricta Erichsen

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ec0-jr9-1js
title: Pertusaria pustulata (Ach.) Duby

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.6084/m9.figshare.30086005
title: Dataset for Roy-Proulx et al. Wood chemical composition of harvesting residues for bioenergy

description: Dataset for manuscript Roy-Proulx et al. <i>Wood chemical composition of harvesting residues for bioenergy</i>, submitted to <i>Wood Science and Technology</i> journal.
DOI: 10.6084/m9.figshare.30086005.v1
title: Dataset for Roy-Proulx et al. Wood chemical composition of harvesting residues for bioenergy

description: Dataset for manuscript Roy-Proulx et al. <i>Wood chemical composition of harvesting residues for bioenergy</i>, submitted to <i>Wood Science and Technology</i> journal.
DOI: 10.3535/ey1-z5d-86b
title: Peltigera malacea (Ach.) Funck

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/2er-rf1-de0
title: Peltigera scabrosa Th. Fr.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/jlk-18f-hg4
title: Pertusaria pupillaris (Nyl.) Th. Fr.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/wl3-70z-wr3
title: Pertusaria pupillaris (Nyl.) Th. Fr.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/b90-gs9-n4y
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/b9c-486-e68
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/185-h6r-t4d
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/zd0-w75-65g
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/3yf-r2j-vpd
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/3rh-znv-fb8
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/6be-6b2-g5g
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ehp-5tw-cgw
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/1zd-2ph-nrl
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/z9h-ehc-fl1
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/23j-x3z-92b
title: Peltigera ponojensis Gyeln.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/7vr-ge1-vp4
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/bp6-1pz-dp0
title: Peltigera ponojensis Gyeln.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/lw6-426-bda
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ptg-5af-67z
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/rp9-nsy-j6n
title: Peltigera ponojensis Gyeln.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/8jx-we2-sh9
title: Peltigera ponojensis Gyeln.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/wx2-le0-x36
title: Peltigera ponojensis Gyeln.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/hww-hp1-n4j
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/90t-n67-ywy
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.qtkvsm
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Papyrocranus congoensis)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 10 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045649-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrzwke
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anoda cristata",
 "Country is Poland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045650-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/2zm-gbj-sdv
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/fj4-vdd-rpe
title: Peltigera venosa (L.) Hoffm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/kvd-myc-rw5
title: Ochrolechia tiroliensis (Erichsen) Hafellner & Türk

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/wqx-b9x-vvm
title: Pertusaria pupillaris (Nyl.) Th. Fr.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/dvf-cv6-2ef
title: Peltigera horizontalis (Huds.) Baumg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/dd2-ydh-1mh
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/dq0-ffb-6ve
title: Peltigera neckeri Hepp ex Müll. Arg.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.5281/zenodo.17085272
title: 2025 PG&E Energy Analytics Challenge: Electric Load Forecasting Datasets

description: Summary:  

This repository contains the datasets used in the 2025 PG&E Energy Analytics Challenge on Electricity Load Forecasting, co-organized by the IISE Energy Systems Division and the INFORMS Quality, Statistics, and Reliability Section, and graciously sponsored by the Pacific Gas & Electric Company (PG&E). 

The repository contains two files:





Train.xlsx: Contains three years of hourly electric loads from San Diego, California (Years 2020-2022), as well as exogenous weather information at five neighboring sites within the San Diego area.   




Test.xlsx: Contains one year of hourly electric loads from San Diego, California (Year 2023), as as well as exogenous weather information at five neighboring sites within the San Diego area.   



Background: 

This competition aimed to predict electricity loads for a specific location within the CAISO system. Accurate load forecasting is critical for managing electricity distribution within California’s diverse and dynamic energy market. Load patterns can vary significantly due to factors such as weather conditions, local supply and demand, and the mix of nearby energy generation sources.

 

During the competition, the specific location and the actual years were not disclosed to the participants. Participants were then asked to generate a year’s worth of load forecasts using historical load values and exogeneous weather information. Predictor data were not allowed to be taken from future time periods: When predicting the load values at a particular day, the model was allowed to only use predictor variable information from that time period or before. For example, if a team is predicting the load for Day 5 Hour 3 in Year 3, the model can only take in predictor values from Day 5 Hour 3 in Year 3, or before. Furthermore, during the competition, the load information for the test set (highlighted in yellow in the test data file) was reserved from all participants, who were asked to submit their predictions for the full year. 

 

This is the second offering of the PG&E Energy Analytics challenge, complementing the first offering in 2024 which focused on electricity price forecasting [Results of the 2024 challenge: Aziz Ezzat, A., Mansouri, M., Yildirim, M., & Fang, X. (2025). IISE PG&E Energy Analytics Challenge 2024: Forecasting day-ahead electricity prices. IISE Transactions, 1–13. https://doi.org/10.1080/24725854.2024.2447049].
DOI: 10.5281/zenodo.17085273
title: 2025 PG&E Energy Analytics Challenge: Electric Load Forecasting Datasets

description: Summary:  

This repository contains the datasets used in the 2025 PG&E Energy Analytics Challenge on Electricity Load Forecasting, co-organized by the IISE Energy Systems Division and the INFORMS Quality, Statistics, and Reliability Section, and graciously sponsored by the Pacific Gas & Electric Company (PG&E). 

The repository contains two files:





Train.xlsx: Contains three years of hourly electric loads from San Diego, California (Years 2020-2022), as well as exogenous weather information at five neighboring sites within the San Diego area.   




Test.xlsx: Contains one year of hourly electric loads from San Diego, California (Year 2023), as as well as exogenous weather information at five neighboring sites within the San Diego area.   



Background: 

This competition aimed to predict electricity loads for a specific location within the CAISO system. Accurate load forecasting is critical for managing electricity distribution within California’s diverse and dynamic energy market. Load patterns can vary significantly due to factors such as weather conditions, local supply and demand, and the mix of nearby energy generation sources.

 

During the competition, the specific location and the actual years were not disclosed to the participants. Participants were then asked to generate a year’s worth of load forecasts using historical load values and exogeneous weather information. Predictor data were not allowed to be taken from future time periods: When predicting the load values at a particular day, the model was allowed to only use predictor variable information from that time period or before. For example, if a team is predicting the load for Day 5 Hour 3 in Year 3, the model can only take in predictor values from Day 5 Hour 3 in Year 3, or before. Furthermore, during the competition, the load information for the test set (highlighted in yellow in the test data file) was reserved from all participants, who were asked to submit their predictions for the full year. 

 

This is the second offering of the PG&E Energy Analytics challenge, complementing the first offering in 2024 which focused on electricity price forecasting [Results of the 2024 challenge: Aziz Ezzat, A., Mansouri, M., Yildirim, M., & Fang, X. (2025). IISE PG&E Energy Analytics Challenge 2024: Forecasting day-ahead electricity prices. IISE Transactions, 1–13. https://doi.org/10.1080/24725854.2024.2447049].
DOI: 10.3535/6qf-h2j-pnn
title: Peltigera membranacea (Ach.) Nyl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.6yw4fk
title: Occurrence Download

description: A dataset containing 514968 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Observation.org, Nature data from around the World",
 "TaxonKey is one of (Bombus muscorum, Limosa limosa, Lasiommata megera)"
 ]
}

 The dataset includes 514968 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045630-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.