cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13131210
title: Linked collectors and determiners for: University of Nevada, Reno (UNR) Fish specimens (Arctos).

description: Natural history specimen data linked to collectors and determiners held within, "University of Nevada, Reno (UNR) Fish specimens (Arctos)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/c316dd38-04ee-4505-acab-4965176edb7b using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/c316dd38-04ee-4505-acab-4965176edb7b. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10510601
title: Linked collectors and determiners for: University of Nevada, Reno (UNR) Fish specimens (Arctos).

description: Natural history specimen data linked to collectors and determiners held within, "University of Nevada, Reno (UNR) Fish specimens (Arctos)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/c316dd38-04ee-4505-acab-4965176edb7b using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/c316dd38-04ee-4505-acab-4965176edb7b. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10597808
title: Linked collectors and determiners for: University of Nevada, Reno (UNR) Fish specimens (Arctos).

description: Natural history specimen data linked to collectors and determiners held within, "University of Nevada, Reno (UNR) Fish specimens (Arctos)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/c316dd38-04ee-4505-acab-4965176edb7b using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/c316dd38-04ee-4505-acab-4965176edb7b. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10882248
title: Linked collectors and determiners for: University of Nevada, Reno (UNR) Fish specimens (Arctos).

description: Natural history specimen data linked to collectors and determiners held within, "University of Nevada, Reno (UNR) Fish specimens (Arctos)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/c316dd38-04ee-4505-acab-4965176edb7b using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/c316dd38-04ee-4505-acab-4965176edb7b. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.11057015
title: Linked collectors and determiners for: University of Nevada, Reno (UNR) Fish specimens (Arctos).

description: Natural history specimen data linked to collectors and determiners held within, "University of Nevada, Reno (UNR) Fish specimens (Arctos)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/c316dd38-04ee-4505-acab-4965176edb7b using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/c316dd38-04ee-4505-acab-4965176edb7b. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.12622328
title: Linked collectors and determiners for: University of Nevada, Reno (UNR) Fish specimens (Arctos).

description: Natural history specimen data linked to collectors and determiners held within, "University of Nevada, Reno (UNR) Fish specimens (Arctos)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/c316dd38-04ee-4505-acab-4965176edb7b using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/c316dd38-04ee-4505-acab-4965176edb7b. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.13979808
title: Linked collectors and determiners for: University of Nevada, Reno (UNR) Fish specimens (Arctos).

description: Natural history specimen data linked to collectors and determiners held within, "University of Nevada, Reno (UNR) Fish specimens (Arctos)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/c316dd38-04ee-4505-acab-4965176edb7b using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/c316dd38-04ee-4505-acab-4965176edb7b. Formatted as a Frictionless Data package.
DOI: 10.3886/7c44-nm35
title: Nicaragua Compact - Transportation: Traffic Counts and Vehicle Operating Cost Data
DOI: 10.3886/6tsb-9a86
title: Nicaragua Compact - Transportation: Traffic Counts and Vehicle Operating Cost Data
DOI: 10.15468/dl.zxwtq5
title: Occurrence Download

description: A dataset containing 1262 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Megachile pyrenaea Pérez, 1890"
 ]
}

 The dataset includes 1262 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039578-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zcve8n
title: Occurrence Download

description: A dataset containing 95469 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "StateProvince is 海南"
 ]
}

 The dataset includes 95469 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039550-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29307401
title: A_Systematic_Literature_Review_on_Dark_Sides_of_Digitalisation_in_Higher_Education_datasources.xlsx

description: <b>A Systematic Literature Review on Dark Sides of Digitalisation in Higher Education</b><b>Is the Academic Community Complicit in Hiding the Darkest Sides?</b>Digitalisation is assumed to give higher education more reach. Critical perspectives have emerged in a limited and fragmented way. This paper seeks to bring greater coherence to the research on dark(er) sides of digitalisation, particularly in the post-COVID-19 context. Higher education institutions were forced to deliver Emergency Remote Teaching. This has led to a focus on the experienced lack of basic technical requirements and deficiencies of digital learning solutions. This narrow-focused and operational approach has resulted in a biased view on solving the problem from a technocratic perspective, leaving less manageable darker sides overseen. In a monopolised market, learning analytics empower Big Tech and serve neoliberal governments. Profiling from surveillance practices makes students buyers of technology instead of academic learners. Risks related to the proliferation of digitalisation with built-in dark sides demand for further research. It is a fundamental problem when the academic community contributes to an overly optimistic view.Research of dark sides is fragmented and narrow-focused, mainly on managing the divides between the haves and the have nots (Azionya & Nhedzi, 2021; Colpitts et al., 2021; Koran & Sarnou, 2022; Sia et al., 2023; Song, 2024; Sumra et al., 2022; Tetteh et al., 2023; Timmis et al., 2016). Resolving these divides might cause a proliferation of DLSs, reenforcing, amplifying, or proliferating conceptually built-in darker sides. This review is based on systematic and critical analyses of former research literature, with a focus on the trends and viewpoints and approaches of researchers. The research objective was to determine which dark sides have been overlooked or would need a broader perspective.This led to the following two research questions in advance.Which clusters can be identified in the literature on the dark sides of digitalisation in higher education?And, to what extent are these dark sides related to technofeudalism and/or technological solutionism?<br>
DOI: 10.6084/m9.figshare.29307401.v1
title: A_Systematic_Literature_Review_on_Dark_Sides_of_Digitalisation_in_Higher_Education_datasources.xlsx

description: <b>A Systematic Literature Review on Dark Sides of Digitalisation in Higher Education</b><b>Is the Academic Community Complicit in Hiding the Darkest Sides?</b>Digitalisation is assumed to give higher education more reach. Critical perspectives have emerged in a limited and fragmented way. This paper seeks to bring greater coherence to the research on dark(er) sides of digitalisation, particularly in the post-COVID-19 context. Higher education institutions were forced to deliver Emergency Remote Teaching. This has led to a focus on the experienced lack of basic technical requirements and deficiencies of digital learning solutions. This narrow-focused and operational approach has resulted in a biased view on solving the problem from a technocratic perspective, leaving less manageable darker sides overseen. In a monopolised market, learning analytics empower Big Tech and serve neoliberal governments. Profiling from surveillance practices makes students buyers of technology instead of academic learners. Risks related to the proliferation of digitalisation with built-in dark sides demand for further research. It is a fundamental problem when the academic community contributes to an overly optimistic view.Research of dark sides is fragmented and narrow-focused, mainly on managing the divides between the haves and the have nots (Azionya & Nhedzi, 2021; Colpitts et al., 2021; Koran & Sarnou, 2022; Sia et al., 2023; Song, 2024; Sumra et al., 2022; Tetteh et al., 2023; Timmis et al., 2016). Resolving these divides might cause a proliferation of DLSs, reenforcing, amplifying, or proliferating conceptually built-in darker sides. This review is based on systematic and critical analyses of former research literature, with a focus on the trends and viewpoints and approaches of researchers. The research objective was to determine which dark sides have been overlooked or would need a broader perspective.This led to the following two research questions in advance.Which clusters can be identified in the literature on the dark sides of digitalisation in higher education?And, to what extent are these dark sides related to technofeudalism and/or technological solutionism?<br>
DOI: 10.15468/dl.mfjjya
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Iowa State University, Ada Hayden Herbarium - Bryophytes",
 "Country is Croatia"
 ]
}

 The dataset includes 29 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039585-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/12145919
title: Detect and Correct Pixelated Images
DOI: 10.15468/dl.rvm7kk
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Rhizocarpon cookeanum H.Magn."
 ]
}

 The dataset includes 45 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039579-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vqaxyz
title: Occurrence Download

description: A dataset containing 116 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is SDNHM Marine Invertebrate Collection",
 "Country is Croatia"
 ]
}

 The dataset includes 116 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039581-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.54gehn
title: Occurrence Download

description: A dataset containing 8417 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Megachile rotundata (Fabricius, 1787)"
 ]
}

 The dataset includes 8417 records from 157 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039582-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/12146200
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.e7m2zk
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Jamesbrittenia montana (Diels) Hilliard",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((35.5808 -24.13,35.5909 -24.0715,30.5701 -24.0715,30.5701 -28.5786,32.4847 -28.5786,32.55 -28.5222,33.0346 -26.8668,32.9741 -26.7838,33.0415 -26.059,32.9304 -26.0011,32.7994 -26.1281,32.6834 -26.0015,32.813 -25.8728,32.8513 -25.7166,33.3048 -25.3731,35.1489 -24.6699,35.5808 -24.13))"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039584-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7924/r4vm4hd42
title: Data from: An engineered prodrug selectively suppresses β-lactam resistant bacteria in a mixed microbial setting

description: Transformed E. coli were grown overnight at 37 °C on Luria Bertani Broth (Lennox) (LB) agar plates containing the appropriate antibiotics (50 μg/mL kanamycin and/or 100 μg/mL ampicillin). A single colony was used to inoculate 5 mL of liquid LB with the appropriate antibiotics and grown at 37 °C and 200 rpm for 20 h. Cells were harvested by centrifugation (4000 rcf, 5 min, rt), resuspended in 0.5 mL of ultrapure water, and DNA was isolated using Zymo Research Zyppy Plasmid Miniprep Kit. Purified DNA was sent to plasmidsaurus for whole-plasmid Oxford Nanopore sequencing. 

.dna files of plasmid maps can be opened with SnapGene Viewer, a freely accessible software. <https://www.snapgene.com/snapgene-viewer> (accessed 2025-01-30)
DOI: 10.15468/dl.deyayp
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Spécimens d'herbiers de G. Fenoul (FEN)",
 "Country is Croatia"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039587-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rve3cj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amphora inariensis Krammer",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((30.5701 -24.0715,25.5395 -24.0715,25.5395 -28.5786,30.5701 -28.5786,30.5701 -24.0715))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039588-250525065834625/datasets/export for details.
DOI: 10.15468/dl.3stsc5
title: Occurrence Download

description: A dataset containing 120 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Terrestrial and limnic invertebrates systematic collection, NTNU University Museum",
 "Country is Croatia"
 ]
}

 The dataset includes 120 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039592-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.usv2cz
title: Occurrence Download

description: A dataset containing 18333 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Megachile willughbiella (Kirby, 1802)"
 ]
}

 The dataset includes 18333 records from 237 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039590-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yeqhsn
title: Occurrence Download

description: A dataset containing 6983 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Megachile versicolor Smith, 1844"
 ]
}

 The dataset includes 6983 records from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039589-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9956n7
title: Occurrence Download

description: A dataset containing 254 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "OccurrenceStatus is Present",
 "TaxonKey is Ateles fusciceps Gray, 1866"
 ]
}

 The dataset includes 254 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039591-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15447675
title: Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches (Replication Package Part 2: Linux dataset)

description: The Replication Package of

"Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches"

Part 2 (LINUX Dataset)



This repository includes:



Code.zip that contains the codes to replicate some parts of this study:a. 1_generate_datasets implements our methodology to generate the datasets.b. 2_run_models runs the ML models during the evaluation.c. 3_result_replication generates charts presented in the paper from the ML evaluation results.

Datasets.zip that contain 2 folders:a. original datasets: 1 from NVD Vuldeepecker and 3 extracted from BigVul.



b. LINUX datasets: train, validation, test sets for each time of observation extracted using our methodology from BigVul dataset for project linux.



Pretrained-models.zip that we generated during our evaluation (3 test results for each time point in the timeline [2011-2019]).

Results.zip of our evaluation, the folder ALL contains the overall results and other folders are results by model.





Documentations



INSTALL.pdf : how to install the codes

README.pdf: readme file

REQUIREMENTS.pdf: hardware and software requirements

STATUS.pdf : status for artifact submission

LICENSE.pdf: the license of this artifact

PAPER.pdf: the camera-ready version of the paper


UPDATED version 4- added a GLOBAL_README.md which contains the 3 stages and how they are connected to each other- updated LineVul.ipynb: import AdamW from torch.optim instead of transformers- updated README.md in Code2Vec with the prerequisites of Java to run gradlew for astminer




UPDATED version 5- updated CodeBert.ipynb: import AdamW from torch.optim instead of transformers


Please refer to the following repositories for the other datasets and pre-trained models:

- Part 1 NVD Vuldeeepecker : https://doi.org/10.5281/zenodo.8207883

- Part 3 OPENSSL : https://doi.org/10.5281/zenodo.10966117

- Part 4 POPPLER : https://doi.org/10.5281/zenodo.14713143

 

This work was partly funded by the EU under the H2020 Program AssureMOSS (Grant n. 952647) and the Horizon Europe Program Sec4AI4Sec (Grant n. 101120393), by the Italian Ministry of University and Research (MUR) under the P.N.R.R. – NextGenerationEU grant n.\ PE00000014 (SERICS subproject COVERT), and by the Dutch Research Council (NWO) under the grant NWA.1215.18.006 (Theseus) and grant KIC1.VE01.20.004 (HEWSTI).
DOI: 10.5281/zenodo.10960662
title: Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches (Replication Package Part 2: Linux dataset)

description: The Replication Package of

"Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches"

Part 2 (LINUX Dataset)



This repository includes:



Code.zip that contains the codes to replicate some parts of this study:a. 1_generate_datasets implements our methodology to generate the datasets.b. 2_run_models runs the ML models during the evaluation.c. 3_result_replication generates charts presented in the paper from the ML evaluation results.

Datasets.zip that contain 2 folders:a. original datasets: 1 from NVD Vuldeepecker and 3 extracted from BigVul.



b. LINUX datasets: train, validation, test sets for each time of observation extracted using our methodology from BigVul dataset for project linux.



Pretrained-models.zip that we generated during our evaluation (3 test results for each time point in the timeline [2011-2019]).

Results.zip of our evaluation, the folder ALL contains the overall results and other folders are results by model.





Documentations



INSTALL.pdf : how to install the codes

README.pdf: readme file

REQUIREMENTS.pdf: hardware and software requirements

STATUS.pdf : status for artifact submission

LICENSE.pdf: the license of this artifact

PAPER.pdf: the camera-ready version of the paper


UPDATED version 4- added a GLOBAL_README.md which contains the 3 stages and how they are connected to each other- updated LineVul.ipynb: import AdamW from torch.optim instead of transformers- updated README.md in Code2Vec with the prerequisites of Java to run gradlew for astminer




UPDATED version 5- updated CodeBert.ipynb: import AdamW from torch.optim instead of transformers


Please refer to the following repositories for the other datasets and pre-trained models:

- Part 1 NVD Vuldeeepecker : https://doi.org/10.5281/zenodo.8207883

- Part 3 OPENSSL : https://doi.org/10.5281/zenodo.10966117

- Part 4 POPPLER : https://doi.org/10.5281/zenodo.14713143

 

This work was partly funded by the EU under the H2020 Program AssureMOSS (Grant n. 952647) and the Horizon Europe Program Sec4AI4Sec (Grant n. 101120393), by the Italian Ministry of University and Research (MUR) under the P.N.R.R. – NextGenerationEU grant n.\ PE00000014 (SERICS subproject COVERT), and by the Dutch Research Council (NWO) under the grant NWA.1215.18.006 (Theseus) and grant KIC1.VE01.20.004 (HEWSTI).
DOI: 10.15468/dl.f7ge6g
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is FSC - Fresno State Herbarium",
 "Country is Croatia"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039593-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.55fdmz
title: Occurrence Download

description: A dataset containing 30774099 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 30774099 records from 2701 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039530-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.