cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17184722
title: Nowe Objezierze stan. 22. Dokumentacja z badań wykopaliskowych w sezonie 2025.

description: Nowe Objezierze stan. 22 AZP 42-03/100

 

Dokumnetacja fotogrametryczna:

Zobrazowanie fotogrametryczne Wykop 6b

Rysunek Wykop 6bZobrazowanie fotogrametryczne. Profile obiektów 311-323

Zobrazowanie fotogrametryczne. Profile obiektów 311-323

Zobrazowanie fotogrametryczne. Plan ob. 317

Zobrazowanie fotogrametryczne. Plan ob. 320

Zobrazowanie fotogrametryczne. Plan ob. 320. Poziom 2

Zobrazowanie fotogrametryczne. Plan ob. 330

Zobrazowanie fotogrametryczne. Plan ob. 330. Poziom 2

Zobrazowanie fotogrametryczne. Plan ob. 332

Zobrazowanie fotogrametryczne. Plan ob. 332. Poziom 2

Zobrazowanie fotogrametryczne. Plan ob. 332. Poziom 3

Zobrazowanie fotogrametryczne. Plan ob. 341

Zobrazowanie fotogrametryczne. Plan ob. 341. Poziom 2

Zobrazowanie fotogrametryczne. Plan ob. 342

Zobrazowanie fotogrametryczne. Plan ob. 342. Poziom 2

Zobrazowanie fotogrametryczne. Plan ob. 343

Zobrazowanie fotogrametryczne. Plan ob. 343. Poziom 2
DOI: 10.15468/dl.w2qq3t
title: Occurrence Download

description: A dataset containing 4004 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Bryophytes of Vietnam (PHH Herbarium, Cryptogam Collection)"
 ]
}

 The dataset includes 4004 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008965-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4rn7ge
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Symphytum hidcotense",
 "Country is Belgium",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008966-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u4xc9x
title: Occurrence Download

description: A dataset containing 84 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Austria",
 "DatasetKey is naturbeobachtung.at",
 "Geometry POLYGON((16.2489 48.20941,16.29386 48.20941,16.29386 48.2436,16.2489 48.2436,16.2489 48.20941))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Squamata, Testudines, Amphibia)"
 ]
}

 The dataset includes 84 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008967-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dd.xmzcbt
title: Dataset generated from Esri tool

description: Derived dataset generated by Esri geoprocessing tool using GBIF API
DOI: 10.15468/dl.8ykyjb
title: Occurrence Download

description: A dataset containing 6253 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Paraserianthes lophantha",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6253 records from 144 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008968-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d4c39t
title: Occurrence Download

description: A dataset containing 54440 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ursus arctos"
 ]
}

 The dataset includes 54440 records from 336 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008929-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17175098
title: DS.StakeholderQuestionnaire_SQ.5

description: The dataset contains responses from a questionnaire, designed to collect expert perspectives on the adoption of collaborative robots across three domains (manufacturing, logistics, agriculture). Variables Q3 to Q11 record sociodemographic and background information, including gender, age, industrial sector, organization, role, and experience with collaborative robots. Open-ended questions in Q14 to Q24 capture qualitative feedback for each use case (UC1, UC2, UC3), focusing on technical issues, safety considerations, and ethical and social implications of cobot adoption. Q25_1 to Q26_11 correspond to the General Attitudes Toward Robots Scale (GAToRS; Koverola et al., 2022), a 20-item instrument with four subscales (Personal Positive, Personal Negative, Societal Positive, Societal Negative), all rated on a 5-point Likert scale. Q27_1 to Q28_7 correspond to the Trust Perception Scale – HRI (Schaefer, 2016), a 14-item scale measuring functionality, performance, safety, maintenance, and informativeness, also on a 5-point Likert scale. Q29_1 to Q29_4 correspond to the Perceived Safety Scale (Weiss et al., 2009), assessing fears of self-harm and harm to the cobot, perceived safety, and overall safety perceptions, likewise on a 5-point Likert scale.
DOI: 10.5281/zenodo.17175097
title: DS.StakeholderQuestionnaire_SQ.5

description: The dataset contains responses from a questionnaire, designed to collect expert perspectives on the adoption of collaborative robots across three domains (manufacturing, logistics, agriculture). Variables Q3 to Q11 record sociodemographic and background information, including gender, age, industrial sector, organization, role, and experience with collaborative robots. Open-ended questions in Q14 to Q24 capture qualitative feedback for each use case (UC1, UC2, UC3), focusing on technical issues, safety considerations, and ethical and social implications of cobot adoption. Q25_1 to Q26_11 correspond to the General Attitudes Toward Robots Scale (GAToRS; Koverola et al., 2022), a 20-item instrument with four subscales (Personal Positive, Personal Negative, Societal Positive, Societal Negative), all rated on a 5-point Likert scale. Q27_1 to Q28_7 correspond to the Trust Perception Scale – HRI (Schaefer, 2016), a 14-item scale measuring functionality, performance, safety, maintenance, and informativeness, also on a 5-point Likert scale. Q29_1 to Q29_4 correspond to the Perceived Safety Scale (Weiss et al., 2009), assessing fears of self-harm and harm to the cobot, perceived safety, and overall safety perceptions, likewise on a 5-point Likert scale.
DOI: 10.5281/zenodo.17164638
title: DS.UC3FocusGroup_UC3FG.4

description: The dataset consists of qualitative data in the form of a transcript from a focus group conducted with five experts from a leading wine cooperative in Trentino, as part of UC3. The transcript records participants’ reflections on innovation in viticulture, first impressions of the proposed robotic platform and exoskeleton, expected effects on workflows and teamwork, organizational aspects influencing adoption, and overall acceptance of collaborative solutions in agricultural contexts. The discussion includes concrete suggestions for improving the design, functionalities, and user experience of the proposed systems.
DOI: 10.5281/zenodo.17164639
title: DS.UC3FocusGroup_UC3FG.4

description: The dataset consists of qualitative data in the form of a transcript from a focus group conducted with five experts from a leading wine cooperative in Trentino, as part of UC3. The transcript records participants’ reflections on innovation in viticulture, first impressions of the proposed robotic platform and exoskeleton, expected effects on workflows and teamwork, organizational aspects influencing adoption, and overall acceptance of collaborative solutions in agricultural contexts. The discussion includes concrete suggestions for improving the design, functionalities, and user experience of the proposed systems.
DOI: 10.15468/dl.ehvs8c
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Heliotropium suaveolens",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008970-250920141307145/datasets/export for details.
DOI: 10.15468/dl.sc8hk8
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Heliotropium suaveolens",
 "Country is Belgium",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008969-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17164539
title: DS.UC2OcadoSurvey_UC2OS.3

description: The dataset contains responses from an expert survey conducted with Ocado employees to investigate perceptions of collaborative robotics in logistics warehouses. The prefixes Q1–Q16 identify the items included in the questionnaire. Q1 measures interest in scientific and technological innovations on a 3-point scale, Q2 captures general opinions about robotics on a 5-point Likert scale, and Q3 records previous experience with robotic systems using a 3-option categorical response. Q4_1 to Q4_6 refer to perceived benefits, Q5_1 to Q5_5 refer to perceived risks, and Q6_1 to Q6_8 address acceptability and trust; all these items were rated on 5-point Likert scales. Q7, Q15, and Q16 collect demographic information on gender, age range, and job role. The dataset also contains system-generated variables from the Qualtrics platform (e.g., start and end times, IP address, response ID).
DOI: 10.5281/zenodo.17164540
title: DS.UC2OcadoSurvey_UC2OS.3

description: The dataset contains responses from an expert survey conducted with Ocado employees to investigate perceptions of collaborative robotics in logistics warehouses. The prefixes Q1–Q16 identify the items included in the questionnaire. Q1 measures interest in scientific and technological innovations on a 3-point scale, Q2 captures general opinions about robotics on a 5-point Likert scale, and Q3 records previous experience with robotic systems using a 3-option categorical response. Q4_1 to Q4_6 refer to perceived benefits, Q5_1 to Q5_5 refer to perceived risks, and Q6_1 to Q6_8 address acceptability and trust; all these items were rated on 5-point Likert scales. Q7, Q15, and Q16 collect demographic information on gender, age range, and job role. The dataset also contains system-generated variables from the Qualtrics platform (e.g., start and end times, IP address, response ID).
DOI: 10.15468/dl.57gaxg
title: Occurrence Download

description: A dataset containing 189555 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Switzerland",
 "DatasetKey is iNaturalist Research-grade Observations",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 189555 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008945-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17164516
title: DS.UC1FocusGroup_FGUC1.2

description: The dataset consists of qualitative data in the form of a transcript from a focus group conducted with workers and experts from CRF to collect early feedback on collaborative technologies developed in UC1. The file contains the verbatim discussion text, in which participants expressed their perceptions, expectations, and concerns regarding the introduction of a collaborative robot and a passive upper-limb exoskeleton in automotive assembly tasks. The content is organized thematically, covering perspectives on technological innovation, first impressions of the proposed solutions, perceived and physical safety, expectations regarding human–robot interaction, comfort, trust, usability, acceptance, and the potential impact on work organization. The transcript also includes participants’ concrete suggestions for improving the design and integration of the technologies
DOI: 10.5281/zenodo.17164517
title: DS.UC1FocusGroup_FGUC1.2

description: The dataset consists of qualitative data in the form of a transcript from a focus group conducted with workers and experts from CRF to collect early feedback on collaborative technologies developed in UC1. The file contains the verbatim discussion text, in which participants expressed their perceptions, expectations, and concerns regarding the introduction of a collaborative robot and a passive upper-limb exoskeleton in automotive assembly tasks. The content is organized thematically, covering perspectives on technological innovation, first impressions of the proposed solutions, perceived and physical safety, expectations regarding human–robot interaction, comfort, trust, usability, acceptance, and the potential impact on work organization. The transcript also includes participants’ concrete suggestions for improving the design and integration of the technologies
DOI: 10.5281/zenodo.17164480
title: DS.UC1ExperimentalTest_UC1ET.2

description: The dataset contains self-report data collected during the experimental testing of the collaborative solutions developed in UC1 of the SESTOSENSO project with human participants. The prefixes ScenAB, ScenAB+C, ScenAB+E, ScenAB+C+E, ScenAB+C Mov, and ScenAB+C+E Mov identify the six experimental conditions under which participants performed the assembly tasks. Each block of variables with the same prefix refers to one specific condition. For each condition, the dataset includes repeated measures of standardized self-report questionnaires: NASA_1 to NASA_6 correspond to the six NASA-TLX dimensions of workload (mental demand, physical demand, temporal demand, performance, effort, frustration); SUS_x refer to the System Usability Scale items, included in all conditions except the manual baseline; ACC_x correspond to the Technology Acceptance Scale items, also excluded in the manual baseline; TRUT_x represent the Trust Toward Robots items, included only in conditions involving the cobot; and Comfort_1–2 are two ad hoc items measuring perceived comfort, included only in conditions with the exoskeleton. The dataset also includes demographic and background variables such as gender, year of birth, level of education, and a free-text field for final comments.
DOI: 10.5281/zenodo.17164481
title: DS.UC1ExperimentalTest_UC1ET.2

description: The dataset contains self-report data collected during the experimental testing of the collaborative solutions developed in UC1 of the SESTOSENSO project with human participants. The prefixes ScenAB, ScenAB+C, ScenAB+E, ScenAB+C+E, ScenAB+C Mov, and ScenAB+C+E Mov identify the six experimental conditions under which participants performed the assembly tasks. Each block of variables with the same prefix refers to one specific condition. For each condition, the dataset includes repeated measures of standardized self-report questionnaires: NASA_1 to NASA_6 correspond to the six NASA-TLX dimensions of workload (mental demand, physical demand, temporal demand, performance, effort, frustration); SUS_x refer to the System Usability Scale items, included in all conditions except the manual baseline; ACC_x correspond to the Technology Acceptance Scale items, also excluded in the manual baseline; TRUT_x represent the Trust Toward Robots items, included only in conditions involving the cobot; and Comfort_1–2 are two ad hoc items measuring perceived comfort, included only in conditions with the exoskeleton. The dataset also includes demographic and background variables such as gender, year of birth, level of education, and a free-text field for final comments.
DOI: 10.48420/30178552
title: Emulsification Drop Size Distribution Dataset

description: All the experimental data was undertaken in cylindrical vessel of diameter 1.37×10<sup>–1</sup> m with a six- inclined 45° bladed pitched turbine of diameter 4.83×10<sup>–2</sup> m and four baffles of 1.37×10<sup>–2</sup> m. The agitator clearance was a third of the vessel diameter and the height of the liquid was equal to the tank diameter. The emulsification time for all experiments was 24 hours, which has been verified as a steady-state value. At least three samples were analysed for each emulsion to makes sure that experiments produced consistent results.200 Fluid XX Silicone Oil (dimethyl siloxane, DowCorning, MI) where “XX” stands for their nominal dynamicviscosity in centistokes [cSt]. SiOils are available over a wide range of viscosity, their shear viscosity is independent of shear rate and their densities and interfacial tensions are similar for most of them. The densities were taken as given by the provider. The viscosities were measured using a DV2T Viscometer (Brookﬁeld Vicometers, Essex, UK). As continuous phase this varied from used a 1.0 wt % sodium laureth sulfate (SLES) aqueous solution, concentrations of Sweet Glucose Syrup M01632 (Brenntag, Mülheim, Germany) aqueous solutions with 1.0 wt% SLES, and water/ethanol mixes. This is reflected in the viscosity of the continuous phase and the interfacial tension.The DSD were obtained using an off-line laser diffraction particle size analyzer, the Mastersizer 3000 (Malvern Instruments, Malvern, UK), which allows measurement of drops in the 10<sup>–3</sup> µm to 3×10<sup>3</sup> µm range. The data produced from the Mastersizer 3000 is a DSD represented as a cumulative volume fraction distribution, i.e. all the output values add up to a fraction of 100%.
DOI: 10.48420/30178552.v1
title: Emulsification Drop Size Distribution Dataset

description: All the experimental data was undertaken in cylindrical vessel of diameter 1.37×10<sup>–1</sup> m with a six- inclined 45° bladed pitched turbine of diameter 4.83×10<sup>–2</sup> m and four baffles of 1.37×10<sup>–2</sup> m. The agitator clearance was a third of the vessel diameter and the height of the liquid was equal to the tank diameter. The emulsification time for all experiments was 24 hours, which has been verified as a steady-state value. At least three samples were analysed for each emulsion to makes sure that experiments produced consistent results.200 Fluid XX Silicone Oil (dimethyl siloxane, DowCorning, MI) where “XX” stands for their nominal dynamicviscosity in centistokes [cSt]. SiOils are available over a wide range of viscosity, their shear viscosity is independent of shear rate and their densities and interfacial tensions are similar for most of them. The densities were taken as given by the provider. The viscosities were measured using a DV2T Viscometer (Brookﬁeld Vicometers, Essex, UK). As continuous phase this varied from used a 1.0 wt % sodium laureth sulfate (SLES) aqueous solution, concentrations of Sweet Glucose Syrup M01632 (Brenntag, Mülheim, Germany) aqueous solutions with 1.0 wt% SLES, and water/ethanol mixes. This is reflected in the viscosity of the continuous phase and the interfacial tension.The DSD were obtained using an off-line laser diffraction particle size analyzer, the Mastersizer 3000 (Malvern Instruments, Malvern, UK), which allows measurement of drops in the 10<sup>–3</sup> µm to 3×10<sup>3</sup> µm range. The data produced from the Mastersizer 3000 is a DSD represented as a cumulative volume fraction distribution, i.e. all the output values add up to a fraction of 100%.
DOI: 10.5281/zenodo.17160250
title: DS.GuidelinesSurvey_GS.1

description: The dataset contains data from an expert survey conducted to evaluate organizational guidelines designed to support the safe, effective, and human-centered integration of collaborative robots in industrial settings. The prefixes G1, G2, etc. identify the guidelines evaluated in the expert survey, with each block of variables referring to one specific guideline. For each guideline, the dataset includes variables on impact (three items measuring the perceived effect on safety, workers’ psychological well-being, and performance), feasibility (two items assessing the perceived technical and organizational feasibility of implementation), and cost (one item estimating the expected cost of implementation on an ordinal scale from very low to very high). Each guideline contains open-text fields: three items (Implementation_16, Implementation_17, Implementation_18) in which experts proposed possible implementation solutions, one item (KPIs) where experts suggested assessment methods or key performance indicators to evaluate effectiveness, and one item (Suggestions) where they provided further comments or recommendations. The dataset also includes demographic and background information about respondents, such as gender, age, area of expertise, and self-rated expertise in human–robot collaboration.
DOI: 10.5281/zenodo.17160251
title: DS.GuidelinesSurvey_GS.1

description: The dataset contains data from an expert survey conducted to evaluate organizational guidelines designed to support the safe, effective, and human-centered integration of collaborative robots in industrial settings. The prefixes G1, G2, etc. identify the guidelines evaluated in the expert survey, with each block of variables referring to one specific guideline. For each guideline, the dataset includes variables on impact (three items measuring the perceived effect on safety, workers’ psychological well-being, and performance), feasibility (two items assessing the perceived technical and organizational feasibility of implementation), and cost (one item estimating the expected cost of implementation on an ordinal scale from very low to very high). Each guideline contains open-text fields: three items (Implementation_16, Implementation_17, Implementation_18) in which experts proposed possible implementation solutions, one item (KPIs) where experts suggested assessment methods or key performance indicators to evaluate effectiveness, and one item (Suggestions) where they provided further comments or recommendations. The dataset also includes demographic and background information about respondents, such as gender, age, area of expertise, and self-rated expertise in human–robot collaboration.
DOI: 10.15468/dl.bwnct7
title: Occurrence Download

description: A dataset containing 497 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Euschistus heros"
 ]
}

 The dataset includes 497 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008973-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mvnv7a
title: Occurrence Download

description: A dataset containing 311 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Canthium vulgare"
 ]
}

 The dataset includes 311 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008974-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2xbzj5
title: Occurrence Download

description: A dataset containing 411 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chusquea subtessellata Hitchc."
 ]
}

 The dataset includes 411 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050170-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.